University of Maribor Faculty of Energy Technology Volume 7 / Issue 4 NOVEMBER 2014 www.fe.um.si/en/jet.html Journal of ENERGY TECHNOLOGY ✓—____л Ш VOLUME 7 / Issue 4 Revija Journal of Energy Technology (JET) je indeksirana v naslednjih bazah: INSPEC©, Cambridge Scientific Abstracts: Abstracts in New Technologies and Engineering (CSA ANTE), ProQuest's Technology Research Database. The Journal of Energy Technology (JET) is indexed and abstracted in the following databases: INSPEC©, Cambridge Scientific Abstracts: Abstracts in New Technologies and Engineering (CSA ANTE), ProQuest's Technology Research Database. . /_____ ш JOURNAL OF ENERGY TECHNOLOGY Ustanovitelj / FOUNDER Fakulteta za energetiko, UNIVERZA V MARIBORU / FACULTY OF ENERGY TECHNOLOGY, UNIVERSITY OF MARIBOR Izdajatelj / PUBLISHER Fakulteta za energetiko, UNIVERZA V MARIBORU / FACULTY OF ENERGY TECHNOLOGY, UNIVERSITY OF MARIBOR Odgovorni urednik / EDITOR-IN-CHIEF Andrej PREDIN Uredniki / CO-EDITORS Jurij AVSEC Miralem HADŽISELIMOVIĆ Gorazd HREN Peter VIRTIČ Izdajateljski svet in uredniški odbor / PUBLISHING COUNCIL AND EDITORIAL BOARD Zasl. prof. dr. Dali ĐONLAGIĆ, Univerza v Mariboru, Slovenija, predsednik / University of Maribor, Slovenia, President Prof. dr. Jurij AVSEC, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Zasl. prof. dr. Bruno CVIKL, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. ddr. Denis ĐONLAGIĆ, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. dr. Danilo FERETIĆ, Sveučilište u Zagrebu, Hrvaška / University in Zagreb, Croatia Doc. dr. Željko HEDERIĆ, Sveučilište Josipa Jurja Strossmayera u Osijeku, Hrvatska / Josip Juraj Strossmayer University Osijek, Croatia Izr. prof. dr. Miralem HADŽISELIMOVIĆ, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Doc. dr. Gorazd HREN, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. dr. Roman KLASINC, Technische Universität Graz, Avstrija / Graz University Of Technology, Austria Prof. dr. Ivan Aleksander KODELI, Institut Jožef Stefan, Slovenija / Jožef Stefan Institute, Slovenia Prof. dr. Alfred LEIPERTZ, Universität Erlangen, Nemčija / University of Erlangen, Germany Prof. dr. Branimir MATIJAŠEVIČ, Sveučilište u Zagrebu, Hrvaška / University of Zagreb, Croatia Prof. dr. Borut MAVKO, Inštitut Jožef Stefan, Slovenija / Jozef Stefan Institute, Slovenia Prof. dr. Matej MENCINGER, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. dr. Greg NATERER, University of Ontario, Kanada / University of Ontario, Canada Prof. dr. Enrico NOBILE, Università degli Studi di Trieste, Italia / University of Trieste, Italy Prof. dr. Andrej PREDIN, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. dr. Aleksandar SALJNIKOV, Univerza Beograd, Srbija / University of Beograd, Serbia Prof. dr. Brane ŠIROK, Univerza v Ljubljani, Slovenija / University of Ljubljana, Slovenia Doc. dr. Andrej TRKOV, Institut Jožef Stefan, Slovenija / Jožef Stefan Institute, Slovenia Izr. prof. dr. Peter VIRTIČ, Univerza v Mariboru, Slovenija / University of Maribor, Slovenia Prof. dr. Koichi WATANABE, KEIO University, Japonska / KEIO University, Japan Prof. dr. Mykhailo ZAGIRNYAK, Kremenchuk Mykhailo Ostrohradskyi National University, Ukrajina / Kremenchuk Mykhailo Ostrohradskyi National University, Ukraine, Tehniška podpora / TECHNICAL SUPPORT Katja BOGOVČIČ, Janko OMERZU Izhajanje revije / PUBLISHING Revija izhaja štirikrat letno v nakladi 150 izvodov. Članki so dostopni na spletni strani revije -www.fe.um.si/si/jet.html / The journal is published four times a year. Articles are available at the journal's home page - www.fe.um.si/en/jet.html. Cena posameznega izvoda revije (brez DDV) / Price per issue (VAT not included in price): 50,00 EUR Informacije o naročninah / Subscription information: http://www.fe.um.si/en/jet/ subscriptions.html Lektoriranje / LANGUAGE EDITING Terry T. JACKSON Oblikovanje in tisk / DESIGN AND PRINT Fotografika, Boštjan Colarič s.p. Oblikovanje revije in znaka revije / JOURNAL AND LOGO DESIGN Andrej PREDIN Ustanovni urednik / FOUNDING EDITOR Andrej PREDIN Izdajanje revije JET finančno podpira Javna agencija za raziskovalno dejavnost Republike Slovenije iz sredstev državnega proračuna iz naslova razpisa za sofinanciranje domačih znanstvenih periodičnih publikacij / The Journal of Energy Technology is co-financed by the Slovenian Research Agency. Ali je že napočil čas za nov korak v energetiki? Zadnja umetno izzvana ekonomska (monetarna?) svetovna kriza je dobila nove odseve predvsem na družbenih, socialnih, kulturnih področjih in konec koncev tudi na energetskem področju. Predsedniki vlad ne najdejo poti, gospodarstveniki tarnajo in tavajo v zaprtem krogu države, kultura se izgublja (ali utaplja?), apatija ljudi je vse večja. Seveda ni nič čudnega, da se vse to reflektira tudi na našem energetskem področju. Nič čudnega, ko pa vsak dan iz medijev slišimo samo banalne novice, kako je kdo kaj ukradel, kako si je človek sodil sam, ker je storil moralni prekršek, mediji pa so z največjim veseljem neusmiljeno drezali vanj... In seveda o našem »Slovenskem zlatem dimniku«, ki je presegel vse meje razumnosti, ali če želite človečnosti, ko na eni strani nekateri nimajo kaj za v usta, na drugi pa se nekateri sprenevedajo, od kod jim poldrugi milijon na bančnem kontu ali v sefu? Da, naš zlati dimnik je požrl enormna sredstva, ki bi jih lahko bistveno bolj preudarno naložili v druge, tehnološko bolj napredne veje energetike in bi bili tako lahko vzor za napredno družbo, ki odpira nov korak v energetiki s tem, da se že končno enkrat oddalji od »ogljikovega« lobija in pretrga dosedanjo odvisnost od le-tega. Ne, žal tudi pri nas še vedno zmaguje ta lobi. Še vedno smo »jahajoča družba«, v kateri šteje le tisti, ki je najvišji v jahajoči piramidi, pravzaprav enako, kot v dvajsetih letih zgodnjega kapitalizma v Združenih državah Amerike. Kot noji še zmeraj rinemo z glavo v pesek in si zatiskamo oči, zavedajoč se dejstva, da je denarja, hrane in energije na svetu dovolj za vse, le porazdelitev šepa. To je že daleč nazaj ugotovil naš Nikola Tesla, pa ga še danes ne želimo (nočemo) razumeti. Nikola je razumel, da vsa energija prihaja od našega sonca, ki ne more biti zasebno (hvala bogu). Res je da še danes koristimo najbolj primitivne oblike (premog, nafta, plin, ...), za katere pa smo si enotni (vsaj upam tako), da trajnostno gledano onesnažujejo naš svet, ki ga imamo samo »v najemu« od naših vnukov. A ni že skrajni čas, da se zamislimo kaj bodo naši vnuki mislili o nas? Morda pa z novo vlado vendarle napravimo korak naprej tudi na energetskem področju Slovenije. Andrej PREDIN Is it already time for a new direction in the energy sector? The recent artificially induced economic (monetary?) global crisis has given rise to new reflections, especially on the social and cultural fields as well as, ultimately, on the energy field. Politicians cannot find the way out, economists complain and wander about seeking a state-based solution, culture is being lost (or drowning), and the apathy of people is increasing; consequently, it is not surprising that all this is also reflected in the energy field, especially considering that we daily hear from the media just predictable news about how someone stole something, how someone should be judged because of an alleged moral offense (and the media have the greatest pleasure in reporting this) and of course about our 'Slovenian golden chimney', which has exceeded all limits of reasonableness, or if you want also all limits of humanity. On one hand, some do not have anything to eat, when on the other, some pretend that they do not know where the half million in their bank account or safe came from. Yes, our golden chimney has consumed enormous resources that could be much better invested in the other, more technologically advanced branches of electric energy production. If we do so, we can be an excellent example of an advanced society, which opens new directions in the energy field. This would finally be the path away from the so-called carbon lobby would cut society's the dependence on it. Unfortunately, the carbon lobby is still winning in our country. We are still 'pyramid society' in which only those who are at the highest level have rights. We still live like in the early years of capitalism in the United States. Like ostriches still putting their head in the sand, we shut our eyes, mindful of the fact that the money, food and energy in the world are enough for all, but only distribution has failed. Nikola Tesla knew this to be true in his time, but we still do not want to accept it, or want to understand it. Tesla understood that all of our energy comes from the sun, which cannot be privatized (thank goodness). It remains true that we use more primitive forms of energy sources (coal, oil, gas, etc.) because of its simple use (via simple technology). However, I do hope that we all know that these technologies have a serious impact on the environment that we have only rented from of our grandchildren. Is it not already the right time to imagine what will our grandchildren think about us? Perhaps we will have success with the new Slovenian government and also step forward in the field of energy. Andrej PREDIN Table of Contents / Kazalo Numerical analysis of an axial flow fan: Ansys vs SolidWorks/ Numerična analiza aksialnega ventilatorja: Ansys in SolidWorks Igor Ščuri, Marko Pezdevšek, Igor Spaseski, Matej Fike, Gorazd Hren...............11 Large hydro power plants in Slovenia/ Velike hidroelektrarne v Sloveniji Ivana Tršelič................................................21 Stability assessment in a power system control centre/ Ocene stabilnosti v nadzornem centru vodenja elektroenergetskega sistema Lajos Jozsa, Vedran Angebrandt, Ivan Tolić...............................33 A spatial evaluation of the impact of air pollution: a GIS-based approach/ Vrednotenje prostorskih vplivov onesnaženja zraka na podlagi GIS-ov Natalija Špeh, Blaž Barborič, Nataša Kopušar.............................43 The optimization options of water supply systems in terms of energy consumption/ Možnosti optimizacije vodovodnih sistemov z vidika porabe energije Ivan Žagar.................................................59 Instructions for authors..........................................77 Journal Of JE1 Volume 7 (2014) p.p. 11-20 Issue 4, November 2014 Energy Technology www.fe.um.si/en/jet.html NUMERICAL ANALYSIS OF AN AXIAL FLOW FAN: ANSYS VS SOLIDWORKS NUMERIČNA ANALIZA AKSIALNEGA VENTILATORJA: ANSYS IN SOLIDWORKS Igor Ščuri R, Marko Pezdevšek, Igor Spaseski, Matej Fike, Gorazd Hren Keywords: numerical analysis, axial fan, CFD, Ansys CFX, SolidWorks Abstract Axial flow fans are designed to operate in stable parts of the characteristic curves for the axial fan. However, it is possible that the operation regime becomes unstable due to changing conditions, resulting in a decrease of the fan's operational characteristics. In this article, a simulation is focused on the stable part of characteristic curves for the axial fan at various mass flow rates, which were acquired with numerical simulation software packages: Ansys CFX and SolidWorks Flow Simulation. The analyses were performed on designed structured meshes with similar numbers of elements, for different mass flow rates. In order to validate the numerically obtained results from both software packages, we compared them to experimental values from a reliable source. Povzetek Aksialni ventilatorji so zasnovani tako, da delujejo v stabilnem področju dušilne krivulje. Določene omejitve lahko povzročijo, da delovanje ventilatorja preide iz stabilnega v nestabilno področje dušilne krivulje. Slednje negativno vplivajo na karakteristike ventilatorja. V članku so predstavljeni rezultati numerične analize dušilne krivulje aksialnega ventilatorja s poudarkom na stabilni del pri različnih masnih pretokih. Za izvedbo numeričnih simulacij sta bila uporabljena programska paketa Ansys CFX ter SolidWorks Flow Simulation. Analiza je bila izvedena s strukturirano mrežo za več masnih pretokov. Z namenom, da ovrednotimo rezultate numeričnih simulacij, smo le te primerjali z eksperimentalno pridobljenimi vrednostmi iz literature. R Corresponding author: Igor Ščuri, Tel.: +386 40 783 926, Mailing address: Brezina 82b, 8250 Brežice, Slovenia, E-mail address: igor.scuri@student.um.si ш 1 INTRODUCTION A fan is typically a mechanical device that causes the movement of air, vapour or other gases in a given system. The basic purpose of the fan is to move a mass with a desired velocity. In order to achieve this objective, there is a slight increase of pressure across the fan rotor. However, the main aim remains to move the mass without any appreciable increase in pressure. Axial flow fans are mainly used for ventilating and air conditioning applications for buildings, mines, vehicles, underground transportation systems, etc. Each application requires a different type of fan. Within a system, particular fans are more appropriate than others in terms of capacity and pressure increase capabilities. In this sense, axial flow fans are generally categorized into four types: propeller fans, tube-axial fans, vane axial fans, and two-stage axial fans, [1]. Axial flow fans are the type for which the fluid flow is predominantly axial, i.e. parallel to the axis of rotation. Axial flow fans usually use air as the working fluid, which operates in an incompressible range, at low speeds and moderate pressures. The flow is treated as axial, with no radial component. The pressure rises with the tangential velocity component increasing, due to the rotation of the impeller and an aerodynamic diffusion process afterwards, [2]. The airflow around the blades profile affects the general shape of the characteristic curve. Furthermore, the airflow through the axial fan causes changes in the angle of attack and the velocity of the airflow around the blades. Due to the aforementioned effects, the axial fan operates in a stable or an unstable part of the characteristic curve, [3]. Axial fans are designed to operate in stable parts of characteristic curve. However, due to spatial or other limitations, it is possible that the fan operation regime becomes unstable, resulting in a decreasing of the fan's operational characteristics. This paper presents a numerical analysis resulting in the characteristic curve of the axial fan with a focus on the stable operating regime. 