Strojniški vestnik Journal of Mechanical Engineering Strojniški vestnik - Journal of Mechanical Engineering (SV-JME) Aim and Scope The international journal publishes original and (mini)review articles covering the concepts of materials science, mechanics, kinematics, thermodynamics, energy and environment, mechatronics and robotics, fluid mechanics, tribology, cybernetics, industrial engineering and structural analysis. The journal follows new trends and progress proven practice in the mechanical engineering and also in the closely related sciences as are electrical, civil and process engineering, medicine, microbiology, ecology, agriculture, transport systems, aviation, and others, thus creating a unique forum for interdisciplinary or multidisciplinary dialogue. The international conferences selected papers are welcome for publishing as a special issue of SV-JME with invited co-editor(s). Editor in Chief Vincenc Butala University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Technical Editor Pika Škraba University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Founding Editor Bojan Kraut University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Editorial Office University of Ljubljana, Faculty of Mechanical Engineering SV-JME, Aškerčeva 6, SI-1000 Ljubljana, Slovenia Phone: 386 (0)1 4771 137 Fax: 386 (0)1 2518 567 info@sv-jme.eu, http://www. sv-jme.eu Print: Grafex, d.o.o., printed in 310 copies Founders and Publishers University of Ljubljana, Faculty of Mechanical Engineering, Slovenia University of Maribor, Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia Chamber of Commerce and Industry of Slovenia, Metal Processing Industry Association President of Publishing Council Branko Širok University of Ljubljana, Faculty of Mechanical Engineering, Slovenia International Editorial Board Kamil Arslan, Karabuk University, Turkey Hafiz Muhammad Ali, University of Engineering and Technology, Pakistan Josep M. Bergada, Politechnical University of Catalonia, Spain Anton Bergant, Litostroj Power, Slovenia Miha Boltežar, UL, Faculty of Mechanical Engineering, Slovenia Franci Čuš, UM, Faculty of Mechanical Engineering, Slovenia Anselmo Eduardo Diniz, State University of Campinas, Brazil Igor Emri, UL, Faculty of Mechanical Engineering, Slovenia Imre Felde, Obuda University, Faculty of Informatics, Hungary Janez Grum, UL, Faculty of Mechanical Engineering, Slovenia Imre Horvath, Delft University of Technology, The Netherlands Aleš Hribernik, UM, Faculty of Mechanical Engineering, Slovenia Soichi Ibaraki, Kyoto University, Department of Micro Eng., Japan Julius Kaplunov, Brunel University, West London, UK Iyas Khader, Fraunhofer Institute for Mechanics of Materials, Germany Jernej Klemenc, UL, Faculty of Mechanical Engineering, Slovenia Milan Kljajin, J.J. Strossmayer University of Osijek, Croatia Peter Krajnik, Chalmers University of Technology, Sweden Janez Kušar, UL, Faculty of Mechanical Engineering, Slovenia Gorazd Lojen, UM, Faculty of Mechanical Engineering, Slovenia Thomas Lubben, University of Bremen, Germany Janez Možina, UL, Faculty of Mechanical Engineering, Slovenia George K. Nikas, KADMOS Engineering, UK José L. Ocana, Technical University of Madrid, Spain Miroslav Plančak, University of Novi Sad, Serbia Vladimir Popovič, University of Belgrade, Faculty of Mech. Eng., Serbia Franci Pušavec, UL, Faculty of Mechanical Engineering, Slovenia Bernd Sauer, University of Kaiserlautern, Germany Rudolph J. Scavuzzo, University of Akron, USA Arkady Voloshin, Lehigh University, Bethlehem, USA Vice-President of Publishing Council Jože Balič University of Maribor, Faculty of Mechanical Engineering, Slovenia Strojniški vestnik Journal of Mechanical "''i^'' Engineering Cover: Front cover shows a measurement and welding robotic application for a product called protector installed in cast-iron cooking plates. The robotic cell enables following of few manufacturing parameters of the protector and calculation of a welding point for each individual protector. Besides all measurement and pose transformation calibrations are performed automatically in regular intervals. Image Courtesy: Laboratory of robotics, Faculty of Electrical Engineering, University of Ljubljana, Slovenia Photo: Jure Rejc ISSN 0039-2480 General information Strojniški vestnik - Journal of Mechanical Engineering is published in 11 issues per year (July and August is a double issue). 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Strojniški vestnik - Journal of Mechanical Engineering is available on http://www.sv-jme.eu, where you access also to papers' supplements, such as simulations, etc. Strojniški vestnik - Journal of Mechanical Engineering 62(2016)12 Contents Contents Strojniški vestnik - Journal of Mechanical Engineering volume 62, (2016), number 12 Ljubljana, December 2016 ISSN 0039-2480 Published monthly Papers Jure Rejc, Marko Munih: Robust Visual Touch-Up Calibration Method in Robot Laser Spot Welding Application 697 Weiping Wang, Bo Wang: An Energy-Saving Control Strategy with Load Sensing for Electro-Hydraulic Servo Systems 709 Tjasa Duh Coz, Andrej Kitanovski, Alojz Poredos: Primary Energy Factor of a District Cooling System 717 Cheng Gu, Xinbo Chen: A Novel Universal Reducer Integrating a Planetary Gear Mechanism with an RCRCR Spatial Mechanism 730 Aijun Yin, Juncheng Lu, Zongxian Dai, Jiang Li, Ouyang Qi: Isomap and Deep Belief Network-Based Machine Health Combined Assessment Model 740 Nnamdi Onochie Chibueze, Chinwuba Victor Ossia, John Umunna Okoli: On the Fatigue of Steel Catenary Risers 751 Yu Dai, Liping Pang, Lisong Chen, Xiang Zhu, Tao Zhang: A New Multi-Body Dynamic Model of a Deep Ocean Mining Vehicle-Pipeline-Ship System and Simulation of Its Integrated Motion 757 Strojniški vestnik - Journal of Mechanical Engineering 62(2016)12, 697-708 © 2016 Journal of Mechanical Engineering. All rights reserved. D0l:10.5545/sv-jme.2016.3708 Original Scientific Paper Received for review: 2016-05-03 Received revised form: 2016-09-29 Accepted for publication: 2016-10-07 Robust Visual Touch-Up Calibration Method in Robot Laser Spot Welding Application Jure Rejc* - Marko Munih University of Ljubljana, Faculty of Electrical Engineering, Slovenia The article is describing the use of visual touch-up calibration method for defining the mathematical transformations used in a shop-floor measurement and welding robot cell in the protector assembly process. The presented system is designed as a robust and cheap solution, using only the equipment needed for the production tasks in the robot cell. The main goal of the presented system is to use vision measurement system for measuring and calibration procedures and laser welding equipment to weld two protector assembly parts together where positioning tolerances are very narrow. These narrow tolerances forced us to implement auto-checking and auto-calibration procedures for all necessary mathematical aspects in the robot cell, based on the robust visual touch-up method. To demonstrate adequate solution in the measurement, calibration and also the production sequences, the graphs show production statistical results over a one year production period. Keywords: robot welding, visual touch-up, calibration, kinematic error, transformations Highlights • The presented system enables accurate distance measurements in the industry. • The presented system enables robust visual touch-up robot calibration method. • The proposed calibration procedures take into account all robot kinematic errors. • All calibration procedures are automatic, enabling short production line dead times. • The system uses a calibration procedure that is not well described in the literature. 0 INTRODUCTION Robot spot welding is nowadays present in several industries all around the globe. These systems increase production efficiency [1] and increase the quality of the products. The physical burden on the human workforce is relieved as well as the stress on their health [2]. Many of these systems are present in automotive industry [3] where contact spot welding is mainly used [4]. Besides automotive industry the robotic spot welding is present also in other industries [5] and [6]. Industrial robots have high position repeatability, but have at least a grade worse absolute position accuracy [7] to [9]. The robots are mainly programmed on-line where all robot points are defined or recalculated in regard to the base coordinate system of the robot. However, improvements in technology enable off-line robot programming to be used more and more nowadays. This type of programming saves the robot points in regard to the virtual robot coordinate systems. When these points are transferred to the real system on the shop-floor, usually a point position difference is present and the literature [10] specifies this error as positional absolute error or kinematic position error. The same problem occurs when machine or robot vision [11] systems are used [12], where points in camera coordinate system need to be transformed into the robot base coordinate system. When transforming coordinates from vision system to the robot system, usually the ideal robot kinematic model is used, but real kinematic parameters differ. For this reason an absolute calibration procedure is a must to accurately position the robot on proper position defined by the vision system. To reduce or eliminate the absolute error, manual calibration of the robot system is usually used. But this conventional approach requires a large amount of calibration points, which results in a long calibration time and is therefore not suitable for shop-floor production. In the field of robotic automatic absolute error calibration procedures the reader can find several approaches using 1D and 2D vision calibration systems [13] to [16], calibration with laser trackers [17], image comparison [18], visual touch-up [19] and hybrid sensors using Kalman filters [20]. Most of the presented work for kinematic calibration of the robot system in the previous paragraph was tested in laboratory and used expensive dedicated measurement equipment or additional equipment needed to be installed that limits robot working space. These academic approaches have a large influence on calibration methods development, but are usually not implemented in shop-floor *Corr. Author's Address: University of Ljubljana, Faculty of Electrical Engineering, Tržaška 25, 1000 Ljubljana, Slovenia, jure.rejc@robo.fe.uni-lj.si 697 production facilities [21]. All presented drawbacks forced us to develop the robot automated visual inspection (AVI) and measurement system for measuring and laser welding cell in a way that used previously installed equipment for measuring, welding and for all necessary calibration procedures. Among the presented approaches from the literature the simplified visual touch-up approach was implemented. The article presents the robot cell design, the automatic position error eliminating procedures and the results of installed approach. Presented is statistics for the whole year production analysis. 