Improved grey wolf optimizer for optimal reactive power dispatch with integration of wind and solar energy

The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). It is a nonlinear multivariable problem of optimization, with multiconstraints. The purpose is to minimize real power losses and improve the voltage profile of a given electric system by adjusting control variables, such as generator voltages, tap ratios of a transformer, switching VAr sources, without violating technical constraints that are presented as equalities and inequalities. Methodology. Metaheuristics are stochastic algorithms that can be applied to solve a wide variety of optimization problems without needing specific problem structure information. The penetration of RERs into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. It is essential to include these sources in power flow studies. The wind and photovoltaic based systems are the most applied technologies in electrical systems compared to other technologies of RERs. Moreover, grey wolf optimizer