Optimal Power Flow and Optimal Reactive Power Dispatch Incorporating TCSC-TCPS Devices Using Different Evolutionary Optimization Techniques

The introduction of flexible AC transmission system (FACTS) has added a new dimension in power system operation and planning. Various types of FACTS controllers such as static compensator (STATCOM), static synchronous series compensator (SSSC), thyristor control series compensator (TCSC), thyristor control phase shifter (TCPS), unified power flow controller (UPFC), etc. are successfully used by various researchers in order to get optimal performance of power system. In this chapter, the various population-based nature-inspired techniques such as grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) are used to find the optimal size of TCSC and TCPS devices in order to find the optimum performance of IEEE 30-bus power system. The simulation results of various cases demonstrate the effectiveness and robustness of the proposed techniques to solve TCSC-TCPS-based OPF and ORPD problems.

Optimal Power Flow and Optimal Reactive Power Dispatch Using Different Evolutionary Optimization Techniques

This chapter describes grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) algorithms to solve both single and multi-objective optimal power flow (MOOPF) and optimal reactive power dispatch (ORPD) problems while satisfying various operational constraints. The proposed HCRO approach along with GWO, TLBO, BBO, KHA, and CRO algorithms are implemented on IEEE 30-bus system to solve four different single objectives: fuel cost minimization, system power loss minimization, voltage stability index minimization, and voltage deviation minimization; two bi-objectives optimization, namely minimization of fuel cost and transmission loss; minimization of fuel cost and voltage profile; and one tri-objective optimization, namely minimization of fuel cost, minimization of transmission losses, and improvement of voltage profile simultaneously. The simulation results clearly suggest that the proposed is able to provide a better solution than other approaches.

Economic Load Dispatch

The main objective of the power system is to deliver electric energy to its loads economically and efficiently in a safe and reliable manner. Due to the complicated structure of the present power system network and competitive environment introduced by deregulation, optimal power flow (OPF) and optimal reactive power flow (ORPD) provide efficient exploitation of existing power generations. This chapter describes the detail problem formulation of OPF and ORPD problems. In this study, three different single objectives, namely fuel cost minimization, voltage profile improvement, and transmission loss minimization, are considered. Moreover, in order to judge the effectiveness of the proposed methods for multi-objective scenario, two bi-objectives, namely simultaneous minimization of fuel cost and voltage deviation; simultaneous minimization of fuel cost and transmission loss; and one tri-objective function, namely simultaneous minimization of fuel cost with voltage deviation and loss, are considered.

Optimal Location of TCSC, TCPS, and SVC Devices for Solving OPF and ORPD Problem Using Different Evolutionary Optimization Techniques

The secure operation of power system has become a topmost issue in today's largely complicated interconnected power systems. This chapter presents the implementation of grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) approaches to find the optimal location of various FACTS devices such as thyristor control series compensator (TCSC), thyristor control phase shifter (TCPS), and static VAR compensator (SVC) to solve optimal power flow (OPF) and optimal reactive power dispatch (ORPD) in power system. In this chapter, a standard IEEE 30-bus test system with multiple TCSC and TCPS and SVC devices are used for different single and multi-objective functions to validate the performance of the proposed methods. The simulation results validate the ability of the HCRO to produce better optimal solutions compared to GWO, TLBO, BBO, KHA, and CRO algorithms.

Power Flow Modeling in Power System With Multiple FACTS Controller

Flexible AC transmission systems (FACTS) devices are integrated into power system networks to control power flow, increase transmission line capability to its thermal limit, and improve the security of transmission systems. Power flow is an important mathematical calculation for planning, operation, and control of power systems network. The focus of the chapter is to explore how to modify Newton-Raphson power flow method to include various FACTS devices such as static VAR compensator (SVC), static synchronous compensator (STATCOM), static synchronous series compensator (SSSC), thyristor-controlled series capacitor (TCSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC) controllers. This chapter briefly describes the power flow equations of the aforesaid FACTS-based power system network, and how the conventional power flow calculation is systematically extended to include these controllers is also been discussed.

Optimal Location of STATCOM, SSSC, and UPFC Devices for Solving OPF and ORPD Problem Using Different Evolutionary Optimization Techniques

The development of FACTS devices based on the advance of semiconductor technology opened up new opportunities for controlling the power flow and extending the load ability of the power transmission network. Amongst the various FACTS devices, the UPFC is considered the most versatile FACTS device that can simultaneously control bus voltage and both active and reactive power flow through the transmission line. This chapter discusses the implementation of grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) approaches to find the optimal placement and parameter setting of unified power flow controller (UPFC) to achieve the optimal performance of optimal power flow (OPF) and optimal reactive power dispatch (ORPD) problems. Two test systems, namely IEEE 14-bus and IEEE 30 with valve-point non-linearity, are considered to demonstrate the effectiveness of proposed approaches.

Evolutionary Algorithm Applied to Economic Load Dispatch

This chapter introduces various evolutionary algorithms, namely grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO) algorithms, for solving the economic load dispatch (ELD) problem of various power systems. To demonstrate the superiority of the proposed approaches in solving non-convex, non-linear and constrained ELD problem, the aforesaid approaches are implemented on 10-unit, 15-unit, 40-unit, 80-unit, and 140-unit test systems. It is observed from the simulation results that HCRO exhibits significantly better performance in terms of solution quality and convergence speed for all the cases compared to other discussed algorithms. Furthermore, the statistical results confirm the robustness of the proposed HCRO algorithm.

Description of Various Evolutionary Optimization Techniques

Despite the success of various classical optimization techniques, there remains a large class of problems where either these methods are unable to find the satisfactory results or the computational times are sufficiently large. Several heuristic methods have emerged in the recent years as complementary tools to various mathematical approaches. These methods include genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE), and so on. Researchers are constantly trying to learn from the behavioral pattern of organisms and implementing those ideas and philosophies in solving optimizing problems. In this chapter, a few efficient optimization algorithms, namely grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO) algorithms, and hybrid CRO (HCRO) are discussed, and in the subsequent chapters, the performance of the aforesaid algorithms are investigated by applying them in a few areas of power systems.

Flexible AC Transmission Systems (FACTS) Controller in Power Transmission

Secure and reliable operation of the power system is a critical issue for large, complicated, and interconnected power system networks. Security constraints such as thermal limits of transmission lines and bus voltage limits must be satisfied under any operating point in order to deliver reliable power to the consumers. One of the best alternative solutions of improvement of the security of power system is the use of flexible AC transmission systems (FACTS) devices. FACTS devices can be used to limit the power flow on the overloaded line and to increase the use of alternative paths to improve power transmission capacity. This chapter briefly describes all three categories of FACTS devices, namely shunt controllers (static synchronous compensator, static var compensator, thyristor-controlled reactor, thyristor switched reactor, thyristor switched capacitor), series controllers (static synchronous series compensator, thyristor controlled series capacitor, thyristor-controlled series reactor), and combined series-shunt controllers (unified power flow controller).