1 THE ROBOT CELL 1.1 The Protector The robot cell workpiece called protector (Fig. 1) is a control and safety element incorporated into classic cast-iron cooking plates manufactured in different diameters and nominal power. The task of the protector is to turn off the power supply of the heating winding hobs in the event of overheating when the temperature reaches 400 °C ± 50 °C. The basic components of the protector (Figs. 1 and 2) are: ceramic housing, 1.2 mm thick bimetal with the set screw, limiter, toggle element, electrical switch and electrical contacts for connecting wires. When the temperature of the cooking plate is rising, the bimetal bends in the protector and exerts force via the set screw on the limiter. When the pressure on the limiter is high enough, it triggers the toggle element, which represents half of the electrical switch. Fig. 1. The protector and its assembly parts The protector manufacturer was forced to change its design in 2013 for two reasons. The set screw was previously fixed to the bimetal with special glue paint. This solution was practical, but it sometimes happened that the set screw was not fixed enough and the protector switch-off temperature moved outside the tolerances. Also, this special paint was expensive, which called for a cheaper and more reliable solution. The protector redesign declared that the set screw is bonded with the bimetal by laser welding these two assembly parts together. Fig. 2. The field of view of the visual inspection system 1.2 The Robot Workspace and Attached Equipment The robot cell (Fig. 3) is installed in the fourth of the five stages of the rotary table, where the assembly process of the protectors is finished. In this stage the task is to inspect two dimensions called A and B in the protector and to determine the intersection position of the bimetal and the set screw where laser welding of these two parts must be performed. The position of the set screw is set in the previous stage of the rotary table and is not important for the article. Fig. 3. Robot cell as one part of the five stage rotary table The selected robot is Epson G6 650 with 4 DOF and superb repeatability specifications: ±15 ^m for the first and second horizontal axis together, ±10 ^m for the vertical axis and ±0.005 ° for rotational axis. On the end of the robot two independent systems are installed, both necessary for all the production tasks in the fourth stage of the rotary table. The first system is a video camera inspection and measurement system. It consists of a video camera and appropriate optics. Installed camera is a type DMK 41AG02, monochrome with resolution of 1280x960 pixels, produced by The Imaging Source. We have chosen optics from the Keyence company, type CA-LM0510. It is specified as macro lens with C-mount connection. The field of view of this video system is approximately 6 mm x 4 mm, marked with a dotted square in Fig. 1. The second attached system is a laser welding system with appropriate optics. The type of laser welding system is TruPulse 44, manufactured by the company Trumpf with a wavelength of 1064 nm and average power of 40 W. The laser optics is BEO D35 with a focus distance of f = 100 mm and 1 mm laser beam spot. This parameter combined with the bimetal width of 1.2 mm defined the laser welding point (WP) tolerance to ±0.2 mm. The laser welding system is equipped with an additional video camera of the same type as the one in the measurement system and is used for calibration procedures of both systems. The camera attached on the welding system share the same optics, making the laser beam and the video camera visual path coaxial. The production process of the fourth stage of the rotational table starts as follows: six protectors, set in a cluster, are rotated into the robot working space at once. After the cluster is positioned, additional mechanism positions the dedicated LED illumination for all protectors in a cluster. Then the robot positions the video measurement system over the first protector in a cluster, the dedicated image acquisition and image processing software captures the image, which is then processed during the motion to the next protector. When the last protector image in a cluster is processed, the robot moves in the opposite direction from protector to protector and positions the welding optics over the welding point according to the information from the measurement system. The laser welding is not performed if there is an error in image analysis or the measured dimensions A or B are not in defined tolerances. In Fig. 3 two very important parts of the whole system are also seen. The measurement system first needs to be checked and calibrated to ensure accuracy. In our opinion the best object to perform the measurement calibration procedures is a precisely known object that is also measured in the robot cell. That is why three calibration protectors are set in the robot working space in a special chamber protected from laser welding dust as much as possible. The height of the optics in regard to these protectors was set by the same robot vertical Z axis distance as by protectors fixed in a cluster rotated by the rotary table. This is possible because both production and calibration protector clusters are physically set to the same height in the production line. This simple approach minimizes the influence of camera intrinsic parameters error and also the optics distortion error. Both dimensions A and B on all three calibration protectors were previously measured with the certified profile projector measuring system, type Mitutoyo PV500. Each protector has different dimensions A and B. The captured image with all important parameters can be seen in Fig. 2, except that the welding point is not defined during the calibration of the measurement video system. The first two calibration protectors are used to gain the transformation information used to recalculate distances from pixels to millimeters and the last calibration protector is used to check the measurement accuracy. The checking is performed every 10,000 pieces and if the accuracy is inside predefined tolerances of ±0.1 mm for both measured distances A and B then the production line continues. Otherwise the robot moves the measurement system over the first two calibration protectors and a new transformation function is calculated. Then the accuracy checking is repeated on the third protector. If the measured values are still outside tolerances, the production line is stopped with error message and an operator must check the situation. Fig. 4. Calibration coordinate system fixed in robot working space The second important system in the robot working space in Fig. 3 is very simple, yet very efficient as we will show in the article. The 3D model of this assembly is shown in Fig. 4. The assembly consists of an L stand that has a 5 mm hole on the bottom side. It is meant for a 5 mm LED. For better contrast we have chosen a green LED. On the top side of the stand two small holes in the 5 mm LED area are drilled. The bigger hole has a diameter of 0.8 mm and the smaller one a diameter of 0.5 mm. These two holes or dots represent one axis of fixed coordinate system (Fig. 5) in robot working space. The larger dot represents the origin (O) of coordinate system and the smaller a dot on the X axis of the coordinate system. Both dots are separated by 3 mm. Fig. 5. Threshold image of two LED dots with drawn coordinate system 2 THE VISUAL TOUCH-UP METHOD The visual touch-up method is a non-contact version of a standard touch calibration method and can be used in many robot calibration areas. The non-contact method can be connected with contact method if the term of virtual pin is introduced (Fig. 6). Virtual pin is a virtual connection from the robot to the target position. The literature is very poor in the field of visual touch-up method used for robot calibration purposes and only Watanabe et al. [19] published a contemporary research article in this field, which was used as the basis for our approach. Watanabe et al. used a single camera attached on the robot end-effector. The calibration target object is a perfect circle with its center point drawn in the robot working space. The size of the circle is predefined and is used to define geometric relations, where