2 GOAL DEFINITIONS In order to compare different numerical software packages, we decided to perform numerical analyses and compare the computed results to existing experimental data of characteristic curves, [3]. The comparison was performed at different mass flow rates, declining from 0.7 kg/s to 0.4 kg/s with a step of 0.05 kg/s and from 0.45 kg/s to 0.40 kg/s with a step of 0.01 kg/s. In addition, the comparison was also made at mass flow rate of 0.475 kg/s. Steady-state simulations were made with Ansys CFX 15.0 and SolidWorks Flow Simulation (SWFS) 2014 software packages in order to obtain the characteristic curve of the axial fan. We have to emphasize the differences in the purposes of the software packages and their limitations. Ansys CFX is a well-known commercial standalone numerical software for numerical analyses, and SolidWorks Flow Simulation is part of a CAD (computer-aided design) package. We attempted to create corresponding meshes and boundary conditions in order to compare the results of analyses, the definitions of meshes, and the user-friendliness of software. 3 NUMERICAL MODEL In order to obtain reliable results, we created meshes with a comparable number of linear elements in both software packages. The axial fan model was simulated assuming steady-state conditions using various Reynolds-averaged Navier-Stokes (RANS) turbulence models. SWFS provides only the k-e turbulence model, while Ansys CFX offers various options. We performed analyses with the k-e turbulence model and the shear stress transport (SST) turbulence model in Ansys CFX. 3.1 Geometry The geometry of the axial fan used in the experimental measurements is highly complex. The fan rotor contained small parts, e.g. screws and mounting brackets, which are difficult to survey with the computational mesh. Therefore, the small parts that we assume are not necessary for simulation results have been suppressed from the numerical model, thereby reducing the number of elements of the mesh, and decreasing the required computer resources and time for solving governing equations. The three-dimensional geometry of the axial fan was modelled in SolidWorks. The numerical model of the axial fan consists of three main parts: inner hub, axial fan rotor with blades and outer tube. The inner hub was divided into two parts. The hub ahead of the axial fan rotor was 1000 mm long and behind it was 2000 mm long. The diameter of the hub is constant with the length of the whole model. With a diameter of 285 mm, the axial fan rotor includes ten aerodynamic blades. The blades have a NACA 6508 profile with a chord length of 80 mm. The blade shape is constant in the radial direction of the blade. The blade angle, i.e. the angle between the chord of the blade and the circumferential direction of the fan, is 45°. The blades have been designed with 2.5 mm as the gap between the top of the blade and outer tube. Therefore, the gap between the top of the blade and the outer tube was constant through the entire length of the model. The geometry of the fan is presented in Figure 1. £ 1000 110 2000 0185 0300 Figure 1: Axial fan geometry. 3.2 Mesh creation In CFD, the numerical mesh has two basic functions: defining the geometry and the discretization of computational domain. The geometry of the numerical mesh has to fulfil the geometry to the greatest extent possible. The complexity of the modelled object affects the final mesh size and, consequently, the required design time. The amount of computer resources for the implementation of the numerical simulations is directly proportionate to the mesh resolution. The accuracy for solving the discrete equations depends on the number of discrete elements and the nodes of the mesh. Generally, a numerical solution becomes more accurate when a mesh with greater resolution is used. Furthermore, a mesh with a higher density is commonly used in areas where high spatial and temporal gradients of critical quantities accrue. In numerical simulations, we tended to optimise mesh size for greater accuracy of results, which are usually limited by available computer resources. Structural computational meshes were designed with a pre-processor ICEM CFD 15.0 for the Ansys CFX software, with which we designed separate meshes for the domain ahead of the rotor, behind the rotor and the rotor itself. Once the three meshes were created, they were merged in Ansys CFX to form a single mesh, which represents the full computational domain. In SWFS, the mesh was created with the built-in mesh manager. Table 1 shows comparable number of elements in both software packages. Table 1: Mesh data Ansys CFX Number of elements SWFS Number of elements 3,030,110 2,929,807 Figure 2, shows a part of the structural mesh created in ICEM CFD and SolidWorks. The resolution of the mesh is greater in regions where greater computational accuracy is needed, e.g. the region close to the blade. The close-ups of the mesh are shown, which clearly represent a different type of mesh creation. Typical structured meshes from Ansys and the use of a Cartesian-based mesh generation in SolidWorks, [4], are presented. a) b) Figure 2: Numerical mesh designed with a) ICEM CFD software and b) SWFS software in close-up view. 3.3 Boundary conditions and convergence criteria Boundary conditions fulfil an important role in all simulations because they govern computational stability and numerical convergence. The initial conditions of the simulation are also specified at these boundaries. The boundary conditions inlet and outlet were defined in both software packages. Different mass flow values were defined for the inlet boundary condition, and the static pressure of 100 kPa was applied to the outlet boundary condition. The mass flow inlet boundary condition requires the specification of the turbulent inlet flow conditions, so the turbulence intensity was set to 1.5% and the turbulence length to 0.01 m. The air density was set to 1.185 kg/m3 and the dynamic viscosity to 1.79-10"5 kg/ms. The axial fan rotor's angular velocity was set to 1440 rpm, [3]. For SWFS, the outer tube and inner hub surfaces were defined as a real wall and then selected to be stationary (stator). For the computation in Ansys CFX, the domains ahead and behind the rotor were defined as stationary domains. The rotor was defined as a rotating domain with the abovementioned angular velocity. In the stationary domain, the top and bottom surfaces were defined as walls. In the rotational domain, the inner surface of the blade and the bottom surface were defined as walls. The boundary condition stage was applied to the surfaces between the rotating and stationary domains, and the sides were defined as rotational periodicity. Figure 3: Boundary conditions defined in Ansys CFX. To satisfy the convergence criteria, all the RMS (root mean square) leftovers from solving equations must be under 1-10-5. We also set number of maximum iterations to 500 and used automatic timescale control. Both software packages have an automatic system for stopping the analysis when it reaches predefined convergence criteria. 4 RESULTS 4.1 Characteristic curve The computed results of the axial fan characteristic curves at various mass flow rates were compared to existing experimental data from [3]. The characteristic curve of the axial fan is defined with the relationship of integral parameters, which are presented by dimensionless numbers. The flow number (coefficient) ф is calculated with the equation: 4 • (4.1) P = where: п-D2 qv - mass flow rate; D - rotor diameter; u - tangential velocity. The pressure number (coefficient) ф is defined with the equation: 2-4p, (4.2) where: ¥ = - 2 p-u Aps - simulated (measured) static pressure increment; p - air density; u - tangential velocity. Figure 4 shows the comparison between experimental data and numerical analysis results for characteristic curves at different mass flow rates. 0,40 Characteristic curve ! f — —Hysteresis 1 - —Hysteresis 2 / ' '/ / / / ■ Unstable characteristic measurements ■ Stable characteristic measurements f / / J / / t / ■ Ansys k-e ^ —»—Ansys S ST / SolidWorks 0,30 ^0,25 0,20 0,10 0,05 0,05 0,10 0,15 0,20 0,25 Ф 0,30 0,35 0,40 0,45 Figure 4: Comparison between experimental data and the data obtained from simulation software packages of the characteristic curves at different mass flow rates. 4.2 Computation time Table 2 shows the average computational times needed for computing the characteristic curve parameters. Computational times in Ansys CFX software using the k-e turbulence model were slightly longer than those using the SST model when one tenth of the axial fan model was simulated. Furthermore, the SolidWorks software took about twice as much time to finish the simulation on the entire axial fan model. Table 2: Average computational times needed for computing characteristic curve parameters Simulated model (ca. 3,000,000 elements) Computational time [hh]:[mm]:[ss] SolidWorks Ansys CFX k-e model Ansys CFX SST model 1/10 of the axial fan model / 0:40:03 0:38:52 Whole axial fan model 10:11:42 6:40:30 6:28:40 5 CONCLUSIONS Simulations of the characteristic curve parameters for various mass flow rates were conducted in order to compare the results from different software packages and then validate them with experimental data. In Ansys CFX, at mass flow rates lower than 0.4 kg/s, convergence was found to be problematic. Therefore, the comparison between the software was made at mass flow rates ranging from 0.7 kg/s to 0.4 kg/s. Results obtained from SolidWorks correlate quite well with the experimental results within the normal (stable) operating range of the axial fan. Generally, SolidWorks produced, in our case, better results than Ansys CFX, when using both turbulence models. The correlation between the numerical and experimental values for both turbulence models in Ansys CFX was found to be adequate. Computational times in Ansys CFX software using k-e turbulence model were slightly longer than those using the SST model when one-tenth of the domain was simulated. With the lack of a rotating periodicy feature in SolidWorks, the results could not be obtained and consequently compared. In this case, when the whole axial fan model was simulated, SolidWorks software took about twice as much time for performing the simulation. Based on the computed results and computational times, Ansys CFX would be the better pick for the example used in this paper, regardless of the turbulence model. Nevertheless, SolidWorks' computed results were found to be sufficient, but the lack of rotational periodicy means that a large amount of computational resources and time was required to compute the results. References [1] D. Dwivedi, D. S. Dandotiya: CFD Analysis of Axial Flow Fans with Skewed Blades, International Journal of Emerging Technology and Advanced Engineering, Volume 3, Issue 10, October 2013, [2] Available at: http://www.ijetae.com/files/Volume3Issue10/IJETAE_1013_121.pdf, [3] Accessed on November 6, 2014. [4] T. Köktürk: Design and performance analysis of a reversible axial flow fan, Master's thesis, Middle East Technical University, Graduate School of Natural and Applied Sciences, 2005 [5] M. Fike: Experimental and numerical analysis of fluid flow in an axial fan, Doctoral thesis, University of Maribor, Faculty of Mechanical Engineering, 2013 [6] A.Sobachkin, G.Dumnov: Numerical Basis of CAD-Embedded CFD, February 2014, Available at: http://www.solidworks.com/sw/docs/Flow_Basis_of_CAD_Embedded_CFD_Whitepa-per.pdf, Accessed on November 13, 2014 Journal Of JE1 Volume 7 (2014) p.p. 21-32 Issue 4, November 2014 Energy Technology www.fe.um.si/en/jet.html LARGE HYDRO POWER PLANTS IN SLOVENIA VELIKE HIDROELEKTRARNE V SLOVENIJI Ivana Tršelič* Keywords: large hydro power plant, water energy, water pollution Abstract Electricity distribution started in Slovenia with hydro power. The first real use for electricity was street lighting, industry, and workshops. With the evolution and expansion of such usage, power lines had to be built. In Slovenia, large hydro power plants on three Slovenian rivers (Drava, Sava, Soča) account for almost one third of the electricity produced in Slovenia. Rivers have limited amounts of water, although there is a large amount of annual precipitation; the problem is that the water is not equally distributed. Slovenia has dry and rainy periods, marked by drought and flooding. With developments and investments in hydro power plants, the efficiency of turbines is being successfully improved; however, for better exploitation of water energy, building new power plants is required. Povzetek Slovensko elektrogospodarstvo je pričelo svoj razvoj z izkoriščanjem vodne energije. Prvi porabnik električne energije je bila javna razsvetljava mest, kasneje industrija in manjši domači porabniki, obrtniki. Vzporedno z razvojem elektrogospodarstva je potekala izgradnja daljnovodov. V Sloveniji večje hidroelektrarne katere izkoriščajo vodno energijo treh večjih slovenskih rek: Dravo, Savo in Sočo priskrbijo skoraj tretjino proizvedene elektrike v Sloveniji. Omejene so s količino vode, katere je v Sloveniji dovolj, le da je neenakomerno porazdeljena preko celega leta, tako po sušnem poletnem obdobju sledi jesensko poplavno obdobje, ki prav tako ovira konstantno delovanje hidroelektrarn. Z dogradnjo in obnovami hidroelektrarn je slovensko hidroelektro gospodarstvo uspešno R Corresponding author: Ivana Tršelič, Tel.: +386 7334 600, Mailing address: Vrbina 18, SI-8270 Krško, Slovenija E-mail address: ivana.trselic@gmail.com ш izboljšalo izkoristke turbin in nekaterim hidroelektrarnam povečalo pretok, tako da so izboljšave na tem področju dovolj omejene, da je potrebno razmišljati dalje in iskati možnosti za izgradnjo novih hidroelektrarn. 