Intelligent energy management in hybrid microgrids considering tidal, wind, solar and battery

Abstract

This article addresses the optimal management of hybrid microgrids considering varied types of renewables such as wind, tidal and solar units. The proposed model considers an AC formulation for the AC part and a DC formulation for DC part which can cooperate with each other to reduce the costs and supply the loads in a high-quality and safe zone. Also, a stochastic structure based on a new point estimate method is developed to capture the uncertainties rooting from the forecasting of tidal unit, wind unit and solar unit, market price and total load demand. In contrast to the conventional methods, only a few concentration points of the probability density function fitting uncertain parameters are needed to make a comprehensive modeling of the problem randomness. Due to the nonlinear and complex nature of the problem, an innovative optimization algorithm based on bat algorithm is proposed to solve the problem. Moreover, a modification approach is devised to let the method increase its population variety and make a better search. The fitting performance and high efficacy of the proposed model is inspected on an IEEE test system.