the center point is the target point. The authors state that the drawbacks of this approach are unidentified camera-intrinsic parameters and the distortion of the lens that can both affect calculations. Visual touch-up method can be used for purposes of robot new tool calibration, robot absolute accuracy calibration and also for calibration of several robots carried vision systems as in our case. The non-contact method can use several sensors for calibration procedures: from laser distance sensors based on triangulation [22] and conoscopic holography [23], inductive or capacitive sensors and especially video cameras as Watanabe et al. is presenting. In our case we have chosen the video camera approach, because both on robot attached systems are vision based and also the planar robot movement simplifies the calibration procedures approach (Fig. 6). The reference objects of our visual touch-up approach are small round green dots presented in Figs. 4 and 5. Fig. 6. Visual touch-up system represented on 3D model 3 IMPLEMENTED VISUAL TOUCH-UP METHOD CALIBRATIONS As described in the previous sections, the measurement vision system is checked for accuracy and calibrated by using the calibration protectors. With the implementation of this system, the welding point (PX, PY) is defined in camera image coordinate system [C, independent in regard to any other coordinate systems of the robot cell (Fig. 2). But to be able to transform the welding point (PX, PY) from [C in to the robot reference coordinate system [R and to position the welding optics to the proper position (WPX, WPY) several coordinate systems need to be defined automatically via the visual touch-up method. These calibration procedures calibrate the system only in X and Y axis, where the Z axis is fixed. The focal distance of the welding laser and its attached camera is 11 cm from the welding optics to the observed or welded object, defined with manual calibration stick, provided by the laser manufacturer. The same analogy valid also for the measurement camera, where the focus distance is also near 11 cm, making the stand-off distance also fixed. In other case the captured images are blurred. 3.1 Robot Self-Calibration of the New Welding Laser Optics Tool The robot can position the welding laser optics to the calculated coordinates WPX and WPY if the welding laser optics frame [L] regarding to the robot default end [e] E is defined as a transformation TL or as a predefined robot new tool (Fig. 7), also called tool center point (TCP). In production facilities this is frequently done by manually defining a new tool attached to the end of the robot with a special Epson wizard for manually defining new TCP's named as ToolN (e.g. Tooll). This procedure requires a certain amount of time of at least a few minutes to be finished by the operator and is therefore too inconvenient for a quick recalibration and totally improper for high volume production line. Fig. 7. The positioning of the welding laser optics according to the WPX, WPY welding point In our system the robot makes fast movements that can shift attached equipment, or the operator accidentally hits the laser optics during maintenance of the robot cell. For these reasons an automatic tool calibration procedure for defining the center of the welding laser as a new tool, called Tooll, was developed. Fig. 8. Transformations for new TCP calculation For the automatic tool calibration procedure a bigger LED dot from Fig. 5 is used. The calibration procedure requires positioning of the laser welding optics |L in the center of a reference point (bigger dot), marked as a filled circle in Fig. 8, in two different robot configurations and can be described with Eq. (1) where N is 1 and 2. To make all further figures transparent, only the x axis of the coordinate frame is marked and the z axis points out of the plane. The y axis is set respectively to the right-hand coordinate system. TR _ TR Tl _ TEN ' (1) In this calibration procedure the robot first moves the laser optics to the predefined position (EXN, EYN, aN) in robot reference frame [R, saved in the previous calibration procedure, where the center of the laser optics and the center of the reference point should align. The decision whether the welding laser optics center is aligned with the center of the reference point is made by the dedicated software by implementing a circular Hough transform [24] to [26] on the captured laser optics video camera image. The task of the Hough transform method is to search for objects of different shapes (lines, circles, ellipse) in an image by a voting approach in parameter space. Within this space the objects are gained as local maximum in an accumulator space. Unlike in Watanabe et al. [19] where the error between the reference point and the captured image point is calculated and used in further calculations, we implemented a simple step position controller to reduce the position error inside the predefined tolerance area of 0.05 mm if the movement is necessary. The movement of the robot is in steps of 0.015 mm in both planar axes. The tolerance area can be specified in millimeters because the width of the bigger dot is known and the result of the Hough transform is the radius of the circle in pixels. At this point the current robot TCP position [E] is saved as a new point (EXN, EYN, aN) for the next calibration attempt. With this information a new transformation TR (Eq. (2); N = 1) is set. TeRn = Rot (z,aN ) • Trans (Em, Em, 0). (2) In order to calculate the transformation TL between the end of the robot (E) and welding laser optics (L) a second transformation is needed (Eq. (1); N = 2). It defines the new configuration (Eq. (2); N = 2) of the robot, pointing with the center of the welding laser optics in the same, bigger LED reference point. The procedure is the same as described before, only the robot initial pose is different EXN, EYN, aN where N equals 2. From the matrix in Eq. (3) only position coordinates ELX and ELY are needed and can be expressed as Eq. (4). Coordinates ELX and ELY define the new TCP (saved as Tooll) representing the welding laser optics center (L) relative to the end of the robot (E). Ter = Rot (z,v) ■ Trans (EX, EY ,0). (7) Tle = Trans (ELX, ELY, 0), ELX =(EX1 - EX 2 )-(cosa1 - cosa2) + + (EY1 - EY2 )-(sina1 - sina2), ELy = (Ey1 -EY2)-(cosat -cosa2)- -(EX l - EX 2 )'(sin«l - sin 4.2 Welding Point Calculation (3) (4) Fig. 9. Transformations for welding point calculation Fig. 9 shows the homogenous transformation relations that are important for calculation of the welding point in the reference robot frame [R. The welding point, marked as P, is determined in the measurement camera frame [C]. This transformation can be written as a homogenous transformation matrix (Eq. (5)) marked as with the same orientation as the measurement camera frame [cl. Tt> (5) = Trans (PX, PY ,0). The camera [C] is physically fixed in regard to the robot end [E] described by the transformation T^ (Eq. (6)). This transformation is defined with the distance (ECX, ECy) from robot end frame [E] to the measuring camera frame [c] and with a rotation angle 9 around the Z axis. TCe = Rot (z,3)-Trans (ECX, ECY ,0). (6) The robot end frame |Ej pose in robot reference frame [R can be written as homogenous transformation T^ (Eq. (7)) with parameters (EX, Ey, 0 0, if ^<0' (2) where is the flow gain coefficient of the servo valve, kx is a positive constant, ps is the supply pressure of the pump, pt is the tank pressure, p is the oil density, p1 and p2 are the chamber pressures of the cylinder, Q1 is the supply flow rate to the forward chamber and Q2 is the return flow rate from the return chamber, ud is the input signal of PDV. The pressure dynamics of the actuator can be written as: [À = h1[Q1 - A1Xp - CtPl + CiP2] 1 p2 = h2[-Q2 + A2xp - CtP2 + CiPl ] (3) where xp is the piston position, Ct=Ci+Ce is the total leakage coefficient [17], Ce is the external leakage coefficient, Ci is the internal leakage coefficient, h1 = fîe / Vj , h2 = fie / V2 , Vj, V2 are the control volumes of the two chambers, respectively. fie is the effective bulk modulus of the system. The force balance equation of the system is expressed as: mxp = Pl Al - Pl 4 - Bc Xp - FL - Pf* (4) where m is the equivalent mass of the load, xp is the displacement of the cylinder rod, Bc is the coefficient of viscous damping, FL is the external load force, Ff is the Coulomb friction force. Define the system state variables as Eq. (5): [ X1, x2, X3, X4] _ [ Xp, pi, p2] (5) In order to make the system fall into the strict feedback form, the state variables are reconstructed as Eq. (6), where a = iA1 . [xPx2,x3]T =[x,xv,pi -ap2f (6) Considering the uncertainties and disturbance in the model, the entire system can be expressed in a state space form as Eq. (7): ■ - a- _ B _ FL_Fl d —2 — —3 —2 d^i —3 — f1—2 /2—3 + /3 —4 + f4Uà ++ d2 (7) y — — 1 / = h a + h2 Aa /2 = hCt + h2Cia f = hC + h2Cta f4 = h kq kx g + h2kq kx ^ (8) wheref ~f4 are shown in Eq. (8) and dx, d2 represent the lumped modelling error including unmodelled dynamics and external disturbance. It can be seen that the system is highly nonlinear because it suffers from the lumped modelling error and parametric uncertainties. The control task is summarized as follows: given the desired motion trajectory xd , the objective is to synthesize a control input of the PDV such that the output xj tracks xd as closely as possible. Meanwhile, The PRV is utilized to regulate the supply pressure ps in order to reduce the energy consumption. 