Optimal reactive power dispatch in power system comprising renewable energy sources by means of a multi-objective particle swarm algorithm

The electricity grid is developing fast today, with more renewable energy sources (RES) penetrating the industry. The traditional optimal reactive power dispatch (ORPD) is a complex and non-linear optimization problem and one of the sub-problems of the optimal distribution of the power flows in an energy system. The incorporation of RES further exacerbates this complex problem. In this paper, the ORPD problem solved as a single-objective as well as a multi-objective optimization problem in a power system comprising RES. This paper aims to minimize the active power loss and improve voltage profile by introducing renewable energy sources, such as wind and solar sources, in addition to the existing traditional sources. The optimization in a power system is achieved by adjusting control variables, such as generator voltages, tap ratios of a transformer, shunt capacitors, without violating technical constraints that are presented as equalities and inequalities. A multiobjective particle swarm optimization (MOPSO) algorithm is proposed to obtain the optimal values of the control variables of the power system. In the first stage, the modified PSO (MPSO) used to determine the optimal location of RES for IEEE 14 bus and IEEE 30 bus test systems. In the second stage, MPSO and genetic algorithm (GA) were used for individual optimization of objectives, and in the third stage, the objective functions are treated as competing objectives and optimized simultaneously in a single run. Finally, the best compromise solution was extracted from the optimal Pareto set and supplied to the decision-maker by fuzzy set theory. Also, the results of MOPSO are compared to MPSO, GA, and multi-objective GA.