1 INTRODUCTION The current condition of the economics of large hydro power plants in Slovenia is the subject of this review. Slovenian electric power distribution started its development at the end of the 19th century. During the time of Austro-Hungarian Empire, the Slovenian region was geologically and topographically explored. The first hydro power plants were planned for the Styrian region. World War One hindered development. Although the economy was in poor shape, the development and planning of new hydro power plants continued, the electric power system grew, and new consumers were sought. At present, the situation is reversed; the demand of consumers is greater than the amount electric energy produced. Old hydro power plants have been rebuilt, and new modern hydro power plants have been and are being build. The control and monitoring of hydro power plants are automatic and sophisticated. The system greatly depends on the amount of precipitation because Slovenia has no conventional hydro power station with large natural reservoirs, but only run-of-the-river electricity production systems. Therefore, electricity production is strongly influenced by hydro-logic conditions. The Sava River basin is a torrent type, in which large fluctuations of the river current occurs, thus influencing the electricity production, [1]. 2 ENERGY STORED IN WATER Water is the most important renewable energy source: 21.6% of electric energy produced in the world comes from exploiting energy from water, [2]. Energy stored in water is actually a gravitational force, seen as falling and flowing water. A hydro power plant is where energy conversion from potential to kinetic to mechanical work into electric energy happens. This conversion should not have an environmental impact, as the entire infrastructure of the hydro power plant brings beneficial and adverse changes to the environment in the immediate area of the hydro power plant. Building a hydro power plant influences the environment in different ways, affecting the landscape and the surface of the river bed. It also influences the characteristics of water flow in the river and around it, [2]. Adverse influences of hydropower plants are observed via analysis of river sediment, which reveals high concentrations of toxic elements in reservoirs, such as sulphur compounds in toxic metals (lead, potassium) and eutrophication substances, such as compounds of phosphorus and nitrogen. Therefore, dropped silt is evaluated as waste, with high amounts of harmful substances [3]. Hydropower plants also endanger fauna, because the oxygen level is decreased, and fish are inevitably suffocated. The beneficial influence of hydropower plants is in their low operational costs and long periods of operation. Hydropower plant technology is considered to be a green technology. It is reliable and stable when connected to the electrical power grid, [2]. As an environmental friendly technology, hydropower is implemented according to energy and environmental policies. The main types of hydro power plants are, [2]: 1. Run-of-the-river HPP, with which a river flow with a relatively low drop is exploited. The river has a dam, but no large reservoir of water is created. 2. Conventional HPP of dammed water with large drop and lower river flow. Water is accumulated with dams or flooded valleys and canyons. 3. Combinations of run-of-the-river and dam hydro power plant are built in a chain, in which the first one has a reservoir. Building a hydro power plant requires a significant intervention in the environment, as it influences farming, forestry, groundwater, the quality of the water, natural river affluent, and the economy (fishing, tourism, and infrastructure). 3 WATER IN SLOVENIA Slovenia is water-rich country, although the water supply is not time and space consistent, [5]. An analysis data of water balance from 1971 to 2000 shows that more than half of the average precipitation (1579 mm) contributes to river flow (862 mm), [4]. Large amounts of precipitation, especially in the western and northern parts of Slovenia, classifies the country among water-rich countries on international scales. Furthermore, water is restored seasonally. According to evaluations, Slovenia has one of the largest amounts of water per capita in Europe. Water deficits are observed in the regions of Kras, Suha and Bela krajina, Obsotelj, Haloze, Slovenske Gorice and the northern part of Prekmurje. Water resources are reflections of climatic conditions, hydrology, relief and geological conditions. Inequalities of those factors determines the existence of different water regimes, [5]. Slovenia is divided into two water regions: that of the Danube River, and that the Adriatic Sea. The Soča River is part of the latter and is 95 km long. In the Danube water region there are the Sava, Drava and Mura rivers. The Sava is Slovenia's longest river; from its source at Sava Dolinka in Zelenci to the Croatian border it runs 221 km. The Drava River has 142 km in Slovenia, and the Mura 95 km, flowing directly on the border with Austria for 65 km. Taking the river flow into account, the Drava is Slovenia's most water-rich river; after its confluence with Pesnica, the Drava's flow exceeds 320 m3/s. Apart from the Sava and Mura, other rivers have significantly lower flow because of minor river basins and characteristics of water accumulation outskirts, [5]. 4 HYDRO POWER IN SLOVENIA 4.1 Development of electricity distribution worldwide and in Slovenia The development of electricity distribution started with the invention of the light bulb. The electric wire was first presented in Paris in 1881: a light bulb with a charcoal filament. From that year onward, electricity distribution developed into one of the strongest branches of the economy, [6]. Cities built small local power plants for electric lighting for individual facilities and factories, or for street lighting. At the beginning, there was a direct current with voltage of 65 V, then 110 V and later 220 V. In the second phase of electricity distribution, provincial lighting developed with alternating current. Power plants were placed directly by the energy source, i.e. by the water, by the coal mine. In Slovenia, the first power plant was a hydro power plant built in Škofja Loka in 1894. The hat factory Šešir installed a water turbine in 1889 for production purposes. In 1894, a generator was implanted; it produced direct current with a voltage of 110 V and with 15 kW of power, [7]. In addition to production, the Šešir factory started to sell the electricity for street lighting in Škofja Loka, [8]. In Ljubljana, the first power plant started to operate in 1898. In 1914, there were 17 locally operated power plants in Slovenia (not counting the Primorska region), with electric power of 2500 kW. The Završnica hydroelectric power plant was the first Slovenian public power plant. The construction of the plant occurred during World War I. And all obstacles aside, it was activated in February 1915, illuminating the streets of Radovljica and Bled. A descriptions of that special day states: "The hydropower plant on Završnica started to operate! For our economy this is very important. Circumstances do not allow special celebration", [9], and "We can see long desired electrical street lighting in Bled. Only now is Bled what it should have been a long time ago. The illumination is beautiful. Around the Lake of Bled crown of lights - it is magical", [10]. The Završnica hydropower plant operated until 2005, after which it became a technical and historical monument. Its part in producing electricity was overtaken by Moste HPP. In 1912, in Styria, preliminary planning of the Fala hydro power plant on the Drava River started. World War I caused a delay, and Fala HPP started to operate in 1918. It was intended to supply industry in upper Styria (sl: Štajerska) with electricity. When World War I ended, Yugoslavia was entitled to Fala HPP, although the investment had come from elsewhere, [11]. After World War I, electricity distribution greatly expanded, with industrial power plants being build parallel to public power plants. World War II influenced the development of economy electric energy production. When the Primorska region joined Yugoslavia, more hydro power plants on Soča River were obtained: Doblar and Plave, [6]. After the end of the war, a systematization of electricity distribution began. A state power plant company was founded. This company joined public and industrial power plants. Six main energy regions were founded: Drava, Sava, Soča, Trbovlje, Rajhenburg, Velenje, [6]. Slovenian large hydropower plants are follows: - SENG - Slovensko elektrogospodarstvo Nova Gorica (Hydro power plants: Doblar 1 in 2, Plave 1 in 2, Solkan, Avče) - SEL - Savske elektrarne Ljubljana (Moste, Mavčiče, Medvode, Vrhovo) - HESS - Hidroelektrarne na spodnji Savi (Boštanj, Blanca, Brežice, Krško) - DEM - Dravske elektrarne Maribor (Dravograd, Vuzenica, Vuhred, Ožbolt, Fala, Mariborski Otok, Zlatoličje, Formin) In the last quarter of 20th century, the number of small hydro power plants increased from 12 to 36. In same period, the production of electricity from hydro power plants doubled, [12]. With the expansion of economy and the erection of new power lines, the consumption of electricity increased and electricity distribution expanded. Consumption levels continue to increase (with a minor decrease following the most recent recession). 4.2 Hydro power plants of river Sava - upper course 4.2.1 HPP Moste Hydro power plant Moste started operating in 1952. It is a hydropower plant with accumulation planned for production of electricity in peak demand. Three generators with Francis water turbines have been installed. The flow is 28.5 m3/s. In 1977, Moste HPP built a forth generator and successfully realised affiliation with Završnica HPP. The system was planned to pump the water into the upper reservoir of Završnica and use it when demand exceeds the production of electricity. Unfortunately, this system was never realised because of water pollution. The generator was reconstructed in 1999. Between 2008 and 2010, a thorough reconstruction of the entire plant took place. The system produces 21 MW of power, [13]. 4.2.2 HPP Mavčiče Hydro power plant Mavčiče is a run-of-the-river hydroelectric power station, with a construction height of 40 m. With two Kaplan turbines and 260 m3/s of flow, the system produces 38 MW of power. Operations began in 1987. Reconstruction started in 2011 with renovation of the equipment and exterior switchyard, [14]. 4.2.3 HPP Medvode Hydro power plant Medvode lies above the confluence of the Sava and Sora Rivers. The dam is made of concrete and makes use of the reservoir from HE Mavčiče. The first two generators started to operate in 1952, the third one in 1955. When the barriers were heightened by one meter in 1964, the power of the turbine increased by 11%. Two Kaplan turbines are able to produce 25 MW of power. In 2003 and 2004, the hydro power plant was modernised; turbines and secondary equipment were replaced, [15]. 4.2.4 HPP Vrhovo Vrhovo HPP is the first hydro power plant in a series on the lower river course of the Sava. Vrhovo HPP started to operate in 1993. With a concrete dam with a construction height of 27 m, the hydro power plant operates as run-of-the-river hydroelectric station, but also serves as reservoir for hydro power plants lying downriver. With three generators, Vrhovo HPP produces 34.2 MW of power, [16]. 4.3 Hydro power plants of the Sava River - lower course 4.3.2 HPP Boštanj Boštanj HPP is the second hydroelectric station and one of the six hydro power plants built on the lower course of the Sava River. It produces 36 MW, which represents 1% of the electricity produced in Slovenia. The plant started to operate in 2006, [17]. 4.3.3 HPP Blanca Arto-Blanca HPP is the third hydro power plant in the chain of lower course of Sava River. It produces 42 M and started to operate in 2010, [18]. 4.3.4 HPP Krško Krško HPP produces 42 MW. This hydro power plant is constructed as combination of accumulation and run-of-the-rive. It started to operate in June 2013. 4.4 Hydropower plants of the Drava River - Dravske elektrarne Maribor The Drava River springs originates from Dobbiaco in South Tirol in Italy. Near Dravograd, it enters Slovenia and, after 133 km, it continues its flow into Croatia. Before the construction of hydro power plants, the Drava was used for transport with rafts to Danube towards the Black Sea. 4.4.1 HPP Dravograd Dravograd HPP in the first hydro power plant in the chain of Drava on the territory of Slovenia. In 1944, it started to operate and it was one of the first pier-type power plants in Europe. Construction began in in 1941 during World War II. In April 1945, allied air raids caused considerable damage to the power plant. With the launch of the third unit in 1955, construction of the power plant was completed, [19]. With renovation of the generator, which started in 1994, the power of HPP increased by 26 MW. In 2010 and 2011, the 110 kV exterior switchyard was modernised. Construction a dam created a reservoir that spreads to Austria, [19]. 4.4.2 HPP Vuzenica Hydro power plant Vuzenica is the second in line on the Drava River. Construction started in the fall of 1947. In HE Vuzenica, the first domestically made Kaplan turbine was installed; it was produced in Litostroj. The first generator started to operate in 1953. After reconstruction in the 1990s, the power increased by 11.2 MW. It is a run-of-the river power plant with pillar construction producing 56 MW, [20]. 4.4.3 HPP Vuhred HE Vuhred operates in a region where the Radlje field closes into a narrow water channel. It is the first of two stages that share the available head of the section of the Drava between the Vuzenica and Fala power plants. Topographical and geological surveys performed immediately after World War II showed that two power plants could be built in this section. Construction began in 1952. The Vuhred HPP was the first plant in the former Yugoslavia that had been planned and constructed on the basis of domestic experience and equipped solely with domestic Slovenian equipment. The first two units began operations in 1956 and the third in 1958. The second phase refurbishment of the Upper Drava power plants, concluded in 2005, encompassed the replacement of the turbines and the other equipment to increase the net capacity of the power plant and flow, [21]. 