optimal allocation of facts devices to enhance voltage stability of power systems Amr Magdy Abdelfattah Sayed A thesis submitted to the

Transcription

1 optimal allocation of facts devices to enhance voltage stability of power systems By Amr Magdy Abdelfattah Sayed A thesis submitted to the Faculty of Engineering at Cairo University In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE In Electrical Power and Machines Engineering FACULTY OF ENGINEERING, CAIRO UNIVERSITY GIZA, EGYPT 2012

2 OPTIMAL ALLOCATION OF FACTS DEVICES TO ENHANCE VOLTAGE STABILITY OF POWER SYSTEMS By Amr Magdy Abd ElFattah Sayed A thesis submitted to the Faculty of Engineering at Cairo University In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE In Electrical Power and Machines Engineering Under Supervision of Prof. Dr. Hosam Kamal Mohamed Electrical Power and Machines Dept Faculty Of Engineering Cairo University Assoc. Prof. Dr. Doaa khalil Ibrahim Electrical Power and Machines Dept. Faculty Of Engineering Cairo University FACULTY OF ENGINEERING, CAIRO UNIVERSITY GIZA, EGYPT January 2012

3 OPTIMAL ALLOCATION OF FACTS DEVICES TO ENHANCE VOLTAGE STABILITY OF POWER SYSTEMS By Amr Magdy Abdelfattah Sayed A thesis submitted to the Faculty of Engineering at Cairo University In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE In Electrical Power and Machines Engineering Approved by the Examining Committee Prof. Dr. Hosam Kamal Mohamed Youssef Main Supervisor Prof. Dr. Essam El-Din Abou El-Zahab Member Prof. Dr. Said Wahsh Member FACULTY OF ENGINEERING, CAIRO UNIVERSITY GIZA, EGYPT January 2012

4 ACKNOWLEDGEMENT I would like deeply to express my gratitude to Prof. Dr. Hosam Kamal Mohamed for all his support, guidance and help during all these years of study. I wish to thank Assoc. Prof. Dr. Doaa khalil Ibrahim for her support. I wish to thank Prof. Dr. Essam El-Din Abou El-Zahab and Prof. Dr. Said Wahsh. I wish to thank all who taught me in both undergraduate and postgraduate studies. Words can not express my gratitude and appreciation to my parents for everything they did for me. I would like to express my gratitude to Eng. Helmy Abd El-Rahman (Department manager - Enppi company) for his support. I would like to thank Eng. Waleed Gad (Section head - Enppi company) for his support, guidance and encouragement. I wish to thank Mr. Mohamed Khater (Panan company) for his encouragement. I would like to thank my wife for her support during all these years. Thanks to all my friends who supported and encouraged me. All thanks and acknowledgements to Allah who enabled me to accomplish this work successfully. i

5 CONTENTS Page LIST OF TABLES vi LIST OF FIGURES vii LIST OF SYMBOLS viii LIST OF ABBREVIATIONS x ABSTRACT xiii Chapter 1: Introduction General Classification of Power System Stability Voltage stability Synchronous or rotor angle stability Frequency stability Power System Stability Analysis Steady-state analysis Dynamic analysis Voltage Stability and the Timeframes of Interest Short-term timeframe Mid-term timeframe Long-term timeframe Voltage Stability Analysis Techniques Static voltage stability analysis techniques Continuation power flow (CPF) Optimal power flow (OPF) Modal analysis Dynamic voltage stability analysis techniques Hopf bifurcation point Time-domain simulation Alleviating Voltage Stability Static VAR compensator (SVC) 9 ii

6 1.6.2 FACTS Thesis Organization 11 Chapter 2: Literature Review on FACTS Allocation Sensitivity Based Methods Classical Optimization Methods Modern Heuristic Optimization Methods Genetic algorithm Evolutionary programming Tabu search Simulated annealing (SA) PSO Major Advantages of Modern Heuristic Optimization Methods 18 Chapter 3: Voltage Control Voltage Instability Mechanism of Steady State Voltage Instability Voltage Collapse Principal Causes of Voltage Stability Problems Methods of Voltage Control Shunt reactors Shunt capacitors Series capacitors Synchronous condensers ULTCs FACTS devices 29 Chapter 4: FACTS Devices FACTS Applications Overview on FACTS Devices Configurations of FACTS Devices Shunt devices SVC STATCOM 41 iii