2 ENERGY-SAVING STRATEGY For a fixed displacement pump, there always exists excess pressure and overflow loss. The VSPC can reduce the excess pressure loss of the system. However, the overflow loss is not considered in these studies. The load-sensing pump can adjust the flow and pressure per the demand. Thus, the overflow loss can be eliminated by employing a load-sensing pump. However, the pressure margin of the load-sensing pump, usually fixed approximately j4 bar to 30 bar across the valve, is not optimized in studies involving load-sensing pumps. Thus, if the VSPC could be applied to the load-sensing pump, the system efficiency would be significantly improved. 2.1 Configuration of the Load-Sensing Structure The load-sensing structure of the proposed system is shown in Fig. 2. The structure comprises the load-sensing pump, the PRV, and the throttle valve. If the pump pressure is larger than the sum of the preset pressure margin pm and feedback pressure pLs , the cylinder will be driven to reduce the angle of the swash plate 6 until the pressure is balanced on both sides and vice versa. The pressure margin pm is preset by the spring inside the load-sensing pump. However, this margin can be indirectly regulated by adjusting the feedback pressure pLs , which is controlled by the PRV. The function of the throttle valve is only to establish the pressure difference between the pump and the PRV. The power consumed in the throttle valve is neglected because the orifice of the throttle valve can be adjusted to a small value and the pressure difference across the valve is equal to pm when the system is stable. PC PRVThrottle Valve Load sensing pump Fig. 2. Schematic diagram of load sensing 2.2 Variable Supply Pressure Control For a certain demand flow, the smallest possible pressure drop will occur if the valve is fully opened. However, in that case, the PDV cannot be adjusted in a certain range to compensate for the tracking error. It can be concluded that if the opening of the PDV remains at a relatively high level during the forward and backward motion while the pump only provides the demand pressure, the pressure loss across the valve will be minimized. The VSPC is introduced as follows. For the forward motion (Xd > 0), the desired inlet pressure drop across the PDV Apj = ps -pj can be calculated as follows: A1 Xd = kq kxaUmax4| "Aft, Api = PAi2 xd2 2£q2ka2uL (9) (10) where Mmax is the maximum input voltage of PDV during the forward motion, a is the desired normalized input signal of PDV determined by the users/designers to indicate the importance of energy saving. The value of a can adjust the desired spool position of the PDV, and a higher value of a can improve the energy efficiency. The pressure drop between pump and valve can be obtained as: Ap2 = X d 2 (11) where X is the layer resistance coefficient, l is the pipe length, d is the pipe diameter. Because of uncertainties in the plant, the design of the desired pump pressure must allow for a margin of safety. Thus, op is added to the value of desired pump pressure [3]. From Eqs. (9), (10) and (11), the desired pump pressure, the indirect feedback pressure and the input signal of PRV can be written as: Psdi = Pi par- + ^P2 + aiPi' (12) Ik^a wmax d 2 PlS1 = = Psdl - Pm ^ Uvl = Psi1' Pm , (13) where krv is the PRV gain, urvl is the control input of the PRV, psd1 is the desired pump pressure in the forward motion, pLs1 is the indirect feedback pressure governed by the PRV in the forward motion. Because the supply pressure always exceeds the cracking pressure, the dynamic of the PRV can be simplified as Eq. (13) [3]. As with the case of forward motion, the desired pump pressure, and control voltage of the PRV when xd < 0 are expressed as: Psd2 = P2 + PA2f\ P2 + (14) 2kk a w„„ d 2 Pls2 = ^K = Psd2 - Pm ^ "rv2 = ^ ^ ■ (15) Remark 1: It should be noted that the pump pressure will remain as the preset pressure margin pm when the desired pump pressure is less than the pm. Furthermore, although the pump pressure is not zero when xd = 0 , the input signal of PDV varies slightly around zero. Consequently, the pump only provides a little flow mainly for compensating for the internal leakage. Therefore, the energy consumption, in this case, is also very small. e n , tanh(—)e2 + m ' e, ftX2 /2*3 f~hX4 + fhUi + ^2 -*3d) - e2 (-02x2-0l)-p,0t0i - p,0,0,. (28) The actual control is designed as: Ud = f ( f-X2 + f2X3 — f3X4 + X3d — k3e3 — J4 e A -S2 tanh(—)e3--- e2), (29) where k is a positive constant. The adaptation law is chosen as: (30) In case the parameter estimate di varies significantly, which may result in a very large input voltage, 0, is updated using the following projection type adaption law [16], Projs (• ) 0 if e i >6^ and • > 0 0 if ei < 6wini and • < 0 i = 1,2. (31) • otherwise Substituting the Eqs. (29) and (30) into Eq. (28) yields: V3 = -ke - k2e2 - k3e3 + \e2 - - 8X tanh(—)e2A2e3 - S2 tanh(-^)e3 < 0. (32) Remark2: Because the proposed control strategy is a set point strategy, it is necessary to verify the stability of the system. However, the stability of the internal dynamics of the system is difficult to ensure. A method in [3], which utilized a new state variable and zero dynamics to validate the stability, can also be used in this study. The extended state variable x5 and the dynamic of the pump pressure, which are deduced by Eqs. (12) and (14), respectively, are as follows X5 = hJp(PS - Pi) - h2)jpp(P 2 - Pt) X1 ^ 0 X5 = hjp(Pi - Pt) - Ps - P2) X1 < 0 , (33) P = p2 + 72 pA2 xv xv +x-Pi d 2 k2k2a2u2 q x max pA2 xp xp d2 k2k2a2u2 q x max . (34) Casel. Zero output: In this case, the output of the system should be kept at zero. This means that xd = xd = xd = xd = xl = xl = x = 'x[ = 0. Thus, the control input approaches zero in this case according to Eq. (29). Accordingly, the flows of the two chambers are also near zero. Neglecting the leakage, we can get P1 = P2 = 0 from Eq. (3). Thus, the chamber pressure will be regulated at constant values. Consequently, the pump pressure is also a constant value and ps = 0 according to Eqs. (12), (14), and (34). As a result, x5 will tend to be a constant value and x5 = 0. Case2. Constant output: In this case, xd = x ^ 0 , xd = xd =xd = xi = xi =x1 = 0 . Based on Eqs. (29) and (34), the control input and ps will approach zero again, and the rest of the analysis will be the same as Case1, which means that in a set point strategy, the internal dynamics of the system will be stable. 4 EXPERIMENTAL RESULTS The setup is presented in Fig. 3. The position of the cylinder is measured by a displacement sensor (LS 628C). The pressures in the two cylinder chambers and supply pressure are measured by pressure sensors (HDP702). A dSpace1104 data acquisition data board is used to acquire the feedback signals from sensors and to generate control signals. The variable pump is a Danfoss load-sensing pump. The parameters of the system are shown in Table 1. Fig. 4 depicts the harmonic reference tracking test for the proposed method by selecting a as 0.86. It can be observed that the actual trajectory follows the desired position well. The pump pressure and chamber pressures are shown in Fig. 5, in which the maximum pressure margin is 7.5 bar. It is less than the 2 preset pressure margin 14 bar in the pump. Moreover, with the increase in the flow, the pressure margin is boosted, and the decrease of the pressure margin is associated with decreases in flow. A higher pressure margin always appears at the middle stroke of the cylinder in both forward and backward motion, which could verify the effectiveness of the energy-saving method. overshoots due to the low-pressure difference and the chattering problem. As can be seen from Fig. 7, a significant tracking error of 3 mm occurs in the peaks of the reference signal. Moreover, the average tracking errors of the proposed method and the sliding mode controller are 0.75 mm and 0.9 mm, respectively. Hence, the proposed method has a better tracking Table 1. Parameters of the system Total leakage coefficient 3x10"11 Oil bulk modulus 1x109 Pa Piston/rod diameter 40/30 mm equivalent mass of the load 15 kg Oil density 890 kg/m3 Viscous damping 800 N/m kqk-x 8.8x10"7 0.005 1 0.2 02 0.05 ki 100 k2 200 k3 135 Fig. 3. Schematic of the equipment 3 6 9 Time (s) Fig. 4. Tracking performance The parameter estimates are shown in Fig. 6, and the tracking errors of three different methods are shown in Fig. 7. It can be observed that the proposed method exhibits a better tracking performance than PID control with a maximum tracking error of 1.2 mm. If sliding mode control is used to achieve the same level of tracking performance, high feedback gain must be employed, which may result in 6 9 Time (s) Fig. 5. Pump pressure and cylinder chamber pressures e ¡il 3i 210 -1-2-3 Time (s> Fig. 6. Estimation results Proposed Control Strategy Siliding Mode control PID 3 6 9 12 Time (s) Fig. 7. Tracking errors (a = 0.86) - Proposed control strategy - Sliding mode control 3 6 9 12 Time (s) Fig. 8. Tracking errors (a = 0.7) performance than the sliding mode control regarding the average error and maximum error. To further verify the tracking performance of the proposed method, another experiment was carried out by selecting the a as 0.7. As can be seen from Fig. 8, the proposed method demonstrates a better tracking performance compared with the sliding mode controller. It can also be found that although the tracking error of the proposed method is slightly smaller when a is 0.7, it is not obvious. Meanwhile, the energy-saving performance will degrade by choosing a smaller value of a. The suitable value of a is determined by trial-and-error and eventually chosen as 0.86 by taking both energy saving and position tracking performance into account. To evaluate the energy-saving performance of the