4.4.4 HPP Ožbalt The second power plant on the section of the Drava River between Vuzenica and Fala was built between 1957 and 1960 as the twin of the Vuhred HPP upstream. The Ožbalt HPP is the fourth power plant in the Slovene section of the Drava River; construction began in 1957 and within three years two units were operating. Since the Ožbalt HPP has the same energy specifications as the Vuhred HPP, the pier type structure was also chosen. After the refurbishment of the Upper Drava power plants in the 1990s, the net capacity increased to 73.2 MW. The plant, with its increased power, annually generates 305 million kWh of electricity. The damming of the Drava River here resulted in a 12.7 km long reservoir containing 10.5 million m3 of water, of which 1.4 million m3 can be used for the generation of power, [22]. 4.4.5 HPP Fala Construction of HPP Fala started in 1913 with the first five units commissioned as early as 1918. Due to increased demands for electric power, a sixth unit was built in 1925 and then a seventh was completed in 1932. When construction of all the other power plants on the Drava River was completed, the plant's turbine discharge proved low in comparison and this led to the construction of an eight unit in 1977 using a Kaplan turbine with the capacity of 17 MW. After extensive refurbishment, the three newer units make use of the 14.6 m available head, have a net capacity of 58 MW, and can generate 260 million kWh of electricity annually, [23]. Within the dam structure complex, the old power house has been preserved as an important item of technical heritage. Its units, comprising double horizontal Francis turbines and generators on the same shaft, were closed down in stages as a result of the construction of the new powerhouse. Today, the old powerhouse is an interesting vantage point for visitors allowing them to become acquainted with both the previous and current methods of operating the power plant, [23]. 4.4.6 HPP Mariborski otok This pier type power plant is located just outside of Maribor in the riverbed, exploiting the energy potential of the Drava River between the Fala HPP and the island in the Drava River. The construction of the power plant had been planned prior to the World War II, but construction only began in 1942. The war caused the construction process to be drawn out considerably, so that in May 1945 it was still only 30% completed. Despite a number of problems after the war, construction work continued and 1948 saw the commissioning of the first unit, with the second and third units beginning operation in 1953 and 1960; its construction created a 15.5 km long reservoir. The dam structure contains three turbine piers between four spillways and a left and right bank building. Each of the turbine piers contains a vertical Kaplan turbine and a generator above it. A 10 kV switchyard and an areas for two main transformers directly connected to 110 kV transmission lines leading towards the Pekre substation are located in the right bank building. Mariborski otok HPP uses the 14.2 m available head and, following its refurbishment, annually generates 270 million kWh of energy with a net capacity of 60 MW, [24]. 4.4.7 HPP Zlatoličje HPP Zlatoličje generates more than a fifth of all the electric power generated by Dravske Elektrarne Maribor and makes use of the energy potential of the Drava River between the cities of Maribor and Ptuj where the river turns into a flatbed. Due to its location, it has been designed as a channeltype power plant. The Zlatoličje HPP makes use of the 33 m head and, after refurbishment from 2007 to 2012, annually generates 577 GWh of electricity with a threshold capacity of 126 MW. The power plant, built between 1964 and 1969, has a supply and discharge channel separate from the riverbed, a 4.5 million m3 reservoir and a dam structure in Melje near the city of Maribor, [25]. 4.4.8 HPP Formin As the last in the chain of power plants on the Drava River, this plant rates as the second largest in terms of electric power generated and also boasts the largest reservoir in the Slovene section of the Drava River. The power plant was completed in 1978 and, due to the natural conditions, was designed as a channel-type power plant, similar to Zlatoličje HPP. With its 29 m available head on the section between Ptuj and the national border with Croatia and with a net capacity of 116 MW, it generates 548 million kWh of electricity annually, [26]. The damming of the Drava River with a dam in Markovci resulted in the creation of the largest artificial lake in Slovenia, with a length of 7 km and a water surface of 3.46 km2. It is called Ptuj Lake and it contains 17.1 million m3 of water of which 4.5 million m3 can be used for the generation of electricity, [26]. 4.5 Hydropower plants of Soča River - Soške elektrarne Nova Gorica 4.5.1 HPP Doblar 1 in 2 Doblar 1 was designed during the Austro-Hungarian Empire. After World War I, research continued with an Italian company. In 1939, it started to operate. In 1979, the equipment had become obsolete and inadequate. Three vertical Francis turbines were substituted with equipment from a local manufacturer. Dolbar 2 was constructed alongside Doblar 1 and uses the infrastructure and equipment of Doblar 1. It started to operate in 2002 with installed power of 20 MW, [27], [28]. 4.5.2 HPP Plave 1 in 2 Plave 1 was planned parallel to HE Doblar and started to operate in 1940. It has a power of 15 MW. Two vertical Kaplan turbines are installed. It operates reliably and no modernization of equipment is currently needed. Doblar 1 and Plave 1 satisfy 40% of the demands for electricity in Slovenia. The design of Plave 2 HPP was based on research results of the available hydroelectric resources. Plave 2 essentially uses the infrastructure of Plave 1. The technology for the construction of the conducting channels was used in Slovenia for the first time. The installed power is 20 MW, and it started to operate in 2002, [29], [30]. 4.5.3 HPP Solkan HPP Solkan started to operate in 1984. Three vertical Kaplan turbines with producing 32 MW were installed. The plant is automatic and managed from the control centre of power plants on Soča in Nova Gorica, [31]. 4.5.4 PHPP Avče The concept of a pumped-storage hydropower plant is based on increased peak demand of electricity. In times of lower price of electricity (i.e. at night), the water is pumped into the upper reservoir. At times of demand the water flows through turbines to produce electricity. PHPP Avče helps alleviate deficits in electricity production in times of peak demand. The installed power is 180 MW with a vertical Francis one-stage reversible turbine. The maximum drop is 521 m. The pumps needed for pumping storage water have a power 185 MW, [32]. 5 THE FUTURE OF HYDRO ENERGY IN SLOVENIA Almost one third of electricity in Slovenia is produced by hydro power, according to Bojnec and Papler, [12]. Experts' opinion is that Slovenia could be able to exploit even more of the available hydropower. Operating possibilities could be doubled, [34]. Table 1: Production of electricity in large hydro power plants in Slovenia from 2002 to 2010, [12] Production of electricity from large hydro power plants (TWh) Production of electricity from all power plants in Slovenia (TWh) Share of HPP in production of electricity in Slovenia (%) 2002 3313 13319 24.87 2003 2957 12491 22.67 2004 4095 13835 29.60 2005 3461 13667 25.32 2006 3591 13643 26.32 2007 3266 13636 23.95 2008 4018 15032 26.73 2009 4713 15208 30.99 2010 4696 15260 30.77 Planned investments for large hydro power plants in the lower course of the Sava River are currently being realised, and there are also investments planned for medium-sized and small hydro-power plants. The modernization of existing hydro power plants also aids in increasing the amount of produced electricity. Construction of new small hydropower plants is planned on the Soča and Idrijca Rivers. On the Drava River, the modernization of existing hydro power plants is taking place to ensure the operating conditions for the next 60 years, [34]. Construction of large hydro power plants is multidisciplinary subject, requiring radical changes in the local environment. The opinions of technicians, environmentalists, cultural heritage, sport and tourism specialists are important. Moreover, civil initiative needs to be respected, which can lead to transnational issues. A typical example is the Mura River. There are many hydro power plants installed on river in Austria, Croatia, Hungary, but none in Slovenia [12]. Preliminary preparations for the first hydro power plants on the Mura River in Slovenia are taking place. The construction is planned to be completed in 2020; flow-of-the-river hydro power plants are planned, which have less influence to the surroundings and can be socially more acceptable, [34]. On the lower course of the Sava River, there are two hydro power plants under construction: Brežice HPP and Mokrice HPP. A survey of the area was made between the years of World War I and World War II. The idea for the hydro power plants is written in an article that was published on the 1st of June, 1925 in Technical Journal. In the article, the Authority of Yugoslavian Engineers and Architects states a report of the possibilities and advantages of water energy from the Sava River between cities Brestanica and Čatež [33]. At the beginning of 2011, a public unveiling of plans for hydro power plant Brežice took place in the city hall of Brežice. Construction should be completed in 2016. Although Slovenia has a good water management, problems are expected in the future. The European directives for water management requires better chemical, quantity and ecological conditions of water and, minimum flows for ecological reasons. This means that there must be more natural and balanced development and better controlled water consumption. That is a new standard in planning and designing environmental politics, [5]. Worldwide, there are extensive possibilities for the future development of exploiting the water sources, especially in developing countries. However, economical, regional, environmental and social factors can substantially affect development. In recent years, the construction of new hydro power plants has significantly decreased, [34]. 6 CONCLUSION The efficiency of energy conversion in hydro power plants is generally between 85% and 95%, which is definitely more than in other types of power plants. Consequently, it can be said that the hydro power plant is the most sophisticated developed system for producing electricity. A relatively large initial investment and long construction period make hydro power plants only slightly profitable, if taking in account only the short-term period between 10 and 20 years. If we consider a longer period of time, reliability and CO2 emission reduction, the hydropower plant is the most suitable renewable energy source, [35]. Electricity production costs over the operating time of hydro power plant are considerably lower in comparison with other renewable sources. This fact reveals that other technologies are in a lower state of development, [35]. The development of hydro power plants in Slovenia is not final. It represents the only optimal way to a "greener" Slovenia. Although larger hydro power plants are not to be defined as entirely harmless for the environment, they can be defined as mainly harmless for the environment. References [1] F. Kržan: Planiranje proizvodnje električne energije savskih elektrarn, Univerza v Mariboru, Fakulteta za Energetiko UM, diplomsko delo, 2013 [2] Vodna energija, Fokus društvo za sonaravni razvoj, http://www.focus.si/ove/index. php?l1=vrste&l2=vodna (from 7th of July, 2014) [3] Več o hidroelektrarnah, Agencija za prestrukturiranje energetike d.o.o., http://194.249.18.202/slojoomla/index.php?option=com_content&task=view&id=103 &Itemid=96 (from 7th of July, 2014) [4] Vode, Agencija Republike Slovenije za okolje, http://www.arso.gov.si/vode/].