Abstract
The problem of optimal reactive power dispatch (ORPD) is one of the most popular and widely discussed problem in power system engineering all over the world. Optimal reactive power dispatch is one of the sub-problems of the optimal power flow which is complex and nonlinear problem, which can be formulated as both single- and multi-objective. In this paper, the problem has been formulated as a single-objective problem to minimize the active power losses in the transmission lines. A recently proposed powerful and reliable meta-heuristic algorithm known as the JAYA algorithm has been applied to solve the ORPD problem. The algorithm has been applied on the standard IEEE 14, 30, 57 and 118 bus systems. The simulation results using the proposed algorithm when compared with the results from other algorithms and few others reported in the literature prove that the JAYA algorithm is the most superior among all.
Highlights
The major challenges in power system engineering nowadays is the large expansion of power and the system stability accompanied with it
Another major problem is the increase in the active power losses in the transmission line, which results in low efficiency of the system and restrict the expansion of power to a certain limit
Problem formulation This paper aims at minimizing the active power loss in the transmission lines by determining the optimal solutions to the optimal reactive power dispatch (ORPD) problem
Summary
The major challenges in power system engineering nowadays is the large expansion of power and the system stability accompanied with it. The solution of the ORPD problem is to minimize the objective function by satisfying the operating constraints It helps in optimally redistributing the reactive power in the system resulting in minimization of transmission line active power losses and improving the voltage profile in the system. Due to this nonlinearity of the problem, many conventional techniques of optimization like the Newton method, quadratic programming, linear programming and interior point methods have failed to solve the ORPD problem due to their low accuracy, complexity, inability to find the local and global optima and resulting in secure converge [1,2,3,4]. These variables are constrained using penalty coefficients to the objective function in Eq (1)
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