proposed method, it is compared with a fixed displacement system. The system pressure of the fixed displacement system is assumed to be 50 bar, and the flow provided by the pump is assumed to be 16 l/min, which is slightly higher than the maximum demand flow. The energy-saving performance of the proposed system was also evaluated by comparing the energy efficiency with that of the fixed displacement system with VSPC, which is similar to the existing VSPC system. Neglecting the energy loss across the throttle valve, the supply energy of the three methods are shown in Fig. 9. The energy is calculated by PsQL , in which QL is the flow rate of the pump. It can be observed from Fig. 9 that the supply energy of a fixed displacement system is 20 kJ, whereas the supply energies are 14.8 kJ and 7.5 kJ in the fixed displacement system with VSPC and the proposed system, respectively. Thus, it can be concluded that the proposed method is capable of saving 62.5 % energy in comparison with a fixed displacement system and approximately 49 % energy in comparison with a fixed displacement system with VSPC. - Proposed system - Fixed displacement system with VSPC Fixed displacement system 6 9 Time (s) Fig. 9. Supply energy of the system To further verify the proposed method, multistep reference tests were conducted by selecting a as 0.82. The results are depicted by Figs. 10 to 12. It can be observed from Fig. 10 that the proposed method succeeded in realizing position tracking and the dynamic behaviour of the presented system is good. The pump pressure and chamber pressures are shown in Fig. 11. It can be observed that the maximum pressure margin is 10 bar and the pump pressure remains at 14 bar when the desired pump pressure is lower than the preset pressure margin. The supply energy during the whole motion cycle is shown in Fig. 12. The system pressure of the fixed displacement system is assumed to be 45 bar. It is shown in Fig. 12 that the supply energy of the fixed displacement system is 28 kJ. Compared with the fixed displacement system, the fixed displacement system with VSPC saved approximately 62 % energy, and the proposed system saved approximately 90 % energy. 0.16-, 0.140.120.100.080.060.040.02 -Reference — Actual V 1 1 \ I'l fl 1 1 3 6 9 Time (s) Fig. 10. Tracking performance 3 6 9 12 15 Time (s) Fig. 11. Pump pressure and cylinder chamber pressures - Proposed system Fixed displacement system with VSPC - Fixed displacement system 1) 6 9 Time (s) Fig. 12. Supply energy of the system 5 CONCLUSIONS A VSPC based load-sensing structure is presented in order to reduce the overflow loss and excess pressure loss across the PDV. Thus, the flow and pressure of the EHSS can both meet the control demand. Additionally, an adaptive backstepping sliding mode control is introduced for position tracking. 2) Compared with the fixed displacement system, the proposed method is capable of saving 62.5 % and 90 % of supply energy in harmonic reference tests and multi-step reference tests, respectively. The results also demonstrate that the presented method has a better energy-saving performance in comparison with [3] and [4] because the overflow loss can be reduced in this study. 3) The proposed method exhibits a good tracking capacity with a maximum tracking error of 1.2 mm in the harmonic reference tests. Furthermore, the tracking performance and dynamic behaviour for the multi-step reference tests are also good. This method could also be combined with the independent metering to save even more energy in mobile machinery and other applications because the load-sensing pump presented here is widely used in engineering machinery. 6 ACKNOWLEDGEMENTS The project is funded in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the 2016 annual general university graduate research and innovation program of Jiangsu Province, China (KYLX16_0525). We also give our great thanks to Keivan Baghestan, Amirkabir University of Technology, Tehran, Iran, for his valuable suggestions. 7 REFERENCES [1] Lu, X.C., Chen, Q.B., Zhang, Z.J. (2014). The electric vehicle routing optimizing algorithm and the charging stations' layout analysis in Beijing. International Journal of Simulation Modelling, no. 13, no. 1, p. 116-127, D0l:10.2507/ IJSIMM13(1)C04. [2] Casoli, P., Pompini, N., Ricco, L. (2015). 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Acta Polytechnica Hungarica, vol. 12, no. 3, p. 129-146, D0I:10.12700/APH.12.3.2015.3.8. Strojniški vestnik - Journal of Mechanical Engineering 62(2016)12, 717-729 © 2016 Journal of Mechanical Engineering. All rights reserved. D0l:10.5545/sv-jme.2016.3777 Original Scientific Paper Received for review: 2016-06-06 Received revised form: 2016-10-14 Accepted for publication: 2016-10-18 Primary Energy Factor of a District Cooling System Tjasa Duh Coz* - Andrej Kitanovski - Alojz Poredos University of Ljubljana, Faculty of Mechanical Engineering, Slovenia The primary energy efficiency for various energy-related processes can be calculated using the primary energy factor (PEF). In this paper, the PEFs of district cooling systems (PEFDC) for different types of cold production are derived. These concern cold production with an absorption chiller driven by different available sources and cold production with a compressor chiller driven by different types of engines and related energy sources. Based on the fundamental definition of the PEF, a mathematical model for calculating the PEFDC for different types of cold production was developed. The results in this study reveal that the PEFDC can be significantly improved in the case of combined cooling and power generation. The PEFDC in the case of combined cooling and power generation is lower than when cooling with electrically driven compressor chillers when the energy efficiency of the electricity generation in thermal power plant (qj is low or the PEF of the electricity (PEFe) is high. In cold production technologies where coal is used as the primary energy source more primary energy is consumed compared to other primary energy sources (i.e. natural gas, waste heat, etc.). Keywords: primary energy factor, combined generation, district cooling, chiller Highlights • Primary energy factors (PEFs) appear in many legislations and research reports. • PEF can be used to determine the primary energy consumption of cold production. • This work provides mathematical model for calculation of PEFs for different cooling technologies. • Moreover this work provides results of analysis of PEFs of district cooling systems. • The PEFs of district cooling systems can be used for the selection of the most primary energy efficient cold production technology. 0 INTRODUCTION In the past decade, the EU has been taking a more active role in the field of improving energy efficiency, reducing energy consumption and exploiting renewable energy sources. In order to define the actual primary energy efficiency of various energy-related processes, the primary energy factor (PEF) can be used as a tool. The PEF enables a comparison between the input primary energy to the system and the energy delivered to the consumer. Its evaluation involves the energy required for the extracting, processing, storing and transporting to a power plant, energy conversion, transmission, distribution and the losses associated with these processes. The primary energy in this particular case includes the energy contained in the raw fuels as well as other forms of energy received as the input to the energy-supply system. It covers both renewable and non-renewable energy sources and the definition here is in accordance with EN 153164-5 [1], which states that '... waste heat, surplus heat and regenerative heat sources are included with the appropriate primary energy factors.' A set of directives has been approved in order to reduce the energy consumption, increase the efficiency and exploit renewable energy sources. The PEF has been used as a significant metric in order to calculate the actual primary energy efficiency of different processes in several legislations, i.e., in Directive 2012/27/EU on energy efficiency [2], Directive 2010/31/EU on the energy performance of buildings [3] and Directive 2009/28/EC on the promotion of the use of energy from renewable sources [4]. The essential requirements from those directives appear in the relevant European standards in order to implement the calculation of the energy efficiency and the PEF. Standard EN 15203/15315:2006 [5] presents the different values of the PEF provided by the Swiss Federal Institute of Technology. In the standards EN 15316-4-5:2006 [1] and EN 15603:2008 [6] the different values of the PEFs for various types of electricity generation are recommended. All the standards listed above use fixed values of the PEFs that are commonly not updated. However, PEFs are variable, because they depend on the specific mix of primary energy sources and the efficiency of the processes of generation, storage and transportation. Beretta et al. [7] presented a method that provides a dynamic calculation of the PEF depending on the variation of time and geographical location. Laverge an Janssens [8] attempted to use empirical data to calculate the PEFs for a set of countries in a specific year. However, his study did not follow a complete and replicable methodology and it did not include the losses associated with generation, storage and transportation. Wilby et al. [9] claimed that fixed *Corr. Author's Address: University of Ljubljana, Faculty of Mechanical Engineering, Askerceva c. 6, Ljubljana, Slovenia, tjasa.coz@fs.uni-lj.si 717 values of PEFs are not capable of representing the evolution of the energy system. He