(from 7th of July, 2014) [5] S. Čehić: Pogled na vode v Sloveniji, Statistični urad Republike Slovenije, Ljubljana, 2007, št. 9, http://www.stat.si/doc/pub/Pogled_na_vode_v_Sloveniji.pdf (from 7th of July, 2014) [6] F. Strajnar: Razvoj elektrogospodarstva v LRS, Časopis za slovensko krajevno zgodovino, Vir: Kronika (Ljubljana), 1954, letnik 2, številka 2Izvor: Narodna in univerzitetna knjižnica (Digitalizirano v okviru projekta Digitalna knjižnica Slovenije - dLib.si (EEA SI0014) [7] J. Gašperšič: Razvoj elektrifikacije konzumnega področja občine Škofja Loka, Vir: Loški razgledi, letnik 03, 1956 [8] Energija vode, Gorenjske elektrarne, http://www.gek.si/voda/200400196/Predstavitev (from 7th of July, 2014) [9] Časnik Domoljub, zbirka Goran Lavrenčak ( Vir: www.dLIb.si; digitalizirano: 1888-1944) [10] Časnik Slovenc, zbirka Branislav Šmitek (Vir: www.dLib.si; digitalizirano: 1873-1945) [11] Zgodovina HE Fala, Dravske elektrarne Maribor, http://www.dem.si/slo/tehniskadediscina/ zgodovinahefala, (from 7th of July, 2014) [12] Š. Bojnec, D. Papier: Renewable sources of energy: Hydro-electricity in Slovenia, Technical Gazette 19, 4, 2012 [13] HE Moste, Savske elektrarne Ljubljana, http://www.sel.si/?p=8&s=1, (from 9th of July, 2014) [14] HE Mavčiče, Savske elektrarne Ljubljana, http://www.sel.si/?p=8&s=2, (from 9th of July, 2014) [15] HE Medvode, Savske elektrarne Ljubljana, http://www.sel.si/?p=8&s=3 (from 9th of July, 2014) [16] HE Vrhovo, Savske elektrarne Ljubljana, http://www.sel.si/?p=8&s=4 (from 9th of July, 2014) [17] HE Boštanj, Hidroelektrarne na spodnji Savi, http://www.he-ss.si/he-bostanj.html (from 9th of July, 2014) [18] HE Blanca, Hidroelektrarne na spodnji Savi, http://www.he-ss.si/he-blanca.html (from 9th of July, 2014) [19] HE Dravograd, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvod-nja/11 (from 9th of July, 2014) [20] HE Vuzenica, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvod-nja/12 (from 9th of July, 2014) [21] HE Vuhred, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvodn-ja/13 (from 9th of July, 2014) [22] HE Ožbalt, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvodnja/14 (from 9th of July, 2014) [23] HE Fala, Dravske elektrarne Maribor., http://www.dem.si/slo/elektrarneinproizvodnja/15 (from 9th of July, 2014) [24] HE Mariborski otok, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproiz-vodnja/16 (from 9th of July, 2014) [25] HE Zlatoličje, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvod-nja/17 (from 9th of July, 2014) [26] HE Formin, Dravske elektrarne Maribor, http://www.dem.si/slo/elektrarneinproizvodnja/19 (from 9th of July, 2014) [27] Doblar 1, Soške elektrarne Nova Gorica, http://www.seng.si/hidroelektrarne/predstavitev_ hidroelektrarn/velike_hidroelektrarne/ (from 9th of July, 2014) [28] Doblar2, Soške elektrarne Nova Gorica, http://www.seng.si/hidroelektrarne/predstavitev_ hidroelektrarn/velike_hidroelektrarne/ (from 9th of July, 2014) [29] Plave 1, Soške elektrarne Nova Gorica, http://www.seng.si/hidroelektrarne/predstavitev_ hidroelektrarn/velike_hidroelektrarne/ (from 9th of July, 2014) [30] Plave 2, Soške elektrarne Nova Gorica, http://www.seng.si/hidroelektrarne/predstavitev_ hidroelektrarn/velike_hidroelektrarne/ (from 9th of July, 2014) [31] HE Solkan, Soške elektrarne Nova Gorica, http://www.seng.si/hidroelektrarne/pred-stavitev_hidroelektrarn/velike_hidroelektrarne/ (from 9th of July, 2014) [32] ČHE Avče, Soške elektrarne Nova Gorica, http://www.seng.si/che_avce/ (from 9th of July, 2014) [33] Tehnički list, leto 7, Številka 11, 1925 [34] R. Tomažič: Razvoj na področju hidroenergije, Varčujmo z energijo, 9.maj, 2011 http:// varcevanje-energije.si/ekoloska-zavest-cloveka/razvoj-na-podrocju-hidroenergije-v-slo-veniji.html (from 10th of July, 2014) [35] Energija vode, Energetska agencija za Podravje, http://www.energap.si/?viewPage=42 (from 10th of July, 2014) ш Journal Of JET Volume 7 (2014) p.p. 33-42 Issue 4, November 2014 Energy Technology www.fe.um.si/en/jet.html STABILITY ASSESSMENT IN A POWER SYSTEM CONTROL CENTRE OCENE STABILNOSTI V NADZORNEM CENTRU VODENJA ELEKTROENERGETSKEGA SISTEMA Lajos JozsaR, Vedran Angebrandt, Ivan Tolić Keywords: power system operation, power system monitoring, power system stability Abstract This paper presents a conceptual picture of new stability control possibilities in power system control centres. A potential future state of power system operations and control, with regard to stability assessment, is described and compared to the present state. New technologies have raised the possibility of developing much faster and more widespread stability control that can enable the safe operation of the grid closer to its limits. Povzetek Članek predstavlja konceptualno sliko novih možnosti nadzora stabilnosti v nadzornem centru elektroenergetskega sistema. Opisana je primerjava med prihodnjim in sedanjim stanjem na področju poslovanja in nadzora, povezano z oceno stabilnosti. Nove tehnologije so odprle hitrejše možnost razvoja in nadzora širokega področja stabilnosti, ki lahko omogoči varno delovanje omrežja v področju skrajnih mej. R Corresponding author: Prof. Lajos Jozsa Ph.D, Tel.: +385 31 224 614, Mailing address: Ulica kneza Trpimira 2B, 31000, Osijek, Croatia E-mail address: lajos.jozsa@etfos.hr 1 INTRODUCTION To maintain interconnected power systems in a stable dynamic state, tight control and protection along with the intelligent and diligent operation of such systems are necessary. The general public often take operating details for granted; a catastrophic failure usually happens before power system stability becomes a topic of discussion. Power system faults mostly occur due to natural phenomena, beyond human control. However, if power systems are expected to recover automatically and to continue delivery power, they have to be well designed. If so, very little inconvenience will be experienced by customers. Achieving this is hardly possible without high costs in terms of manpower and equipment. The result of an open market economy is that power systems are forced to operate much closer to their limits of stability; therefore, the decisions of operating personnel must be based on an accurate, online system information and simulations. The current practice of extensive offline simulation of a comprehensive set of possible system operating conditions is good for training purposes but is less useful in real time power system operation situations. As a side effect of liberalized transmission access, networks have to accommodate MW transfers that can be quite different from those for which their transmission networks were originally planned. This is mainly because of the possibility for parallel flows to occur, which is often the case with energy transactions across multi-area systems. Low bus voltages and significant network loadings can occur. The risk of such deteriorated operating conditions, causing blackouts due to instability, increases when a large amount of MW is transferred across a stability-constrained transmission corridor. Furthermore, there are other causes, such as a major disturbance occurring, or even if an otherwise insignificant topology change (such as a minor line trip) happens in a system already operating near its maximum load ability limit. The abovementioned facts highlight the need to compute stability limits for the current and next-day operations processes, thereby foreseeing whether the transmission loading progresses and it is projected to maintain in secure operating reliability limits. 2 STABILITY ASSESSMENT IN THE SCADA/EMS 2.1 SCADA/EMS The main function of the control centre is real time data acquisition from the entire power system so that the operator can monitor its operation. Manual operation of controls, such as changing transformer taps or opening or closing circuit breakers is also a significant part of a control centre's function. These functions are all together known as Supervisory Control and Data Acquisition (SCADA), and the control centre is often referred to as SCADA. Most of the SCADA functions are executed in real time. The monitoring of data generated by a real-time process is a typical example of real-time activity. However, the information generated in SCADA system can also be used in other ways that do not qualify as real time. A data warehouse can be created from historical data and used for post-analysis. Together with advances in information technology, the computational power of the control centres has grown, and consequently more functions have been added. The most prominent one recently added has been the state estimator. It calculates the real time steady state model of the network. This model can thus be used for two kinds of real time calculations. One, known as security analysis, can study the effects of disturbances (contingencies) and can alert the operator if the post-contingency conditions violate limits. The other, usually using a set of analysis tools known as optimal power flow, can be used to suggest better operational conditions to dispatchers. The abovementioned advanced analytical tools provide better operational guidance to the operator and can provide more efficient operation than the old SCADA systems could. Those functions are now known as Energy Management Systems (EMS). 2.2 Real-Time Stability Assessment Possibilities There are at least three ways to distinguish on-line security assessment, [2]: • Distinguishing computer analysis and simulation of contingencies from direct monitoring of the current operating point, • Distinguishing the criteria of types of phenomena: thermal overload, voltage stability problems, or angle stability problems, • Differing between preventive countermeasures because of a potential disturbance threat and corrective countermeasures that follow the occurrence of the actual disturbance. The transient stability problem is, unfortunately, far too demanding on computers for true realtime performance, especially if using the conventional time-step simulation method. The outcome of transient stability calculations depends on the initial state, but there is also an issue of the critical dependency on the duration and the location of the fault in the network. Accordingly, determination of system stability requires immense computational effort even for medium-sized networks. Another issue arises regarding the representation of injections in tie lines by SCADA/EMS models. On the border line, the internal network model, and the external system, the incoming power flows (imported power) are usually shown as generated powers being injected into the internal network. Since the abovementioned generators are not actually generators, some other way must found to represent them in the stability calculations. One way of solving this issue is to introduce dynamic equivalents to the model. The capability of a power system to retain its stability in the presence of slow deviations in the total demand is another type of stability. Practically, an operator needs to know how much additional load can be handled by the transmission system starting from the current state if the load and, consequently, generation and imports would be increased progressively. This can be referred to as steady state stability. Large disturbances caused by faults, loss of equipment, and so on are not part of the transient stability problem. The limit of steady state stability corresponds to the maximum load; moreover, a wheeled power system is able to cope in the current system configuration without collapsing. Imbalances in increases of transmission capacity and growth in the use of electrical power bring many power systems close to limit of stability. Large transfer capacities make power systems more flexible and robust than those lacking the ability to accommodate certain power transfers. One indicator of power system security is certainly the system's transfer capacity. Real-time cognition and the monitoring of the steady state (voltage) stability limit is highly valuable for the system operator. For that information to be usable as a simple indicator, a limit should be set in terms of a "distance" to instability; specifically, the indicator answers the question about how far the current system is from the defined limit. Voltage control is always a local control, but one must be aware that controlling the voltage at one node affects the neighbouring nodes. 2.3 Voltage Stability Voltage stability is considered to be the ability of a power system to maintain voltages in acceptable ranges at all buses in an observed power system under normal conditions and after disturbances occur. Voltage stability assessment is becoming increasingly complicated as power systems are strengthened. To substantiate that, it should be noted that voltages do not indicate the proximity to voltage collapse point in heavy loading conditions or even in heavily compensated systems. In previous decades, transient angle stability has very rarely been a reason for the restriction of power transfers due to stronger power systems and the development of new equipment technology. Nevertheless, over the past 20 years, the power system blackouts occurring throughout the world have been voltage collapses in most cases. Voltage instability progress is rather slow, so the dynamic security analysis techniques do not yield satisfying results in voltage collapse detection. Accordingly, separate software is required for voltage security analysis. The continuation of power flow programs use a special technique to obtain a convergence of the power flow solution near voltage collapse conditions and, therefore, are the main off-line tool used to study voltage conditions in networks. This ensures a method for determining the limits in order to avoid voltage collapse. Using these kinds of techniques online has been described in other articles [15], [16]. It has been stated that the static and dynamic security assessment tools provide much information about voltage trends in real time system under contingencies, and that they should be used as a basis for voltage collapse prediction. The static security assessments, for instance, calculate voltages for each contingency, and a voltage collapse limit alert is triggered if there are voltages that are particularly low. If there is no convergence in power flow studies for a contingency, it may be an indication of voltage collapse and continuation of the power flow should be performed. One problem that exists on online security monitoring is finding the distance of an operating point from stability. Such a measure may be qualitative or quantitative. A qualitative measure does not give the exact megawatt margin but a number, i.e. a stability index that can be interpreted as a degree of stability. For quantitative evaluation, the exact active power value of deviation to stability with respect to a credible scenario is known. Displaying the exact active power value can be computationally highly intense, so the focus is generally in generating a precise voltage stability index. In online applications, these indices are tended to be kept in a way that simplifies their calculation from the online measurements available. If on-line analysis is not possible, the offline study results must be translated into operating limits and indices that are easy to monitor and understand by the operating personnel. The basis of the online security assessment is usually offline computed security limits, such as transfer limits at interconnections. The data warehouse holds the security limits, and the data monitored online is compared for the closest match in the database. Operators commonly recognize these security limits as a security boundary. The uncertainty of offline security assessments that are typically done months in advance of actual operation is minimized with the use of emerging technologies of online security assessment. The security assessment involves the simulation of the potential contingencies and effects on power systems online, i.e. closest to real time as possible. The study mode of security assessment is useful for determining power transfer capabilities, but the user has to be aware of some conservative assumptions made by the offline system. If new conditions occur that are potentially not well understood, real-time assessment can immediately assure ongoing operation in a secure state. The first step in comprehensive security assessment is voltage security assessment. It can be done via power flow simulation; since voltage security encompasses localized problems, it is simpler than inter-area dynamic security assessment. Currently, voltage criteria very frequently limit power transfer in power companies. On-line security assessment requires static state estimation, which is difficult to perform in large power systems. The monitoring of reactive power is an essential part of voltage stability assessment actions. If reactive power sources are near their limits, then voltages are insecure even if voltage magnitudes are within acceptable ranges. Reactive power reserves and high and low reactive power outputs are sensitive indicators of non-secure voltage situations. Emergency control of voltage stability has the primary goal of halting the progress of an unstable scenario before it progresses toward a voltage collapse. Therefore, timing is critical, i.e. time to detect the instability and time to start applying the emergency control is crucial. There are a diversity of measures for voltage stability control in emergency conditions, including reactive device switching, tap changer control, generation rescheduling, and load shedding. 