Computational Intelligence Based Tehnique for Load Shedding Scheme

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<p>COMPUTATIONAL INTELLIGENCE BASED TEHNIQUE FOR LOAD SHEDDING SCHEME</p> <p>LUKMAN HAKIM BIN HAMRON</p> <p>FACULTY OF ELECTRICAL ENGINEERINGUNIVERSITI TEKNOLOGI MARAMALAYSIA</p> <p>COMPUTATIONAL INTELLIGENCE BASED TECHNIQUE FOR LOAD SHEDDING SCHEME</p> <p> Project report is presented in partial fulfillment for the award of the Bachelor of Electrical Engineering (Hons) Universiti Teknologi MARA (UiTM)</p> <p>LUKMAN HAKIM BIN HAMRONFaculty of Electrical EngineeringUNIVERSITI TEKNOLOGI MARA40450 SHAH ALAM, SELANGOR</p> <p> A report submitted to Faculty of Electrical Engineering, Universiti Teknologi MARA in partial fulfillment of the requirement for Bachelor of Electrical Engineering (Hons).</p> <p>This thesis is approved by:</p> <p>.Associate Professor Dr. Ismail MusirinProject supervisorFaculty of Electrical EngineeringUniversiti Teknologi MARA (UiTM)40450 Shah AlamSelangor.Date:..</p> <p>DECLARATION</p> <p>It is hereby declared that all materials in this thesis are the result of my own work and all the materials that are not the result of my own work have been clearly acknowledged. Although, certain result on this thesis is effort from other dispute.</p> <p>ACKNOWLEGMENT</p> <p>First and foremost, all praise to Allah S.W.T. The Most Gracious and Most Merciful who had given me the strength, ability and patient upon completing this final year project.</p> <p>I wish to conveymy deepest gratitude and appreciation to my supervisor, Assoc. Prof. Dr. Ismail Musirin for his guidance, concern, valuable time, effort, constant encouragement and patience in supervising this project from the start until the completion if this thesis.</p> <p>I also wish to take this opportunity to express my gratitude to my family especially to my mother and my father for supporting me along way my journey in this field. They have encourage me throughout my education , and I will always be grateful for their sacrifice, generosity and love. May Allah S.W.T. bless them all. </p> <p>Not forget to my friends and anyone who directly or indirectly giving their support and contribution to finished this project. May Almighty Allah bless and reward them for their generosity. Thank you very much.</p> <p>ABSTRACT</p> <p>Losses in generation and overloading effect are two phenomena that may occur due to progressing demand at the load side. This may lead to system instability in forms of voltage and frequency. In order to avoid this problem, the under voltage load shedding scheme can be performed to shed some amount of load before the disturbance occur. This paper presents computational intelligence technique for load shedding. The study involves the development of fuzzy rules in order to make decision on load shedding. This method functions will determine the amount of load that needs to be shed depending on the measured minimum voltage of the system. The result of this paper will show the performance of under voltage load shedding scheme in determining power system stability by shedding some amount of the load demand. The technique has been validated on the IEEE 30-bus system.</p> <p>Index Termsvoltage collapse, system stability, fuzzy logic, under voltage load shedding</p> <p>TABLE OF CONTENTS</p> <p>CHAPTERDESCRIPTIONPAGE</p> <p>DECLARATIONi</p> <p>ACKNOWLEDGEMENTii</p> <p>ABSTRACTiii</p> <p>TABLE OF CONTENTSiv</p> <p>LIST OF FIGURESvi</p> <p>LIST OF TABLESvii</p> <p>LIST OF ABBREVIATIONSviii</p> <p>1.0INTRODUCTION1</p> <p>1.1 INTRODUCTION1</p> <p>1.2 PROBLEM STATEMENT3</p> <p>1.3 OBJECTIVE3</p> <p>1.4 SCOPE OF THE PROJECT1.5 RESEARCH FRAMEWORK1.6 OVERVIEW OF THE REPORT456</p> <p>2.0LITERATURE REVIEW5</p> <p>2.1 ECONOMIC DISPATCH (ED)5</p> <p>2.2 DYNAMIC ECONOMIC DISPATCH(DED)6</p> <p> 2.2.1 Ramp Rate Constraint8</p> <p>2.3 PARTICLE SWARM OPTIMIZATION (PSO)2.4 METHOD TO SOLVE DED910</p> <p>3.0METHODOLOGY15</p> <p>3.1 INTRODUCTION</p> <p>15</p> <p>3.2 DYNAMIC ECONOMIC DISPATCH (DED) FORMULATION 15</p> <p> 3.2.1 Objective Function15</p> <p> 3.2.2 Equality Constraint 16</p> <p> 3.2.3 Inequality Constraint 17</p> <p> 3.2.4 Dynamic Constraint17</p> <p> 3.2.5 Fitness Function18</p> <p>3.3 PARTICLE SWARM OPTIMIZATION (PSO)19</p> <p> 3.3.1 Basic PSO Algorithm19</p> <p> 3.3.2 Particles Velocity Update20</p> <p> 3.3.3 Constriction Factor Approach (CFA)20</p> <p> 3.3.4 Particles Position Update21</p> <p> 3.3.5 Representation of Particles Position21</p> <p>3.4 DED BASED ON PSO TECHNIQUE23</p> <p>4.0RESULTS AND DISCUSSION26</p> <p>4.1 DATA FOR IEEE 26-BUS TEST SYSTEM26</p> <p>4.2 PSO PARAMETERS SETTING28</p> <p>4.3 SIMULATION RESULTS FOR SOLUTION OF DED BASED ON PSO29</p> <p>4.4 ANALYSIS OF PSO METHOD ON DED SOLUTION32</p> <p>5.0CONCLUSION36</p> <p>6.0RECOMMENDATIONS FOR FUTURE WORKS37</p> <p>REFERENCES38</p> <p>APPENDICES43</p> <p>LIST OF FIGURES</p> <p>FIGURETITLEPAGE</p> <p>2.1Single line diagram of transmission line6</p> <p>3.1Matrix representation of particles position22</p> <p>3.2Modification of gBest according to generator