Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty

Networked microgrids (NMGs) are beneficial and economical for both microgrids' owners and consumers as this structure could potentially play a significant role in energy efficiency, power system reliability and sustainability. Renewable energy sources (RESs) and sharp fluctuations in load consumption impose new challenges in solving operational problems in smart distribution grids. As a result, deterministic methods are not able to provide a precise analysis of microgrids operation and planning. Therefore, stochastic algorithms are used as powerful tools in ensuring reliable solutions especially in operation problems. In this paper, daily optimal scheduling problem of NMGs considering intermittent behavior in generation and load is investigated in a proposed energy management system (EMS). Two demand response programs (DRPs) based on time of use (TOU) and real time pricing (RTP) are integrated into the optimal scheduling model and the developed model is solved using a metaheuristic algorithm under uncertainties of RESs and loads. The numerical simulations show the effectiveness of the proposed model through comparison with solution from stochastic optimization.