3 MODERN CONTROL CENTER The common current technology of monitoring and control may be summarized thusly, [8]: a. Contingency screening is the basis of the security assessment, which is mainly a steady state power flow analysis. b. Local information is mostly the basis of the protection and control system. In recent papers, [11], Special Protection Schemes have been described in the global impact sense. Offline studies are used to adjust control strategies, so generally the coordination of different protection and control systems is limited. c. State estimation output is the basis of the monitoring system. It is subject to a considerable delay at the scale of tens of seconds to minutes. Usually, it is based on the local control area information. Interaction with neighbouring system is limited in most cases. In order to eliminate these limitations, control centres built in the future are expected to make the most of wide-area information for online, measurement-based real-time security assessment, which would ensure the implementation of an automatic and decentralized control strategy. Monitoring systems in control centres currently depend on a state estimator that is based on data collected via remote terminal units and SCADA. Future control centres should obtain the system level information from the state measurement module based preferably on a Phasor Measurement Unit (PMU). From the state measurement based on a PMU, higher efficiency is expected than at present since synchronized phasor signals give the state variables, specifically voltage angles. Data collected from Remote Terminal Units (RTU) is not synchronized, and a major effort must be made in order for bad data to be detected and the topology to be checked; therefore, the present state estimation requires more running time and is less robust. In the future, state measurements should replace state estimates. An innovative technology called "on-line pre-decision" is the future of stability control in power systems. Decision making will be provided in five minutes as a result of online decision-making technology. Using this system will enable the calculation of the decision table to be formed online, and necessary suggestions can also be given to the grid dispatching operators together with instructions. 3.1 True Stability Margin Monitoring If there is possibility of using state variables from state measurement, displaying the true system stability measures in real time is more feasible. Usually, only voltage magnitude is displayed, and that is insufficient information for the determination of the voltage stability margin. "As the system is more stressed and voltage collapse is a recurring threat, the voltage magnitude is no longer a good indicator of voltage stability. Hence, a true indicator of voltage stability margin is needed for better monitoring", [7]. Most of the current technology relies on monitoring frequencies on a small area. The frequency and phase of all power generation units must keep their synchronism within narrow limits in order to keep the power grid stable. If the generator frequency falls below 50 Hz, it will rapidly heat in its bearings and eventually destroy them. Therefore, at that point, frequency protection detects frequency variations and sends a command to the circuit breakers and trips a generator out of the system. Even small frequency changes can be indicators of instability in the grid. In order to enable identifying the fault in remote locations, and to prepare for possible instability, the frequency in the wider area and its change must be monitored and traced. Using the proposed technology together with the assistance of the wide-area GIS data would make displaying the voltage stability margin and trends of changes in frequency in real time on the top layer of the actual wide-area GIS map possible. Current technology mostly relies on simulations and visualizations of local measurements. In the future, a measurement-based stability margin monitoring system will greatly aid operators in the prediction and identification of potential realtime operation problems. 3.2 Dynamic Security Assessment After outages, a static security assessment checks for limit violations, but with assumes that the power system is in a steady state in the post-outage time. Since outages are usually the results of an accidental short-circuit that causes the isolation of the short-circuited elements by protective systems, the power system may experience significant outing in the voltages and power flows during such disturbances, [10]. If a severe enough disturbance occurs, these swings may cause generators to become unstable. In that case, widespread outages would occur instead of a single outage. Those short circuits or contingencies that cause instabilities are identified by the dynamic security assessment. No contingencies should make the system unstable if it is operated within its limits and properly planned. Nevertheless, in real-time operation, the power system happens to end up in conditions that were not foreseen when the planning was done. It is important to analyse whether such contingencies can make the system unstable. The stability calculations are even more computationally intensive and time consuming than the power flow calculations, so the online checking of stability in hundreds of possible contingencies is an exhausting task. Dynamic security assessment has become a reality thanks to the continuous falling of the price-performance ratio in information technology. Running a static security assessment has led to some new techniques as well as new algorithms, all of which have been very useful in developing dynamic security assessment tools. Contingency screening based on the concept of rapidly isolating the worst contingencies is also applicable for dynamic security. The task is to isolate the few unstable contingencies among most of the stable ones. A rapid approximate method is needed via contingency screening in order to determine the stability of the system. One common and accurate method is the time domain solution performed over sufficiently long time periods that allow the trajectories to depict stable or unstable behaviour. The approximate method calculates the time domain solution for a short time just beyond fault clearing and then projects the stable or unstable behaviour from these trajectories by performing other calculations. There are various techniques that are used: transient energy and their margins, signal energy, different coherency measures and the equal area criterion, [10]. Ranking the contingencies in order to determine the worst cases is possible via these measures. The traditional time domain solution can be used to accurately determine the stability of the system once the worst cases are determined. The abovementioned techniques work quite well for systems that are at high risk for instabilities caused by a lack of synchronizing power. These instabilities can be detected using fewer calculations because they occur very quickly, within a second or so. Those instabilities that occur after several oscillations because of negative damping are difficult to detect without detailed and longer simulation or by using modal analysis. Online dynamic security assessment is still not available for these kinds of systems, and conservative operating limits calculated offline are, unfortunately, the only answer. When the dynamic security assessment detects instabilities (although those are rare cases), the operator, once alerted, needs to take preventive action. When a contingency occurs, the rush of instability is very fast, so the possibility of the operator to take manual corrective action is rather slim. Sometimes, the operator may be able to trip special protection devices to shed load or generation, which will ensure stability. A common case is the modification of the generating pattern, which the operator uses as the available preventive action. Because this increases the cost of operation, methods to quickly calculate the minimum changes required to maintain stability for a particular contingency are being explored. The simplest way known to do this is by recalculating the power flow limits on a certain transmission corridor. 4 WIDE-AREA STABILITY AND VOLTAGE CONTROL There is a synergy between on-line security assessment and wide-area controls. Wide-area stability controls are presently utilized mainly as so-called special protection systems. They can be also referred as remedial action schemes. These schemes are about the direct detection of severe outages. Detection is followed by transferring commands for generator tripping or other discrete feed-forward stabilizing actions. Using such controls is commonly based on direct monitoring, i.e. system conditions observed by control centre operators and/or dispatchers; the system conditions for arming such tripping are determined by off-line simulation and analysis. These controls only operate for predetermined outages, in comparison to response-based controls. It is realistic to expect more sophisticated wide-area stability controls in the future. While local stability controls are normally used and generally preferred, there are opportunities for using more advanced wide-area or centralized controls. Superior observability is the driving force behind using remote signals, [2]. Centralized controls can take action based on a large information base, and they are often a switching action. 4.1 Wide-Area Protection System for Stability The modern power system and its stability characteristics are becoming increasingly complicated along with the increase of transmission distance, growth of loads and the composite structure of HVAC and HVDC systems. There are advanced systems that are made for the purpose of protecting the power system from blackout, and they also can significantly improve the stability of the power grid. The main defence lines of that system are: a. Fault Clearing. It is based on accurate and fast protective relays whose job is to ensure that the fault can be quickly cleared, thereby ensuring the stability of power system. There are reliable and high-speed protection products that can ensure that the fault is quickly cleared before the system loses the stability, thanks to innovative protection elements that can significantly reduce the pickup time to trip the fault. b. Load Shedding and generator shut-down is used in severe contingencies for emergency control. Rising of the load and generation unbalance will provoke the wide-area protection to take some intervention, such as generator shut-down or load-shedding, to ensure stability. If a stability loss in the power system is detected after the serious fault is cleared, wide-area protection and the control system calculate the power flows and generate corresponding control strategies. Control commands are then sent to the executing device so that prompt intervention can be made in order to maintain the stability of the system. c. Out-Of-Step Islanding is local corrective control for extremely severe contingencies. If the above-described fault clearing and load shedding cannot maintain the power system's stability, then the third line of defence will be activated in order to avoid the collapse and minimize the load loss. This third line includes control devices such as out-of-step protection and frequency-voltage to maintain the system stability. The theory behind the out-of-step model of system protection is avoiding any element in power system that may trip while stable swings are on. When synchronicity is lost between two areas of same power system, or two interconnected systems, these areas must be detached as soon as possible. This is performed automatically in order to avoid equipment damage and the shutdown of major portions of the power system, [14]. Uncontrolled circuit breakers trips while the power system is in an out-of-step state can cause equipment damage and potential danger for utility personnel. With this method, it can be concluded that controlled manipulations of indispensable power system elements are necessary in order to prevent equipment damage and severe wide-area power outages, as well as to minimize the negative effects of the disturbance. 