constraints22</p> <p>3.3Flow chart for DED based on PSO process25</p> <p>4.1Variation of Cost with Power Demand Curve for 6 units system30</p> <p>4.2Variation of Power loss with the Load Demand for 6 units system30</p> <p>4.3Graph of Fuel Cost against Load Demand for comparison between PSO and Newton Raphson method33</p> <p>4.4Convergence Characteristics of PSO Method for 6 units system34</p> <p>LIST OF TABLES</p> <p>TABLETITLEPAGE</p> <p>4.1Generating Unit Capacity and Coefficients for IEEE 26-bus system26</p> <p>4.2Initial output power and Ramp Rate limits for IEEE 26-bus system27</p> <p>4.3Load Demand for IEEE 26-bus system of 24 hours27</p> <p>4.4Transmission loss Coefficients for IEEE 26-bus system28</p> <p>4.5PSO parameters28</p> <p>4.6Optimal MW Generation for each unit, Transmission loss and Fuel Cost of 24 hours29</p> <p>4.7Comparison of PSO and Newton Raphson Result32</p> <p>4.8Result for the Variation Number of Particles35</p> <p>LIST OF ABBREVIATIONS</p> <p>ED-Economic DispatchDED-Dynamic Economic DispatchPSO-Particle Swarm OptimizationSED-Static Economic DispatchAI-Artificial IntelligentFACTS-Flexible Alternative Current Transmission SystemsDP-Dynamic programmingGA-Genetic AlgorithmSA-Simulated AnnealingEP-Evolutionary ProgrammingLP-Linear ProgrammingNLP-Non-Linear ProgrammingQP-Quadratic ProgrammingDE-Differential EvolutionANN-Artificial Neural NetworkHNN-Hopfield Neural NetworkCFA-Constriction Factor ApproachIEEE-Institute of Electrical and Electronics Engineers</p> <p>6</p> <p>CHAPTER 1.0</p> <p>INTRODUCTION</p> <p>1.1 BACKGROUND OF THE STUDY</p> <p>In power system operation, the balance between load demand and the available generation is important to make sure the stability of the system is in good condition [1]. Nowadays, there are many situation occur where the demand load have reached the limit of an available generation in certain place. When this condition occurs, there will be same situation as in 2005 where there was power outage in Malaysia where many states of Malaysias northern peninsular, including Perlis, Perak, Penang and Kedah due to the occurred fault. This situation happened due to the load demand used by the user has exceed the limit that the available generation can support. From this situation a load shedding scheme is initiated to avoid the system from collapsed [2]. There are many factories have take improvement step to prevent this phenomena happening again by developing a new alternative extensively to ensure the power system network operates in the normal steady state condition conveniently [3].</p> <p>A system enters a state of voltage instability when a disturbance, increase in load demand, or change in system condition causes a progressive and uncontrollable drop in voltage [4]. The main factor for instability is the inability of the power system to meet the demand of increased reactive power. Literally, it will cause the system collapse.</p> <p>There are several studies that indicate about voltage stability of the power system. One of these studies is about estimating the voltage stability of power system [5]. This study is based on the fast calculation of indicators of risk of voltage instability has been developed. These indicators can detect on-line voltage instability and signal the tendency towards a critical situation.</p> <p>Several methods have been developed to prevent the voltage from collapse. In this paper load shedding is applied to the selected bus so the voltage minimum will increase and the system become stable. This technique is proposed to make sure the system in a balanced condition. In [6], there are several methods to perform the load shedding technique such as under-voltage load shedding and under-frequency load shedding. The best way to perform load shedding scheme in a system is by minimizing the amount of load to be shed [7] for voltage collapse prevention. In [7], the paper study about the practical approach to perform the load shedding scheme.</p> <p>In order to perform the developed technique, a fuzzy logic algorithm was proposed. This algorithm provides solution as decision making to determine which load bus that need to be shed and how much load will be shed to make sure the system recover to the normal operation. Fuzzy logic was a useful algorithm where it can be used in wide area of study. In [8], fuzzy logic was used to solve the unit commitment problem. While in [9], fuzzy load shedding based algorithm is performed by using voltage stability indicator for averting voltage collapse. In this paper, fuzzy logic is performed by monitoring the minimum voltage by running the load flow. Then under voltage load shedding will be perform to get the system back to normal operation. The variable is selected from the load flow results. </p> <p>This paper presents computational intelligence based technique for load shedding scheme. The study involves the development of fuzzy rules in order to make decision on load shedding. Results from the experiment indicated that the proposed technique is successful to solve the load shedding problems. The load levels increase are divided into several different loading factors. The fuzzy technique is applied to each case to select load bus to be shed and to calculate the amount load to be shed to prevent voltage instability.