An intelligent approach based on GSO for optimal management of renewable-based MGs

Abstract

This article suggests a probabilistic framework based on Scenario production to take account the uncertainties in the optimal operation management of Micro Grids (MGs). The MG includes different renewable energy resources such as Wind Turbine (WT), Micro Turbine (MT), Photovoltaic (PV), Fuel Cell ( FC) and one battery as the storage device. The suggested framework is based on scenario generation and Roulette wheel mechanism to generate different scenarios for handling the uncertainties of different parameters. It uses normal distribution function as a probability distribution function of random parameters. The uncertainties which are considered in this paper are grid bid changes, load demand forecasting error and PV and WT output power productions. It is worthy to say that solving the MG problem for 24 hours of a day by considering different uncertainties and different constraints needs one powerful optimization method that can converge fast when it doesn’t fall in local optimum point. As a result, one Group Search Optimization (GSO) algorithm is introduced to prospect the total search space globally. The GSO algorithm is originated from group living of animals. Besides the GSO algorithm, one modification is also proposed for this algorithm. The proposed framework and method is implemented o one test grid-connected MG as a typical grid.