Artificial Bee Colony Optimization for Optimal Reactive Power Dispatch Incorporating FACTS Devices

Artificial Bee Colony Optimization for Optimal Reactive Power Dispatch Incorporating FACTS Devices

Susanta Dutta (Department of Electrical Engineering, Dr. B.C.Roy Engineering College, Durgapur, India), Provas Kumar Roy (Department of Electrical Engineering, Dr. B.C.Roy Engineering College, Durgapur, India) and Debashis Nandi (Department of Information Technology, National Institute of Technology, Durgapur, India)
Copyright: © 2014 |Pages: 21
DOI: 10.4018/ijeoe.2014040103
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Abstract

This paper illustrates, for the first time, the use of artificial bee colony optimization (ABC) technique to study optimal reactive power dispatch (ORPD) in power system with the use of flexible AC transmission systems (FACTS). FACTS controller cannot only increase the power transmission capacity without installing new transmission lines, but they can also enhance voltage profile and reduce transmission loss in power system. Two types of FACTS devices namely, thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifter (TCPS) are considered in this paper. A standard IEEE 30-bus test system with multiple TCSC and TCPS devices is used for two different objective functions to validate the performance of the proposed method. The simulation results demonstrates the ability of the ABC to produce better optimal solutions compared to particle swarm optimization with inertia weight approach (PSOIWA) and real coded genetic algorithm (RGA).
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1. 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 and Yun (1998) ”, Newton’s method “ Ambriz-Pérez, Acha and Fuerte-Esquivel (2006)”, linear programming “Sundar and Ravikumar (2012)”, interior-point method “Rakpenthai, Premrudeepreechacharn and Uatrongjit (2009) ”. However, these techniques have limitations in handling nonlinear, discontinuous functions and constraints, and often lead to a local minimum point “Chung and 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 and Bhattacharjee (2012)”, hybrid tabu search “Bhasaputra and Ongsakul (2002)”, genetic algorithm (GA) “Cai and Erlich (2003);Ippolito, Cortiglia and Petrocelli (2006); Mahdad, Srairia and Bouktir (2010); Wirmond, Fernandes, and Tortelli (2011)”, particle swarm optimization (PSO) “Benabid, Boudour and Abido (2009); Kennedy and Eberhart (1995); Mollazei, Farsangi, and Nezamabadi-pour (2007) ; Mondal, Chakrabarti and Sengupta (2012); Roy, Ghoshal and Thakur (2010); Saravanan, Slochanal, Venkatesh and Abraham (2007)”, differential evolution (DE) “Basu (2008); Shaheen, Rashed and Cheng (2011)”, ant colony optimization (ACO) “Sreejith, Chandrasekaran and Simon (2009)”, bacteria foraging optimization (BFO) “Abd-Elazim and Ali (2012)”, biogeography based optimization (BBO) “Roy, Ghoshal and Thakur (2011); Roy, Ghoshal and Thakur (2012) ”, immune algorithm “Taher and Amooshahi (2011)”, harmony search algorithm (HSA) “Sirjani, Mohamed and Shareef (2012)”, gravitational search algorithm (GSA) “Bhattacharya and Roy (2012); Roy, Mandal and Bhattacharya (2012); Sonmez, Duman, Guvenc and Yorukeren (2012); Altinoz, Yilmaz and Weber (2013) ”, 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.

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