proposed an application to calculate dynamic PEFs based on empirical data. Among the 14 countries that were included in the study, 9 countries had real PEFs of electricity below the European average of 2.5 (Finland 1.32, Norway 1.39, Denmark 1.7, etc.) and the rest of the countries had values above the European average (Poland 2.91, France 3.4, etc.). Schicktanz et al. [10], Fumo and Chamra [11] and Mago and Chamra [12] used the PEF to calculate the primary energy consumption and energy costs of a combined heating, cooling and power system (trigeneration). Different PEFs from different types of district heating and cooling systems are presented by Wirgentius [13]. The renewable part of the primary energy was excluded from the study. Dalla Rosa and Christensen [14] presented the primary energy performance of a network that was designed for low-temperature operation. The calculations hypothesized PEFs of 2.5 for electricity and 0.8 for district heating. Prandin [15] used the PEFs to calculate the exergy consumption of a space heating system. Zyczynska [16] explored the methodology for determining the PEF of a specific urban heating system. The methodology was based on real measurements. A PEF of 0.5 (heat from cogeneration) was obtained in this study. Jungbauer et al. [17] presented measurements of the PEF of a district cooling system in Barcelona (0.6), Copenhagen (0.93), Helsinki (0.18), Gothenburg (0.44) and Vienna (0.62). Riepl et al. [18] used PEFs to calculate the primary energy savings using solar thermal cooling and heating plants with absorption chillers compared to electric vapour-compressor chiller systems. The aim of this study is a development of a general mathematical model for the calculation of the PEFdc. This mathematical model can be used as a tool in a feasibility study of a new district cooling system in order to select the cooling technology with the lowest PEFDC. In this paper several different types of cold production are included in the calculation of the PEFdc. This study concerns cold production with an absorption chiller driven by the heat from different available sources as well as cold production with a compressor chiller driven by different types of engines and related energy sources. A study of PEFDC in such a wide range of district cooling technologies has not yet been found in the literature. 1 DEFINITION OF THE PEF OF A DISTRIC COOLING SYSTEM The primary energy efficiency of a district cooling system can be defined by evaluating the PEFDC, which is the ratio between the primary energy input QP and the cooling energy at the primary side of the substation QDC. The cooling energy QDC in the Eq. (1) presents the sum of the cooling energy of all consumers connected to the district cooling system. The basic definition of the PEF for a district cooling system can be shown using the following expression: PEFdc = QpiQd (1) In the case of a trigeneration system only part of the fuel input is used for the cold production. The rest of it is used for the production of heat and electricity. Therefore, in the case of a district cooling system related to a trigeneration plant, the expression for PEF in Eq. (1) can be rearranged as [19]: Z Qf ■ PEF F pefdc = - Z Qd • PEFd +Z Qdh ,, • PEFa _i__ Z QDC Jk (2) In the following text, the PEFDC for different types of cold production and different types of fuel input are determined. In this case the cooling-energy consumption of an absorption chiller is defined as: QDC ,abs = QH ■ COPabs '"HdN. (3) For the compressor chiller, the cooling-energy consumption is defined as: Qd ' COPcom 'nDN. (4) Fig. 1 illustrates the different types of cold production that are analyzed in this paper. Cold can be produced either by a compressor or by absorption chillers. Different types of absorption chillers can be used: a single-effect absorption chiller (SEAC) driven by hot water, a double-effect absorption chiller (DEAC) driven by steam and a direct-fired absorption chiller (DFAC) driven by natural gas. Waste heat (WH) from an industrial process can also be used to drive an absorption chiller. Compressor chillers are divided into two groups: compressor chillers driven by an electric motor (CC) and compressor chillers driven by an internal combustion engine (ICE). In this study, the primary energy consumption of the cooling towers is not included in the calculation of the PEFDC. The technical parameters of the chillers are presented in Table 2. el Fig. 1. The different types of cold production included in this study 1.1 Cold Production with an Absorption Chiller Driven by the Heat from a Boiler (CB) The heat from the combustion of fuel in a boiler drives the absorption chiller. A single- or double-effect absorption chiller can be used to produce cold. The primary energy consumption is: qp,cb = ' peff . (5) The PEF of a district cooling system for this particular case can be defined by using Eqs. (3) and (5) in Eq. (1): ( 1 A PEFn, 1 COPabs 'VON ncB PEFb (6) Coal and natural gas are considered as fossil fuels in this study. According to [1], the PEFcoa[ = 1.3, and for natural gas, the PEFNG = 1.1 (see also Table 1). 1.2 Cold Production with a Direct-Fired Absorption Chiller Driven by Natural Gas (DFACNG) A direct-fired absorption chiller is driven by the heat from the combustion of natural gas. According to Makita [20], the COP of a direct-fired absorption chiller is defined as: COP DFAC = QJQl (7) The primary energy consumption of a direct-fired absorption chiller is calculated as: qp,ng qlhv ' pefng ■ (8) Using Eqs. (1), (7) and (8), the PEF of a district cooling system can be defined as: ( 1 A PEFn, 1 COPDFAC '^DN pefm, (9) The PEFNG is given in Section 1.1 (see also Table 1). 1.3 Cold Production with an Absorption Chiller Driven by Waste Heat from an Industrial Process (WH) In the case of a district cooling system consisting of an absorption chiller driven by the waste heat from an industrial process, the primary energy consumption is calculated as follows: Q 'P ,WH QH ' PEFWH. (10) The heat delivered to the absorption chiller can be effluent, hot water or steam. Using Eqs. (1), (3) and (10), the PEF of the waste heat from the industrial process is: ( 1 A PEFn, 1 COP„b ■Von PEF,,r (11) The waste heat includes the heat from municipal incineration and industrial surplus heat. The PEF of the waste heat is defined according to Refs. [21] and [22] as PEFwh=0.05 (see also Table 1). Using waste heat to drive an absorption chiller avoids the use of fossil fuels and make use of the energy flows that otherwise would be lost. Hence, the value of the PEF is almost 0. When calculating the PEFDC that uses waste heat to drive an absorption chiller, it is necessary to take into account that heat with different parameters (see Table 2) is used. 1.4 Cold Production with a Compressor Chiller Driven by the Electricity from the Grid (CCmix) Different energy sources can be used to generate electricity. This is then further used to drive the motor of the compressor chiller. The primary energy consumption of an electrically driven compressor chiller is: Qp = We,. PEFeI,mic. (12) Using Eqs. (4) and (12), Eq. (1) can be rewritten as: PEFn, 1 COP ■ PEF, (13) com l DN y The PEF of the electricity from the grid is defined according to Ref. [14] as PEFe,mix=2.5. This value represents the European average. Each country has the right to set a different value for its PEFe, mix, providing its choice is adequately justified (see also Section 0). 1.5 Cold Production with a Compressor Chiller Driven by the Electricity Generated in a Thermal Power Plant (CCTPP) produced in a thermal power plant) is calculated using Eqs. (1), (4) and (14): ( 1 A PEF, 1 COPcom -VdN nd PEF (15) The PEFf are given in Section 1.1 (see also Table 1). 1.6 Cold Production with a Compressor Chiller Driven by an Internal Combustion Engine (CC,ce) This kind of system consists of a compressor chiller that is driven by the mechanical energy produced with an internal combustion engine (ICE). According to Yingjian [23], the COP of an engine-driven compressor chiller is defined as: COP rCE com,ICE = QcWm (16) The primary energy consumption of an engine-driven compressor chiller is: QP ■ PEFf . (17) Using Eq. (4), (16) and (17), Eq. (1) can be rewritten as: ( , A PEFn, 1 COP„. ' '^DN PEF (18) The ICE can be driven by diesel, petrol, kerosene or natural gas; the values for the PEF of the fuel are defined according to [1] and [24] (see also Table 1). Since the electricity from thermal power plants (TPP) represents only a part of the electricity mix, the electricity produced in the thermal power plant is discussed separately. In this subsection a compressor chiller driven by the electricity from a thermal power plant (TPP) is studied. Two different scenarios are discussed: a compressor chiller driven by the electricity generated in a generator, connected to a steam turbine (combustion of coal), and a compressor chiller driven by electricity, where the generator is connected to a combined cycle of gas and steam turbine (combustion of natural gas). The primary energy consumption of the electrically driven compressor chiller is calculated as: Q =-e-. PEF TPP 1 -^-i F Vel (14) The PEF of a district cooling system with an electrically driven compressor chiller (electricity 1.7 Cold Production in Combined Cooling and Power Generation (CCP) A trigeneration system (combined cooling, heating and power generation) is a combination of a cogeneration plant and an absorption chiller (see Fig. 1). In such a system where the cooling energy is produced with absorption chillers driven by heat, the steam should be extracted from an extraction-condensing turbine using the parameters that are