7 4.3.2 Series devices TCSC SSSC Shunt and series devices Dynamic flow controller Unified power flow controller Interline power flow controller Generalized unified power flow controller (GUPFC) Back-to-back devices 49 Chapter 5: Optimization Techniques Historical Development Engineering Applications of Optimization Classical Optimization Techniques Modern Heuristic Optimization Techniques Advantages of Evolutionary Computation Conceptual simplicity Broad applicability Outperform classic methods on real problems Potential to use knowledge and hybridize with other methods Parallelism Robust to dynamic changes Capability for self-optimization Able to solve problems that have no known solutions An overview of modern heuristic optimization techniques Genetic algorithm (GA) Evolution strategies and evolutionary programming Ant colony algorithms Tabu search (TS) Simulated annealing Fuzzy systems Differential evolution (DE) 65 iv

8 Pareto multi-objective optimization Trust-Tech paradigm for computing high-quality optimal solutions PSO 66 Chapter 6: Particle Swarm Optimization PSO Searching Procedure PSO Algorithm and Flowchart 71 Chapter 7: Application of PSO in Optimal Allocation of FACTS Devices 7.1 Problem Identification Problem Formulation SVC modeling Statement of an optimization problem Design Vector Design Constraints Objective Function PSO Parameters The Application of Thesis Problem on IEEE 14-bus system 80 Chapter 8: Conclusions and Future Work Summary of results Future Work v

9 LIST OF TABLES Table 4.1: Estimated number of worldwide installed FACTS devices and the estimated total installed power Page 37 Table 7.1: Voltage profile of IEEE 14-bus system without installing SVC 83 Table 7.2: Voltage profile of overloaded IEEE 14-bus system 84 Table 7.3: Voltage profile of IEEE 14-bus system after T.L. outage without installing SVC 85 vi

10 LIST OF FIGURES Figure 1.1: Time responses of different controls and components to voltage stability Figure 1.2: An example of P-V curve showing points of collapse before and after compensation Figure 3.1: P-V characteristic curve 21 Figure 4.1: Operational limits of transmission lines for different voltage levels Figure 4.2: Overview of major FACTS-Devices 34 Figure 4.3: SVC structure 40 Figure 4.4: Site view of SVC 40 Figure 4.5: STATCOM structure 41 Figure 4.6: TCSC configuration 43 Figure 4.7: TCSC on transmission level 44 Figure 4.8: SSSC structure 45 Figure 4.9: DFC configuration 46 Figure 4.10: Principle configuration of an UPFC 47 Figure 4.11: Principle configuration of an IPFC 48 Figure 4.12: Principle configuration of a GUPFC 49 Figure 4.13: Schematic configuration of a HVDC Back-to-Back with Voltage Source Converters Figure 5.1: Minimum of f(x) is same as maximum of -f(x). 52 Figure 5.2: The main flowchart of the vast majority of evolutionary algorithms Figure 5.3: The behavior of real ants. 63 Figure 6.1: Concept of modification of a searching point by PSO. 71 Figure 6.2: A general flowchart of PSO. 73 Figure 7.1: IEEE 14-bus system 81 Page 5 Figure 7.2: Flow chart of the program vii

11 LIST OF SYMBOLS A, B Line constants C c 1, c 2 Csvc gbest iter max iter L P r Capacitance Weighting coefficients Cost of SVC in united states dollar/kvar Best value of the group Maximum number of iterations Current iteration number Inductance Load active power P 1 Power at point 1 pbest i Q r Q svc Best value of agent i Load reactive power Rating of SVC in pu rand 1 Random number between 0 and 1 rand 2 Random number between 0 and 1 S k s i Operating range of the FACTS device in MVAR Current position of agent i at iteration k VD V i Voltage deviation Voltage magnitude at load bus i k v Velocity of agent i at iteration k, i V r Receiving end voltage viii

