Robust PSO ‐based framework for concurrent active/reactive and reserve management in microgrids in the presence of energy storage systems

Abstract

Nowadays, concurrent participation of distributed energy resources in providing electrical energy and ancillary services brings many benefits. Also, energy storage systems (ESSs) along with renewable generations have a growing penetration rate in modern power systems aimed at declining environmental issues. Due to the uncertainties of intermittent nonpredictable power resources in microgrids (MGs), high integration of these products leads to an increase in ancillary services requirements and it necessitates the coordinated management of these technologies with the ESSs. In this paper, for the first time, a robust model based on particle swarm optimization (PSO) metaheuristic is developed to cope with the uncertainty of renewables in concurrent active/reactive and reserve management problem in the MG with ESS. The robust framework provides a medium priority in comparison with deterministic and stochastic techniques. The objective function of the robust concurrent active/reactive and reserve scheduling problem in MGs is expressed as maximizing social welfare (SW). The proposed model is carried out using a max-min optimization scheme. The robust design will be attained in such a way that the maximizer at the outer level seeks an optimal solution against the worst-case objective function achieved through the minimizer at the inner level taking into account the uncertainty neighborhood. The performance of the presented approach has been evaluated on a typical MG. Simulation results verify that the suggested robust-PSO technique will aid MG operators to decrease daily operational costs and to yield a higher SW.