The chapter presents two effective evolutionary methods, namely, artificial bee colony optimization (ABC) and biogeography based optimization (BBO) for solving optimal reactive power dispatch (ORPD) problem using flexible AC transmission systems (FACTS) devices. The idea is to allocate two types of FACTS devices such as thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifter (TCPS) in such a manner that the cost of operation is minimized. In this paper, IEEE 30-bus test system with multiple TCSC and TCPS devices is considered for investigations and the results clearly show that the proposed ABC and BBO methods are very competent in solving ORPD problem in comparison with other existing methods.
Top1. Introduction
The secure operation of power system has become an important and critical issue in today’s large, complicated, and interconnected power systems. Security constraints such as thermal limits of transmission lines and bus voltage limits must be satisfied under any operating point. The best alternative solution of improvement of the security of power system is the use of Flexible AC Transmission Systems (FACTS) devices. FACTS devices can be used to reduce the flow of power on the overloaded line and to increase the use of alternative paths to improve power transmission capacity. This allows existing transmission and distribution systems to operate under normal operating conditions and allows the load lines to operate much closer to their thermal limits. Now-a-days these power electronics based devices have become very popular in improving the overall performances of power system under both steady state and dynamic condition.
Optimal reactive power dispatch (ORPD) problem is one of the major issues in operation of power systems. Because of its significant influence on secure and economic operation of power systems, ORPD has received an ever-increasing interest from electric utilities. On the other hand, FACTS devices can reduce the power flows of heavily loaded lines, maintain the bus voltages at desired level, and consequently, they can reduce the transmission loss. Therefore, the optimal reactive power dispatch incorporating FACTS devices has become an important area of research in recent years and it motivates the authors to work on FACTS based ORPD problem whose main objective is to minimize the network losses at improve voltage level and maintain the power system under normal operating conditions.
In this study, flexible AC transmission system (FACTS) devices are considered as additional control parameters in the ORPD formulation. Static models of two FACTS devices consisting of thyristor controlled series compensator (TCSC) and thyristor controlled phase shifter (TCPS) are used in the present work. Minimization of the transmission loss and voltage deviation are achieved by finding suitable values of FACTS devices along with other control variables such as generator bus voltage, reactive power generation and transformer tap settings in the original ORPD problem.
A number of numerical optimization techniques have been proposed to solve the traditional ORPD problem, such as quadratic programming (Chung & Yun 1998), Newton’s method (Ambriz-Pérez, Acha & Fuerte-Esquivel, 2006), linear programming (Sundar & Ravikumar, 2012), interior-point method (Rakpenthai, Premrudeepreechacharn & Uatrongjit, 2009), etc. However, these techniques have limitations in handling nonlinear, discontinuous functions and constraints, and often lead to a local minimum point (Chung & Yun, 1998). But due to non-continuous, non-linear and non-differential objective function and constraints of FACTS based ORPD, these methods are unable to locate the global optimum solution. Recently, some new heuristic methods like evolutionary programming (EP) “Ma (2003);Ongsakul and Jirapong (2005)”, simulated annealing (SA) (Majumdar, Chakraborty, Chattopadhyay & Bhattacharjee, 2012), hybrid tabu search (Bhasaputra & Ongsakul, 2002), genetic algorithm (GA) (Cai & Erlich 2003; Ippolito, Cortiglia & Petrocelli, 2006; Mahdad, Srairia & Bouktir, 2010; Wirmond, Fernandes, & Tortelli, 2011), particle swarm optimization (PSO) (Benabid, Boudour & Abido, 2009; Kennedy & Eberhart, 1995; Mollazei, Farsangi & Nezamabadi-pour 2007; Mondal, Chakrabarti & Sengupta, 2012; Roy, Ghoshal & Thakur, 2010; Saravanan, Slochanal, Venkatesh & Abraham, 2007), differential evolution (DE) (Basu, 2008; Shaheen, Rashed & Cheng, 2011), ant colony optimization (ACO) (Sreejith, Chandrasekaran & Simon, 2009), bacteria foraging optimization (BFO) (Abd-Elazim & Ali, 2012), biogeography based optimization (BBO) (Roy, Ghoshal & Thakur, 2011; Roy, Ghoshal & Thakur, 2012), immune algorithm (Taher & Amooshahi, 2011), harmony search algorithm (HSA) (Sirjani, Mohamed & Shareef, 2012), gravitational search algorithm (GSA) (Bhattacharya & Roy, 2012; Roy, Mandal & Bhattacharya, 2012; Sonmez, Duman, Guvenc & Yorukeren, 2012), have been developed for the nonlinear optimization problem. These methods can generate high-quality solutions and have stable convergence characteristic when dealing with ORPD problem and other complex optimization problems in power systems.