Bi-level fuzzy stochastic-robust model for flexibility valorizing of renewable networked microgrids

This paper presents a new bi-level multi-objective model to valorize the microgrid (MG) flexibility based on flexible power management system. It considers presence of renewable and resources including demand response program (DRP), energy storage system integrated unit electric spring with vehicles (EVs) parking (IUEE). The proposed in upper-level maximizes expected profit subject constraints. Also, lower level, minimizing MG cost voltage deviation function Pareto optimization technique is considered as objective functions; it bounded by linearized AC optimal flow constraints, limits, restrictions. In following, using Karush–Kuhn–Tucker (KKT) converted single-level counterpart, fuzzy decision-making method employed achieve best compromise solution. Further, hybrid stochastic-robust programming models uncertain parameters model, so that stochastic uncertainties associated demand, price, maximum renewables active generation. capture potential capabilities IUEE, robust EVs’ uncertainty. Finally, numerical results confirm could jointly improve operation, economic conditions turned flexi-optimized-renewable MG. • Bi-level value presented. Integrated modeled. deals maximizing microgrids. Fuzzy stochastic/robust handle