</p> <p>1.2 PROBLEM STATEMENT</p> <p>Everyday people are using equipment continuously and the load demand for each distribution network is increasing with the increasing of electric usage among the user. Each generation that was established in Malaysia is enough to support the load demand in certain area depending on the load usage. There are some cases where the load demand is higher than the generation level. This will cause voltage collapse in the area. For example in 1995, blackout situations happen in Malaysia due to high load usage. The reason why this situation happened is because of the hot weather at that time. The same situation occurred in 2005 where the biggest blackout happened in Malaysia where there is no electricity due to the fault of the main cable transmission line grid. </p> <p>As the usage of equipment is increasing, the load demand will also increase. This condition will burden the generation to support the load demand. A generation has their limit to support the load demand in each area. When the consumer load demand has gone beyond the limit of available generation, it may lead to blackout. When this situation happens, it will cause problem to all consumer. This reason becomes the why a new method is needed to overcome this problem.</p> <p>1.3 OBJECTIVE</p> <p>i. To develop load shedding scheme in power systemii. To identify the Selected bus for load shedding and amount of load demand that should be shed for stable power system operationiii. To improve the power balance in power system operation by using computational intelligence</p> <p>1.4 SCOPE OF THE PROJECT</p> <p>The scope of this project is to analyze the balance between the load demand and the available generation. The data will be taken from legal resource as the first step of this project. Later, it will be analyzed to match with the load shedding technique. This technique is used to develop an algorithm as the solution for solving the load shedding problem. A selected load bus will be chosen for shedding based on the output of the develop algorithm.The under voltage load shedding scheme is employed in order to determine which load and amount of load that need to be shed. The voltage magnitude, active power and reactive power at load bus will be assigned as the input variable to fuzzy logic system. This fuzzy system will be implemented using MATLAB software. The proposed method gives satisfactory results in term of blackouts prevention and minimum voltage improvement. Moreover, this project will show the performance of fuzzy logic algorithm to be effective and useful in problem concerning the load shedding. The results of this method will be used to decide which of the load is the most suitable to be removed for maintaining the stability of the system.Flow chart in Figure 1 below summarizes the involved process:</p> <p>Determine the shedding load to balance the systemDevelop the fuzzy logic algorithm in matlabInitialize the load shedding schemePreparing the system dataFigure 1: Scope of project</p> <p>1.5 RESEARCH FRAMEWORK</p> <p>DEVELOPMENT OF CONCEPTUAL MODEL OF LOAD SHEDDINGFigure 2: Research frameworkIMPLEMENTATION OF FUZZY LOGIC ALGORITHM FOR LOAD SHEDDINGDEVELOP THE PROGRAMMING CODES IN MATLABDEVELOPMENT OF SIMPLELOAD SHEDDING TECHNIQUE AND UVLSLOADSHEDDINGFUZZY LOGIC ALGORITHMMATLAB PROGRAMMINGKNOWLEDGE ACQUISITION START</p> <p>1.6 OVERVIEW OF THE REPORT</p> <p>This thesis consist of five chapters explain about solving under voltage load shedding (UVLS) schemes implemented by using fuzzy logic system. Chapter 1 describes an introduction of the project which includes the objective of this research and also scope of work to complete this project.</p> <p>In Chapter 2, the theory and basic of voltage stability, under voltage load shedding and fuzzy logic systems are reviewed and explained properly. The summary are include the full details of problem in power system, theory of UVLS scheme, theory of fuzzy logic and its application and some literature review on method to solve the load shedding problems. </p> <p>This project thesis was followed by the design methodology that explained clearly in Chapter 3. This chapter explains the DED formulation algorithm including all the constraints and the PSO techniques algorithm and lastly implementation of PSO techniques to DED problems. This chapter also indicates the flow chart of DED based on PSO techniques.</p> <p>Next is Chapter 4 that illustrated all the results obtained together with the discussion of the results. All the tables and graph plotted are discussed clearly in this chapter including the analysis of PSO techniques on DED solution. </p> <p>On the Chapter 5, a conclusion that has been made upon the result obtains and the last chapter is Chapter 6 which discusses the recommendations for future works in order to improve the s...</p>