required for the chiller's normal operation (see the parameters in Table 2). Consequently, the generation of electrical energy is reduced, and more primary energy is consumed in order to produce the same amount of electrical energy as in the case of a condensing turbine regime. In this subchapter the combined cooling and power generation is considered. It is assumed that all the available heat from a thermal power plant is used to produce cold. Therefore, the district heat consumption Qdh in Eq. (2) is equal to 0. To calculate the PEFDC based on combined cooling and power generation (CCP) the Eq. (2) can be rearranged to: PEFn, MQ, ■ PEF, cop„ 1 ■Vdn (n (19) where AQP presents the difference between the energy consumption of fuel, when both, electricity and cold are produced (i.e. CCP) and when only electrical energy is produced in thermal power plant (TPP) (see the Eq. (20)). In both cases the amount of produced electrical energy remains the same (Wei = Wel,TTP = Wel,ccP). ( , , \ AQf = Qf ,CCP - Qf 1 J_ nd (20) The PEF of a district cooling system where all the available heat from plant is used in an absorption chiller to produce the cooling energy is calculated using Eqs. (3), (19) and (20): PEFn, where = PEFF '(I - * ) _ C0Pabs nDN ' (c 1 x=nc il n (21) (22) is the ratio between the energy efficiency of the electricity generation in a combined cooling and power generation system nCCP,el (heat and power production; heat is extracted from an extraction-condensing turbine) and the energy efficiency of the electricity generation in a thermal power plant when operation is related only to the production of electricity nel (power production; condensing turbine). The total energy efficiency of a cogeneration system where all the extracted heat is used for cold production is nCCP,total. Only natural gas and coal are considered as the fuels in this study. The PEFf are given in Section 1.1. 2 PARAMETERS USED IN THIS ANALYSIS Based on the equations from Section 1 a mathematical model was developed. The parameters used in this model are divided into two categories: • Primary energy factors (PEFDC, PEFet PEFf (PEFcoal, PEFng, PEFwh)). • Technical parameters (ncB , Vdn , nel , nccp.ei , nCCP, totah COPabs, COPDFAC, COpCom, COpComjCE). The PEFs of the fuels considered in this study are shown in Table 1. Table 1. Primary energy factors of fuels Fuel PEF Ref. Coal 1.3 [1] Natural gas 1.1 [1] OH 1.1 [1] Heat from combined gas and steam turbine 0.5 [25] Heat from steam turbine 0.8 [14] and [25] Waste heat from industrial process 0.05 [21] and [22] Electricity (EU average) 2.5 [14] Diesel, petrol, kerosene 1.19 [24] Table 2 shows the technical parameters of the chillers considered in this study. The calculations for the PEFdc were made for a single-effect absorption chiller driven by hot water, a double-effect absorption chiller driven by steam, and a direct-fired absorption chiller driven by natural gas or the waste heat from an industrial process. The electrically driven and engine-driven compressor chillers were also included in this study. In the literature the COPs of different types of chillers were presented at given conditions: for gas absorption and engine-driven compressor chiller the chilled water temperature was 7 °C. The cooling water inlet temperature was 32 °C for DFAC and 30 °C for ICE. For all other types of chillers the chilled water temperature was 6 °C and cooling water inlet temperature 32 °C. Table 2. Data for the selected chillers Chiller Cooling power [kW] Chilled water temperature [°C] Cooled water inlet temperature [°C] Driving energy COP Ref. Steam absorption (DEAC) 2000 6 32 8 bar steam COP = = Qc / Qh = 1.39 [26] Hot water absorption (SEAC) 2000 6 32 98 °C hot water COP ■- = Qc / Qh = 0.79 [26] Gas absorption (DFAC) 282 to 2462 7 32 Natural gas (LHV=34 MJ/Sm3) COP = Qc / Qlhv = 1.42 [20] Compressor chiller 2000 6 32 Electricity COP = Qc / Wel - = 6.6 [26] and [27] Engine-driven compressor chiller (ICE) 140 7 30 Fossil fuels COP = Qc / =2.7 [24] and [28] The following energy efficiencies were used in this study [29] to [34]: the total energy efficiency of a combined cooling and power generation system (Vccp.totai), the boiler efficiency (nCs) and the energy efficiency of a district network (nDN). For the purpose of the study they are all assumed to be 0.9. Energy efficiency of the network considers heat gains which affect the primary energy consumption; therefore, more primary energy has to be used to provide the required cooling demand. 3 RESULTS AND DISCUSSIONS Based on the parametric analysis, introduced in Section 1, this section provides the values for the PEF of a district cooling system (PEFDC) for different types of cold production as a function of: • the COP of absorption or compressor chillers (COPabs, COPcom), • the PEF of the electricity (PEFel), • the energy efficiency of the electricity generation when operation is related only to the production of electricity (nel). In this study the ratios x in Eq. (22) are set as 0.95 when single effect absorption chiller is used for cold production and 0.92 or 0.90 when double effect absorption chiller is used. The values of the PEF for the electricity mix considered in this study are 2.5 [17] and 1.3 [9]. The PEFDC in Sections 3.1 and 3.2 were calculated for a constant energy efficiency of the electricity generation when operation is related only to the production of electricity: nel = 0.37 for a steam turbine and nel = 0.55 for a combined cycle of gas and steam turbine. The COP is highly dependent on operating conditions. The operating conditions are considered in this study indirectly in Sections 3.1 and 3.2, where the PEFDC as a function of COPs is presented. 3.1 PEFdc as a Function of the COP for the Absorption Chiller The PEF of a district cooling system (PEFDC) as a function of the COP of an absorption chiller (COPabs) is presented in Fig. 2. In this case, different types of cooling with an absorption chiller were evaluated: • cooling with an absorption chiller driven by heat from a boiler, where coal (Cscoal) and natural gas (CBng) are used as the fuel, • cooling with a direct-fired absorption chiller where natural gas (DFACNG) is used as the fuel, • cooling with an absorption chiller driven by waste heat from an industrial process, • cooling with combined cooling and power ge^tron, where c°al (CCpcoal,x=o.95nel=0.37) and natural gas (CCPNG x=0 95 0 55 ) are used as the fuel. ' ' '" ' In this Section the ratio x remains the same (x = 0.95) for all the values of the COPci>s. In the following subsections the different values of the ratio x, as a consequence of the different parameters of the heat extracted from the extraction-condensing turbine, are taken into account. As can be seen from Fig. 2, the PEFDC decreases with an increase of the COPabs (since less heat is required to drive the absorption chiller). The highest value of the PEFDC is achieved when the absorption chiller is driven by the heat from a boiler and when coal is used as the fuel (CBcoal). For this particular case the PEFDC=2.53 for the absorption chiller with the COP = 0.6 and the PEFDC = 1.09 for the absorption chiller with the COP = 1.4. Fig. 2. Primary energy factor of a district cooling system as a function of the COP for an absorption chiller The PEFdc can certainly be improved in the case of combined cooling and power generation (CCP - a CHP plant where all amount of heat is used to drive absorption chillers). For instance, when coal (i.e. case CCPcoal) is used as the primary energy source in such a plant, the PEFDC = 0.22 (for the COP=0.6) and the PEFdc = 0.09 (for the COP = 1.4). When natural gas (i.e. case CCPNG) is considered as the primary energy source, the PEFDC=0.27 (for the COP = 0.6) and to PEFdc = 0.12 (for the COP=1.4). The lowest value of PEFdc is achieved when the absorption chiller is driven by waste heat from the industrial process. 3.2 PEFdq as a Function of the COP for the Electrically Driven Compressor Chiller The PEFdc as a function of the COP for an electrically driven compressor chiller (COPcom) is shown in Fig. 3. In this case different types of cooling with a compressor chiller were evaluated: • cooling with a compressor chiller driven by electricity mix from the grid (CCmix), • cooling with a compressor chiller driven by electricity generated in a thermal power plant, where coal ( CCTPPcan=0.37 and cctppcoaln=0.45 ) and natural gas are used as the fuel ( CCTPP,NG,nel =0.55 and CCTPP,NGn =0.60 ). From the results in Fig. 3 it is clear that the lowest values of the PEFDC are achieved when a compressor chiller driven by electricity mix from the grid (PEFei = 1.3) is used. For this particular case PEFdc = 0.36 (for the COPcom = 4) and PEFDC = 0.18 (for the COPcom = 8). In the case when the compressor chiller is driven by electricity from a thermal power plant (combined cycle of gas and steam turbine; natural gas is used as the fuel), PEFDC=0.56 (for the COPcom = 4) and PEFDC = 0.28 (for the COPcom = 8) when nei=0-55. When nei=0.60, the PEFDC for this case decrease to PEFDC=0.51 (for the COPcom=4) and PEFdc = 0.25 (for the COPcom = 8). The highest values of PEFDC are achieved when the cold is produced by a compressor chiller driven by electricity generated in a thermal power plant with nel = 0.37 where coal is used as the primary energy source ( CCTPP,coaltfel =0.37 ). 