12 V s v x v y w max w min YBus α Sending end voltage Velocity of x axis Velocity of y axis Initial weight Final weight Admittance matrix Angle of line constant A α1, α2 Constants indicate the relative weights of objective functions β Angle of line constant B ix

13 LIST OF ABBREVIATIONS ACO ACSA CPF CR CSC DE DFC DVR EP EPRI ES FACTS GA GUPFC IGBT IGCT IPFC LTC MBS MILP MINLP Ant colony optimization Ant colony search algorithm Continuation power flow Convergence rate Convertible static compensator Differential evolution Dynamic power flow controller Dynamic voltage restorer Evolutionary programming Electric power research institute Evolution strategies Flexible ac transmission systems Genetic algorithm Generalized unified power flow controller Insulated gate bipolar transistor Insulated ate commutated thyristor Interline power flow controller Load tap changer Model-based search Mixed integer linear programming Mixed integer nonlinear programming x

14 MO MSC NYPA ODE OEL OLTC OPF PoC PSO PST SA SCOPF SCS SM SO SSR SSSC STATCOM SVC SVR TCR TCSC TS Multi-objective Mechanically switched shunt capacitor New York power authority Ordinary differential equation Over-excitation limiter On load tap-changer Optimal power flow Point of collapse Particle swarm optimization Phase shifting transformer Simulated annealing Security constrained optimal power flow Single contingency sensitivity Stability margin Single-objective Sub-synchronous resonance Static synchronous series compensator Static compensator Static var compensator Static voltage restorer Thyristor controlled reactor Thyristor controlled series compensator Tabu search xi

15 TSC TTC ULTC UPFC VSC Thyristor switched capacitor Total transfer capability Under load-tap changer Unified power flow controller Voltage source converter xii

16 ABSTRACT In the last few years, voltage instability problems in power systems have been of permanent concern for electric utilities. Power demand has increased substantially while the expansion of power generation and transmission has been severely limited due to limited resources and environmental restrictions. As a consequence, some transmission lines are heavily loaded and the system becomes unstable. This thesis discusses voltage instability problem illustrating principle causes of voltage instability and mechanism of steady state voltage instability. Several network blackouts have been related to voltage collapses. This phenomenon tends to occur due to lack of reactive power supports in heavily stressed conditions, which are usually triggered by system faults. Therefore, the voltage collapse problem is closely related to a reactive power planning problem including contingency analysis. The objective of the reactive power planning problem is to provide a minimum number of new reactive power supplies to satisfy the voltage feasibility constraints in normal and post-contingency states. Methods of voltage control are discussed in this thesis especially Flexible AC Transmission Systems (FACTS) devices. FACTS devices have been mainly used for solving various power system steady state control problems. However, recent studies reveal that FACTS devices could be employed to enhance voltage stability in addition to their main function of power flow control. It is important to ascertain the optimum location and rating of these devices because of their high costs. In this thesis, an optimization problem is formulated where the objective function is to minimize voltage deviation with minimum cost of installation of FACTS. Minimization of voltage deviation is chosen because the main factor contributing to voltage instability is usually the voltage drop that occurs when xiii

17 active and reactive power flow through inductive reactances associated with the transmission network. Optimization techniques are surveyed to utilize one of them in solving such problem. Modern heuristic optimization techniques outperform classical techniques of optimization because of their simplicity, broad applicability, robustness to dynamic changes and their ability to solve problem that are difficult to be solved by classical techniques. Among modern heuristic optimization techniques is the particle swarm optimization (PSO) which is studied deeply and chosen to be employed in thesis optimization problem. PSO has gained rapid popularity as an efficient optimization technique. It is based on the analogy of swarm of birds and school of fish. It has the ability to enhance and adapt the global and local exploration abilities within a short calculation time. The main advantages of PSO algorithm are summarized as: simple concept, easy implementation, robustness to control parameters, and computational efficiency when compared with mathematical algorithm and other heuristic optimization techniques. PSO is employed to allocate FACTS in IEEE 14-bus system being subjected to two different conditions: Overloading the whole system by increasing real and reactive loads. Outage of a transmission line. Simulation results within this research show a significant improvement of voltage profile after optimal allocation of FACTS using PSO. xiv

