Optimal Power Flow Integrating Renewable Energy Sources in Microgrid Employing Hybrid Grey Wolf- Equilibrium Optimizer

Abstract

The grid electricity market is undergoing massive transformation in the midst of advent of renewable energy sources (RES). The intermittent and stochastic nature of RES poses a great challenge for effective and economical operation of the grid. The optimal power flow mathematical formulation has high non-convexity as well as non-linearity. The complexity further increases by the addition of the RES for the grid stability and adequacy. This paper proposes a hybrid Grey wolf - Equilibrium Optimizer (HGW-EO) for finding optimal scheduling of a hybrid power plant consisting of thermal generators, wind power farms and solar power farm. The uncertainty of the solar and wind power is considered for real time grid operation. The stochastic nature of wind and solar farms power output are forecasted using the Weibull and Lognormal probability density functions. For real world scenario, the overestimation and underestimation costs are also considered.A modified IEEE-30 bus system is utilised for testing and comparing the proposed HGW-EO algorithms to other metaheuristics methods showing promising results.