3.3 PEFdc as a Function of the PEF for Electricity Fig. 4 shows the PEFDC depending on the PEF of electricity (PEFel) for the typical COPs for the absorption and compressor chillers given in Table 2. Different types of cold production were considered in this analysis: • the cold production by an electrically driven compressor chiller (CCmix); the PEFelmix ranges from 1.3 to 3.5, • the cold production by an engine-driven compressor chiller (CCICE), • the cold production by single- and double-effect absorption chillers; absorption chillers driven by the heat from a steam turbine; (CCPSEAC,coal, CCPDEAC,coal ); the net of a steam turbine ranges from 0.32 to 0.45 and consequently the PEFet of a steam turbine ranges from 2.9 to 4, • the cold production by single- and double-effect absorption chillers driven by the heat from a combined cycle of gas and steam turbine (CCPseac,ng, CCPdeac,ng); the nei ranges from 0.35 to 0.60 and consequently the PEFet of a gas and steam turbine ranges from 1.8 to 3.1. From the results in Fig. 4 it is clear that the PEFDC system decreases when increasing the PEFe of the thermal power plant in the case when absorption chillers are used to produce the cold. The PEFe of Fig. 3. Primary energy factor of a district cooling system as function of the COP for an electrically driven compressor chiller Fig. 4. Primary energy factor of a district cooling system as a function of the primary energy factors of electricity for different chillers the thermal power plant is inversely proportional to the energy efficiency of the electricity generation (PEFel = PEFf/ rjel); therefore, by decreasing the nei , the PEFdc decreases. In the case of electrically driven compressor chiller the PEFDC increases when increasing the PEFeh The PEFd does not affect the PEFDC when an engine-driven compressor chiller (CCICE) is used (because this particular compressor chiller is directly driven by mechanical energy, i.e., no electricity is used). In this particular case the PEFDC can be considered as constant (PEFDC,ICE=0.49). Therefore, when the PEFei > 2.9, the primary energy consumption is lower in the case of an engine-driven compressor chiller, compared to an electrically driven compressor chiller (pEFc^e < PEFCC >m&). The PEFDC of the electrically driven compressor chiller (CCmix) increases from PEFDC=0.22 (at PEFel = 1.3) to PEFDC=0.59 (at PEFel = 3.5). The lowest value for the PEFDC is achieved when a double-effect absorption chiller (x=0.92), driven by the heat from a combined cycle of gas and steam turbine, is used (CCPDEAC,NGx=092). For this example PEFDC = 0.24 (at nei = 0.6 and PEFel = 1.8) and PEFDC = 0.13 (at nei=0.35 and PEFel = 3.1). If ratio x for double effect absorption chiller is lower (x = 0.9), the PEFDC increases and is even higher compared to PEFDC when single effect absorption chiller is used. The energy efficiency of the electricity generation using the steam turbine, when operation is related only to the production of electricity, ranges from 0.32 to 0.45. The lower the nel, the lower is the PEFDC. For this particular case the lowest PEFDC=0.18 is achieved at net=0.35 when double effect absorption chiller (x=0.92) is used. 3.4 PEFdc as a Function of the Energy Efficiency of Electricity Generation in a Thermal Power Plant The aim of this subsection is to provide information about the PEFDC as a function of the energy efficiency of electricity generation in a thermal power plant, when operation is related only to the production of electricity (nel). In Fig. 5a, the condensing steam turbine (coal is used as the primary energy source) is illustrated when a compressor chiller is driven by the electricity from the thermal power plant, and an extraction-condensing steam turbine is illustrated when absorption chillers are used. In Fig. 5b the combined cycle of gas and steam turbine is taken into account (natural gas is used as the primary energy source). As is clear from both examples in Fig. 5, the PEFDC is the lowest when a double-effect absorption chiller (CCPDEAC,x=0.92) is used to produce the cold. The PEFDC, with a compressor chiller driven by electricity from the grid (CCmix,), does not depend on the energy efficiency of the thermal power plant (nel). In this particular case, it remains constant (PEFDC = 0.42 at PEFel=2.5 and PEFDC = 0.22 at PEFel = 1.3). By increasing the value of the nel the PEFDC decreases when a compressor chiller driven by electricity from a thermal power plant (CCTPP) is used. From the results in Fig. 5a, the PEFDC with a single-effect absorption chiller (CCPSEAC,coal,x=0.95) and double-effect absorption chillers (CCPDEAC,coal,x=0.92 and CCPDEAC,coal,x=0.90) are lower, compared to electrically driven compressor chillers (CCmix and CCTPP), for any value of r)ei at given ratios x. Analysing the results from Fig. 5b, the PEFDC with a compressor chiller driven by electricity from Fig. 5. Primary energy factors for a district cooling system as a function of the energy efficiency of the electricity generation in a thermal power plant: a) steam turbine (coal), b) combined cycle of gas and steam turbine (natural gas) a thermal power plant is lower, compared with the one driven by the electricity mix (PEFel=2.5) when nei> 0.44. In the case of cold production with a single-effect absorption chiller (CCPSEAC,NG,x=0.95), the PEFdc is lower compared to electrically driven compressor chiller (PEFel=1.3) until nei> 0.57. Using the double-effect absorption chiller with x=0.92, the PEFdc are lower compared to any electrically driven compressor chiller for any value of neh When double effect absorption chiller with x=0.90 is used, the PEFdc is lower compared to the compressor chiller driven by electricity from the grid (PEFel = 1.3) when nel < 0.55. 4 CONCLUSIONS In this paper an analysis of the primary energy factors of district cooling systems (PEFDC) for different types of cold production is presented. Several different types of chillers were included in the study: a single-effect absorption chiller, a double-effect absorption chiller, a direct-fired absorption chiller and a compressor chiller driven by electrical energy or by mechanical energy from an internal combustion engine. The PEFs of the different fuels were taken from earlier studies. The results of the study reveal that: • The most primary energy of all the cases discussed in this study is consumed for cold production with an absorption chiller driven by the heat from a boiler (see Fig. 2). • Cold production with an engine-driven compressor chiller (ICE) compared to an electrically driven compressor chiller (CCmix) is rational only if the PEFel > 2.9 (see Fig. 4). • Primary energy consumption can be reduced by using heat from CHP plant to drive absorption chillers (heat and electricity are produced in a CHP plant; all of the heat is used for the cold production). The lower the energy efficiency of electricity generation in a thermal power plant (nel), the lower is the PEFDC (see Fig. 5). • If the energy efficiency of electricity generation in a thermal power plant with a combined cycle of gas and steam turbine is higher than 0.44, the PEFdc is lower for a compressor chiller driven by electricity from a thermal power plant (CCTPP,NG) , compared to a compressor chiller driven by electricity from the grid with PEFel = 2.5 (see Fig. 4). The PEFdc of a thermal power plant with a combined cycle of gas and steam turbine achieve its lowest value when nel=0.6 (PEFDC = 0.31). • The heat extracted from the turbine affects the energy efficiency of electricity generation in a CHP plant. When a double-effect absorption chiller is used to produce cold, the energy efficiency of the electricity generation is lower compared to the energy efficiency of electricity generation when the heat to drive a single-effect absorption chiller is extracted. The ratio x, between the energy efficiency of electricity generation in a CHP plant (the heat is extracted from the extraction-condensing turbine) and the energy efficiency of electricity generation in a thermal power plant (condensing turbine) has a significant impact on the PEFDC (see Fig. 5). • The comparison between the primary energy consumption of different cooling technologies and the cooling with electrically driven compressor chiller when PEFel=2.5 is presented in Appendix A. The general mathematical model developed in this study can be used as a tool for selecting the most primary energy efficient type of cooling technology in a feasibility study of a new district cooling system implementation. In the future work this mathematical model has to be improved by considering the production of the electricity, heat and cold at the same time (trigeneration system). A very complex general mathematical model for the calculation of the PEFdc will have to take into account the ratio between the heat used for heating and the heat used for cold production. Moreover, it will consider the increase of the consumption of the primary energy as a consequence of heat extraction from the turbine and lastly, the primary energy consumption as a consequence of different parameters of the extracted steam has to be taken into the consideration. 5 NOMENCLATURE COP coefficient of performance, [-] PEF primary energy factor, [-] Q energy, [kWh] W work, [kWh] n energy efficiency, [-] Abbreviations abs absorption chiller coal coal com compressor chiller el electricity G generator H heat F fuel me mechanical energy mix electricity mix P primary energy trigen trigeneration 6 REFERENCES [1] Standard EN 15316-4-5:2006. 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The primary energy input of different cooling technologies compared to the primary energy input when cooling with electrically driven compressor chillers (PEFei=2.5) Table A1. PEFDC for different types of cooling technologies Type of cooling technology General Eq. for PEFDCi CB PEFn, 1 COPabs -VdN nCB PEF DFACng PEFd DC,NG I rnp „I ^ NG DFAC IDN y ■ PEF„, WH PEF, DCWH~lcopabs n™ ■ PEFW. PEF, DC PEF = I DC ,CB