18 Chapter 1 Introduction 1.1 General In recent years, power demand is increasing continuously while the expansion of power generation and transmission is severely limited due to limited resources and environmental restrictions. As power systems become more heavily loaded due to increased power consumption and larger networks interconnections, systems are forced to operate closer to their capability limits. Power systems operation needs high degree of reliability and security levels with investment cost as the prime factor. Considering this issue, voltage stability has become a matter of great concern worldwide due to the significant number of blackouts which have occurred and which frequently have involved voltage stability issues. 1.2 Classification of Power System Stability Power system stability may be broadly defined as that property of a power system that enables it to remain in a state of operating equilibrium under normal operating conditions and to regain an acceptable state of equilibrium after being subjected to a disturbance [1]. Instability of the power system can take different forms and is influenced by a wide range of factors. Analysis of stability problems is greatly facilitated by classification of stability into appropriate categories [2]. 1

19 1.2.1 Voltage stability Voltage stability is the ability of a power system to maintain steady voltages at all buses in the system under normal operating conditions and after being subjected to a disturbance. The main factor contributing to voltage instability is usually the voltage drop that occurs when active and reactive power flow through inductive reactances associated with the transmission network. This limits the capability of transmission network for power transfer. The power transfer limit is further limited when some of the generators hit their reactive power capability limits. The driving force for voltage instability is the loads; in response to a disturbance, power consumed by the loads tends to be restored by the action of distribution voltage regulators, tap changing transformers. Restored loads increase the stress on the high voltage network causing more voltage reduction. A rundown situation causing voltage instability occurs when load dynamics attempts to restore power consumption beyond the capability of the transmission system and the connected generation Synchronous or rotor angle stability Rotor angle stability is the ability of interconnected synchronous machines of a power system to remain in synchronism under normal operating conditions and after being subjected to a disturbance. It depends on the ability to maintain/restore equilibrium between electromagnetic torque and mechanical torque of each synchronous machine in the system. Instability that may result occurs in the form of increasing angular swings of some generators leading to their loss of synchronism with other generators. Rotor angle stability problem involves the study of the electromechanical oscillations inherent in power systems. A fundamental factor in this problem is the manner in which the power outputs of synchronous machines vary as their rotor 2

20 angles change. The mechanism by which interconnected synchronous machines maintain synchronism with one another is through restoring forces, which act whenever there are forces tending to accelerate or decelerate one or more machines with respect to other machines. Under steady-state conditions, there is equilibrium between the input mechanical torque and the output electrical torque of each machine, and the speed remains constant. If the system is perturbed, this equilibrium is upset, resulting in acceleration or deceleration of the rotors of the machines according to the laws of motion of a rotating body. If one generator temporarily runs faster than another, the angular position of its rotor relative to that of the slower machine will advance. The resulting angular difference transfers part of the load from the slow machine to the fast machine, depending on the power-angle relationship. This tends to reduce the speed difference and hence the angular separation. The power-angle relationship is highly nonlinear. Beyond a certain limit, an increase in angular separation is accompanied by a decrease in power transfer; this increases the angular separation further and leads to instability. For any given situation, the stability of the system depends on whether or not the deviations in angular positions of the rotors result in sufficient restoring torques Frequency stability Frequency stability is concerned with the ability of a power system to maintain steady frequency within a nominal range following a severe system upset resulting in a significant imbalance between generation and load. It depends on the ability to restore balance between system generation and load, with minimum loss of load. Severe system upsets generally result in large excursions of frequency, power flows, voltage, and other system variables, thereby invoking the actions of processes, controls, and protections that are not modeled in conventional transient stability or voltage stability studies. In large interconnected power systems, this type of situation is most commonly associated with islanding. 3