4.2 The Future The merging of information and control can definitely be considered to be the future in on-line security assessment and wide-area control. One distinct challenge is the development of wide state estimation on interconnections. Rapidly developing information-age technology is crucial in meeting this challenge. This includes advanced systems such as integrated substation and power plant control and protection, advanced sensors, phasor measurements, communications through fibre optic and WAN and LAN technologies. In control centre-based centralized control, where a large measurement and information database is available, new control technologies such as intelligent automated controls may be applicable. 5 CONCLUSION Adequate planning and proper operational procedures with smart decision making are crucial for maintaining the security of the power system. Current technology and a vision of the future are discussed, and a comparison between those two is given. Modern technology, specifically in terms of improvements in computers, communications and controllers, is already being used in power systems in many ways. By combining these technologies, it is possible to develop wide-area controls for power systems, which enable controlling stability better and, consequently, increasing transmission limits. New control technologies, i.e. intelligent controls, may be applied for control centre-based centralized control where large amounts of measurement and information data base are available. Steady-state contingency analyses are generally the best that the present on-line analyses in control centres typically perform. The reach of those analyses is analysing each credible contingency event by using contingency power flow studies and identifying line flow violations. Future control centres are expected to have online time domain-based analysis. That would imply the ability to perform voltage stabilization and transient angular stability in real time. References [1] C .W. Taylor: Power System Voltage Stability, New York: McGraw-Hill Education, 1994. [2] C .W. Taylor: The Future in On-Line Security Assessment and Wide-Area Stability Control, Bonneville Power Administration, 2000. [3] T .E. Dy-Liacco: Control Centers Are Here To Stay, IEEE Computer Applications in Power, 2002. [4] D .Q. Zhou, U.D. Annakkage, A .D. Rajapakse: Online Monitoring of Voltage Stability Margin Using an Artificial Neural Network, IEEE Transactions on Power Systems, 2010. [5] B. Fardanesh: Future Trends in Power System Control, IEEE Computer Applications in Power, 2002. [6] J. Hauer, D. Trudnowski, G. Rogers, B. Mittelstadt, W. Litzenberger, J. Johnson: Keeping an Eye on Power System Dynamics, IEEE Computer Applications in Power, 1997. [7] G. M. Huang and L. Zhao: Measurement based Voltage Stability Monitoring of Power system, PSERC publications, 2001. [8] F. Li, P. Zhang and N. Bhatt: Next Generation Monitoring and Control Functions for Future Control Centers, 2009. [9] Cigre TF 38.02.12: Criteria and Countermeasures for Voltage Collapse, 1995. [10] A. Bose, K. Tomsovic: Power System Security, Washington State University, 2000. [11] M. Zima: Special Protection Schemes in Electric Power Systems, Literature Survey, 2002. [12] L. Jozsa: Uvod u problem stabilnosti, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, lectures [13] L. Jozsa: Power System Control, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, 2005. [14] D.A. Tziouvaras, D. Hou: Out-of-step protection fundamentals and advancements, Schweitzer Engineering Laboratiories, Inc., USA, 2004. [15] M. Nizam, A. Mohamed, A. Hussain: Performance Evaluation of Voltage Stability Indices for Dynamic Voltage Collapse Prediction, Journal of Applied Sciences, 2006. [16] H. Pradeep, N. Venugopalan: A Study of Voltage Collapse Detection for Power Systems, IJETAE, 2013. Journal Of JE1 Volume 7 (2014) p.p. 43-58 Issue 4, November 2014 Energy Technology www.fe.um.si/en/jet.html A SPATIAL EVALUATION OF THE IMPACT OF AIR POLLUTION: A GIS-BASED APPROACH VREDNOTENJE PROSTORSKIH VPLIVOV ONESNAŽENJA ZRAKA NA PODLAGI GIS-OV Natalija ŠpehR, Blaž Barborič, Nataša Kopušar Keywords: air quality indicators, Bosnia and Herzegovina, living environment, Montenegro, Slovenia, spatial evaluation Abstract The common denominator of the three areas discussed in this paper is basin-type terrain; all areas of the research were thoroughly transformed by human activities (mining, production of energy, industry, settlements and associated infrastructure) in the second half of the 20th century: 1) the wider area of Plevlja Community in Montenegro; air quality indicators were monitored at 19 sampling places; 2) Tuzla basin in Bosnia and Herzegovina as a heavily polluted landscape (industry, energy production, heating of private furnace); 20 monitoring sites were placed there. The anthropogenic environmental pressures have not been reduced; 3) Šalek Valley (Slovenia) as an example with an entire range of well-established technological environmental solutions and measures in the manufacturing sector with 34 measuring points. In all three cases, very active transport activity caused by different users represents significant environmental pressure. R Corresponding author: Asst. prof. Natalija Špeh, PhD, Tel.: +386 3 8986 417, Fax: +386 3 8986 412, Mailing address: Trg mladosti 2, 3320 Velenje, Slovenia E-mail address: natalija.speh@vsvo.si ш The evaluation of the quality of the living environment was made indirectly, using the environmental indicator method. The basis of the survey was carried out during the winter heating period, since we intended to determine the presence of some air pollutants and their effects (especially spatial ones) on the quality of the living environment. Principally, the researched areas are more delicate in the winter period, because private heating system fossil fuels are used. We monitored sulphur dioxide and nitrogen dioxide. In the survey, the method of measurement with diffusion tubes placed at various outdoor locations of the living environment was used, with locations in rural and urban area. We wanted to add an applied value to the preliminary results of measurements, so these results were used for the spatial presentation below. Both can play an important role in the municipal spatial planning of socio-economic activities, e.g. settlement, educational and medical institutions, manufacturing facilities. Furthermore, we intend to show the obtained results of the air quality level in relation to the data on morbidity in the treated areas, i.e. cardiorespiratory diseases. Povzetek Območja raziskave so v 2. polovici 20. stoletja močno preoblikovale in obremenile človekove dejavnosti: rudarstvo, energetika, industrija, poselitev in pripadajoča infrastruktura. V prispevku obravnavamo tri območja s še enim skupnim imenovalcem - kotlinski pokrajinski tip: 1) širše območje občine Plevlja v Črni gori, kjer smo antropogene pritiske na kakovost zraka spremljali na 19 merilnih mestih; 2) Tuzlanska kotlina v Bosni in Hercegovini, 20 merilnih mest, okoljsko obremenjevanje ne po-jenjuje (kemična industrija, termoenergetika); 3) Šaleška dolina s celim nizom uvedenih dobrih tehnoloških okoljskih rešitev in ukrepov v proizvodnih dejavnostih, kjer smo izpostavili 34 merilnih mest. Kakovost bivalnega okolja smo vrednotili posredno, z merjenjem kazalcev za zrak v zimskem (kurilnem) obdobju. Tako smo se odločili predvsem zaradi tujih območij, kjer v hladnem delu leta zasebna kurišča zaradi rabe fosilnih goriv močno vplivajo na kakovost zraka. Ugotavljali smo prisotnost nekaterih zračnih onesnažil ter njihovo prostorsko razporeditev in vpliv na kakovost bivalnega okolja. Spremljali smo vsebnost žveplovega dioksida in dušikovega dioksida v zunanjem zraku. Na terenu je bila uporabljena metoda merjenja s pasivnimi difuzivnimi vzorčevalniki, nameščenimi na lokacije s funkcijo bivalnega okolja. Rezultatom meritev smo želeli dodati aplikativno vrednost in jih prikazali tudi prostorsko. Imajo lahko pomembno vlogo pri nadaljnjem umeščanju posameznih dejavnosti, npr. poselitev, izobraževalne in zdravstvene ustanove, ter proizvodni obrati v preučevanih območjih. V nadaljevanju raziskave želimo prikazati dobljene rezultate kakovosti zraka v razmerju do podatkov o obolevnosti, predvsem kardiorespiratornih bolezni, na obravnavanih območjih. 1 INTRODUCTION The combination of environmental impact assessments (EIA) and GIS (Geographical Information System) could provide an approach to explore the scope of the evaluation of air quality. GIS can be used to obtain the spatial information for the assessment of air pollution impact in various suburban and rural areas. Such information serves as an example to quantify the negative impacts of ambient air quality associated with any planned projects of anthropogenic origin. The approach utilized the spatial evaluation of air pollution and aids in providing critical insight to the assessment, which is not apparent while carrying out such activity in the traditional manner. That kind of study could encourage spatial planners to make wider application of the technique for an in-depth assessment of environmental impacts, [3]. The Slovenian Environment Agency has been monitoring air pollutants in the ambient air by using diffusive samplers since 2003, [7]. Slovenia has been obliged to adopt two European Directives on ambient air quality. The directives establish, [10]: • Ambient air quality standards, in particular the target, limit, warning, critical and alert values for ambient air quality in order to avoid, prevent or reduce adverse effects on human health and the environment, • Ways of informing the public on overcoming the threshold values for certain pollutants, • An obligation to draw up plans and measures for maintaining and improving air quality. Fieldwork was carried out in three areas, in different nations, but related by geophysical characteristics. All belong to the basin area type, especially sensitive in terms of the self-cleaning ability of the air. Locally, the most variable factors depending on the terrain are the wind speed and the wind direction. The direction of wind is usually dominated by the axis of the valley. The wind at the bottom of the valley is the weakest, while its speed increases with the height of the valley slopes, [8]. Winter is also unfavourable due to frequent foggy days and the occurrence of temperature inversions. Two areas of inversion have been identified: a) a terrestrial temperature inversion layer, which protects the bottom of the valley from the air pollution, as there are usually high exhaust chimneys of thermal power plants up to 230 m, and b) a higher subsidence temperature inversion layer, that closes the flue gas path from a thermal power plant. These accumulate below the top layer of the air with a temperature inversion, and then the slope winds move down towards the bottom of the valley; as a result, the terrestrial inversion is not achieved, [6]. The researched sites have inherited similar social development policies. Their appearance today is energy-intensive and industrialized (there are thermal power facilities of national significance), concentrated with settlements and associated infrastructure. Šalek Valley represents an isolated role as an example of a thoroughly improved environmental landscape, while environmental measures in the other two areas are lagging behind (both in the perception of air pollution and the implementation of remediation). Periods of exposure to diffusive samplers coincided with a cold period due to a lack of available sampling materials, and measurements were performed sequentially in Šalek Valley between the 20 November and 4 December 2009, from 27 October to 18 November 2010 in the Tuzla basin, and from 27 October to 22 November 2012 in Montenegro. We wanted to determine the presence of certain air pollutants and their spatial distribution. To measure the quality of the living environment, we deliberately chose to use the fossil fuels most consumed in winter. Based on the results of air quality measurements and trends of urbanization, we can systematically track changes in the environment and coordinate them with the spatial needs of different socio-economic activities, [4]. 1.1 Air quality indicators The Slovene Regulation of sulphur dioxide, nitrogen oxides and particulate matter in ambient air, [12], was replaced in 2011 by the Regulation on ambient air quality, [11]. By 2005, the hourly limit value for nitrogen dioxide was 200 g/m3, which was not supposed to happen more than 18 times per calendar year. Later, the threshold value steadily decreased (in 2005 50 g/m3, in 2006 40 g/m3, in 2007 30 g/m3, in 2008 20 g/m3 and from 2009 onward 10 g/m3). The value for the calendar year until 2005 amounted to 40 g/m3, then decreased (in 2005 10 g/m3, in 2006 8 g/m3, in 2007 6 g/m3, in 2008, 4 g/m3, and from 2009 onward 2 g/m3). Table 1: Allowed concentration, limit values and tolerance (in mg/m3) for NO2 and SO2 comparison between Slovenia, Montenegro and Bosnia and Herzegovina SO2 [^g/m3] NO2 [^g/m3] hourly daily hourly annual Bosnia and Herzegovina 350 (alarm value 500) 125 200 (alarm value 400) 40 Montenegro 350 350 or 200 bay mass flow of 1800 g/h Slovenia 350 (may not be exceeded more than 24 times per calendar year) 125 (may not be exceeded more than 3 times per calendar year) 10 2 1.1.1 Nitrogen Oxides The indicator shows the total emissions of nitrogen oxides (NOx), indicating mostly the impact of traffic. In 2011, road transport Slovenia contributed 54% of the total emissions of nitrogen oxides. The energy sector is the second largest source of these pollutants. Data for annual NOx emissions for Slovenia in the period from 1987 to 2007 showed a reduction of emissions in 2007 by almost 20% compared to 1987. The decrease happened due to higher proportion of vehicles with catalytic converters. NOx emissions in 2007 were 1% lower than the predicted target value. The level of air pollution with nitrogen dioxide in the 1992-2008 period fell below the prescribed limit average annual concentration. Only in Maribor did the annual concentration throughout the 1992-2008 period exceed the critical value of annual NOx for the protection of vegetation and ecosystems, mainly due to the influence of surrounding traffic. 