Abstract
Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.
Highlights
The optimal reactive power dispatch (ORPD) is a sub problem of the optimal power flow calculation and has a significant influence on secure and economic operation of power systems
The goal of optimal reactive power dispatch [7,8,9] is to determine the optimum values of independent variables by optimizing a predefined objective function with respect to the operating bounds of the system
The heuristic algorithm optimization is required in finding the optimal settings of control variables including voltage magnitude of a new distributed generating (DG)
Summary
The optimal reactive power dispatch (ORPD) is a sub problem of the optimal power flow calculation and has a significant influence on secure and economic operation of power systems. Several conventional optimization algorithms [3] have been proposed to solve the ORPD problem such as linear programming, quadratic programming, and interior point method. As the ORPD is nonlinear, evolutionary computation methods such as genetic algorithm (GA) [4], evolutionary programming (EP) and particle swarm optimization (PSO) [5] algorithm are best suitable to solve it. An application of particle swarm optimization (PSO) and MATPOWER toolbox [6] is used to solve optimal reactive power dispatch problem integrating a new DG.
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