1.1.2 Sulphur dioxide In Slovenia, the level of ambient air pollution with sulphur dioxide in urban areas, according to the limits laid down in the Regulation on ambient air quality, [11], does not reach levels dangerous to human health. Moreover, critical annual concentrations for the protection of vegetation are not exceeded. Improvement of the air quality in the previous decade is attributable to the higher grade of the fuel (higher quality coal, oil, gas) plus activation of desulphurization plant of the TPP Šoštanj and Trbovlje. In the Zasavje region, a purifying plant in the Lafarge factory was installed. In Slovenia, the SO2 emissions were reduced by 2007 to 94% compared to 1980. The decrease was primarily due to lower and controlled releases from power plants and the use of higher quality fuels. Emissions of SO2 in 2007 were 47% lower in comparison to the predicted target value. 2 METHODS AND MATERIALS 2.1 Diffusive samplers method As a basic material for the research fieldwork, we used the diffusive samplers. This method works on the principle of pollutant transport in the sampler by means of molecular diffusion. Samplers are tubes that stay open at one end during the time of sampling and are continuously exposed to the ambient air. At the closed end of the tube, there is a membrane with a reagent to a given substance (pollutant). Pipes should be opened just before exposure and closed immediately afterwards. The recommended exposure time is 14 to 21 days. The advantages of this method are flexibility, convenience, affordability and, therefore, the possibility of a recurrence of sampling, which increases the usefulness of the method. Due to the lower reliability of the method, it can be complemented by parallel measurements of data at automatic stations. The results provide with information about the average pollution values for the period of exposure, but not maximum, hourly and daily values, as required by legislation, [11]. Figure 1: Exposure of diffusive samplers 2.2 Inverse Distance Weighted method (IDW) Each method of interpolation determines or estimates the value of the measurements at selected locations, which lie in locations with a known monitored value. The quality of the approximated model surface depends on the measurement that is interpolated, the allocation (distribution) of sample points, and the chosen interpolation method. In principle, the denser and more homogeneous distribution of the given points leads to a credible result. The method of inverse distance weights (IDW) assumes that any given sample point has its local impact, which decreases with the inverse potency of the distance from the interpolated point. Points closer to the interpolated point are weighted (influential) more than more distant ones. The IDW method assesses the value of the intersection of the two profiles of the cellular network by calculating the average value of the given sample points near each intersection. This approach thus allows a greater impact of closer points than more distant ones. The method is applicable in cases in which the influence of the studied variables decreases with the distance from the sample locations. For example, the interpolation of point location of pollutants, the concentration decreases with distance from the location of contaminants, and the use of this method is logical. The disadvantage of this method is that the approximated surface can reach local extremes (minima and maxima) only in the given point, which does not reflect the situation in nature. The IDW method is suitable for the preview of the approximated surface, [2]. 3 RESULTS AND DISCUSSION The data for measured values of the monitored air quality indicators were processed with the basic statistics. Due to the low number of sample points (19-34), the most appropriate interpretation of the results was to use the mean value of the median. Measurements revealed the highest mean (median) in the measured period for NO2 emissions in the municipality Plevlja in Montenegro (20.22 mg NO2/m3). The Tuzla basin followed with 13.68 mg NO2/m3, and the least burdened air with NO2 was measured in Šalek Valley. The indicator of sulphur dioxide in the ambient air pollution had the highest value of 45.85 mg SO2/m3 in the area of Tuzla. The wider area of the municipality of Plevlja in Montenegro tended to have almost the half of the concentration of sulphur dioxide pollution (23.57 mg SO2/m3), while the average value of this indicator in Šalek Valley was negligible (0.01 mg SO2/m3). Table 2: The calculated mean value (median), average, standard deviation from the average and maximum measured concentrations of NO2 and SO2 in the discussed period and in selected areas. Area/Pollutant no2 [Mg/m 3] SO2 [Mg/m3] TUZLA (n=20) median 13.68 45.85 average 14.02 44.95 st. deviation 11.56 23.22 maximum 37.99 88.49 PLEVLJA (n=19) median 20.22 23.57 average 19.61 23.95 st. deviation 8.69 12.47 maximum 34.08 50.14 ŠALEK VALLEY (n=34) median 13.29 0.01 average 14.96 1.61 st. deviation 3.99 2.65 maximum 22.21 9.42 The maximum concentration of NO2 was measured in Tuzla (37.99 mg NO2/m3). The data for Plevlja showed 34.08 mg NO2/m3 and the least air pollution pressure was evident in Šalek Valley (22.21 mg NO2/m3). Even after the measured concentrations of SO2, as calculated by the maximum value, the outstanding result was found in the Tuzla basin (88.49 mg SO2/m3), followed by the municipality of Plevlja (50.14 mg SO2/m3). The least laden ambient air with sulphur dioxide was measured in Šalek Valley (9.42 mg SO2/m3). (c) Figure 2: The spatial display of the measured values for SO2 in the researched areas (a) - Tuzla basin in Bosnia and Herzegovina (b) - the area of the Plevlja municipality in Montenegro and (c) - Šalek Valley in Slovenia The spatial distribution of the measured indicators for the quality of air produced by the GIS (Geographic Information System) approach reflects the pollution of the individual parts of the areas of research. Based on the pollution measurement of the ambient air and the appropriate number of repeated measurements with the denser (systematic) monitoring network, we could determine more detailed findings on air quality. In addition, microclimatic conditions (flow of air) and meteorological data for days of exposure of the samplers should be taken into account. Such data on air pollutants may be an appropriate form of assistance for spatial planners in assessing and allocating activities and their potential effects on the environment. The data are also useful in the design of remedial measures and programmes. 3.1 Tuzla basin Measurements were performed at altitudes of 221 to 326 m above sea level. They revealed a very strong contamination of the site Tuzla basin with sulphur dioxide. The highest measured values are shown in a cartographic representation for the area Mejdan in the city centre, close to the university and associated faculties, [14]. The highest measured value (88.49 mg SO2/m3) was also there. The lowest values were found at monitoring sites Bukinje, west of the city. Data for NO2 showed the lowest values in urban areas of Mejdan and Stupine, a residential (blocks of apartments) quarter, which is located south east of the city centre. Low values (up to 15 mg NO2/ m3) were also measured south from the eastern artery into the city. Maximum values reflect the results of measurements of NO2 in the northeast outskirts of Tuzla basin (Grabovica Donja). 3.2 Plevlja The measuring points were set at altitudes of 753 to 1017 m. The basin type of landscape has a typical spatial distribution of sulphur dioxide, i.e. heavily laden at the bottom of the depression and pollution-free edge of the basin. The highest values were measured at three urban locations (between 40 and 50 mg SO2/m3), the maximum at the measurement site Moćevac (50.14 mg SO2/m3) in the northern part of the measurement area. Values from 30 to 40 mg SO2/m3 were characteristic for the rest dense populated area of Plevlja. Less pollution (7-15 mg SO2/m3) was observed by the stations at the W and SE of the basin perimeter. According to the results of NO2 measurements, three locations in the N and NW part of the studied area were outstanding. Again, as the most polluted areas there were three urban sites with the highest value of NO2 at the location Moćevac NO2 (34.08 mg NO2/m3). The lowest values were measured in the western part of the area, outside the dense populated town Plevlja. 3.3 Šalek Valley Diffusive samplers were exposed between 352 and 772 m above the sea level. Despite the very low concentrations of burdening ambient air in the valley with SO2, peak values occurred on the SE edge of the Velenje basin (category 4 to 4.7 mg SO2/m3). Values were reduced to the NW in the town of Velenje with the wider hinterland, where we measured values between 2 and 3.5 mg SO2/ m3. The lowest values were evidenced at all other measuring points of the basin periphery (0 to 0.5 mg SO2/m3). Maximum values for NO2 were measured at the very southern edge of the basin. The sites of the researched area mostly expressed very low levels, with the exception of a mountain location: Graška Gora (category 20 to 25 mg NO2/m3). (a) (b) Figure 3: The spatial display of the measured values for NO2 in the researched areas (a) Tuzla basin in Bosnia and Herzegovina, (b) the area of Plevlja municipality in Montenegro and (c) Šalek Valley in Slovenia. 3.4 Air Quality Index (AQI) The AQI (of the Environmental Protection Agency (EPA)) is an index for reporting daily air quality. It explains how clean or polluted the monitored air is and what associated health effects might be of concern. The higher the AQI value, the greater the level of air pollution and the greater the health concern. For example, an AQI value of 50 represents good air quality with little potential to affect public health, while an AQI value over 300 represents hazardous air quality. The purpose of the AQI is to aid in understanding what local air quality means to peoples' health. Each category corresponds to a different level of health concern. The six levels of health concern and what they mean are, [5]: Table 3: AQI categories and Health Concern Air Quality Index Levels of Health Concern Numerical Value Meaning Good 0 to 50 Air quality is considered satisfactory, and air pollution poses little or no risk Moderate 51 to 100 Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution. Unhealthy for Sensitive Groups 101 to 150 Members of sensitive groups may experience health effects. The general public is not likely to be affected. Unhealthy 151 to 200 Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects. Very Unhealthy 201 to 300 Health warnings of emergency conditions. The entire population is more likely to be affected. Hazardous 301 to 500 Health alert: everyone may experience more serious health effects The highest AQI SO2 concentration results were in the Tuzla area. The third category (AQI index: 146) evidenced an increased vulnerability for the people with respiratory illnesses. There are also warnings relevant to inhabitants subject to asthma in other two researched areas, but with no health effects and cautionary statements. The air quality state in the Bosnian fieldwork area required urgent sanitation measures. Table 4: Air Quality Index (AQI) in the discussed areas after calculation of SO2 concentration Area AQI AQI Category Sensitive Groups Health Effects Statements Cautionary Statements Tuzla 146 Unhealthy for Sensitive Groups People with asthma are the group most at risk. Increasing likelihood of respiratory symptoms, such as chest tightness and breathing discomfort, in people with asthma. People with asthma should consider limiting outdoor exertion. Plevlja 9 Good People with asthma are the group most at risk. None none Šalek Valley 6 Good People with asthma are the group most at risk. None none (AQI calculation accessed at http://airnow.gov/index.cfm?action=resources.conc aqi calc) Measurements of NO2 concentrations revealed the Plevlja area to be the most polluted with nitrogen oxides. An AQI of 102 indicated unhealthy environment for people with increased likelihood of respiratory diseases, breathing discomfort and lung disease. Šalek Valley and the Tuzla basin area also seemed to be risky living environments for children and elderly with respiratory illnesses. Due to the moderate AQI category, prolonged and heavy outdoor exposure should be avoided. Table 5: Air Quality Index (AQI) in the discussed areas after calculation of NO concentration Area AQI AQI Category Sensitive Groups Health Effects Statements Cautionary Statements Tuzla 71 Moderate People with asthma or other respiratory diseases, the elderly, and children are the groups most at risk. Unusually sensitive individuals may experience respiratory symptoms. Unusually sensitive people should consider reducing prolonged or heavy outdoor exertion. Plevlja 102 Unhealthy for Sensitive Groups People with asthma or other respiratory diseases, the elderly, and children are the groups most at risk. Increasing likelihood of respiratory symptoms and breathing discomfort in active children, the elderly, and people with lung disease, such as asthma. Active children, the elderly, and people with lung disease, such as asthma, should reduce prolonged or heavy outdoor exertion. Šalek Valley 69 Moderate People with asthma or other respiratory diseases, the elderly, and children are the groups most at risk. Unusually sensitive individuals may experience respiratory symptoms. Unusually sensitive people should consider reducing prolonged or heavy outdoor exertion. (AQI calculation accessed at http://airnow.gov/index.cfm?action=resources.conc aqi calc) 4 CONCLUSIONS Monitoring of ambient air quality is a key activity in evaluating the state of the living environment or assessing and planning additional burdens in a selected area. Data on air pollution in Slovenian cities suggest high levels of pollution with NO2. In addition, Slovenian urban areas have been increasingly more polluted with particulates of