Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong's point estimate method
Abstract The increasing penetration of renewable energy resources (RER) and their stochastic behaviors on the one hand and also, sharp fluctuations of electricity prices on the other hand have created substantial challenges for optimal operation of microgrids (MG). demand response (DR) programs associated with reconfiguration of MGs can provide feasible solution for this issue. Therefore, to address the aforementioned uncertainties in the optimal operation of MGs, this paper proposes an innovative Hong’s 2m point estimate method (PEM) for simultaneously DR and reconfiguration scheduling with purpose to minimize the operating costs as well as to reinforce the reliability and resiliency of interconnected MGs in confronting with uncertainties. The Incentive-based model relies on interruptible/curtailable service (I/C) has been extended as DR program in the deregulated market. Meanwhile, an unprecedented dynamic reconfiguration problem has been optimally executed in order to reinforce the flexibility and robustness of MGs in confronting with diverse operating uncertainties. Finally, the proposed integrated model has been successfully solved by a population-based meta-heuristic algorithm namely exchange market algorithm (EMA). The simulation study is accomplished on the modified PG&E 69-bus distribution system over 24-h period. The obtained results demonstrate the usefulness and applicability of the proposed model. Highlights An integrated incentive-based DR and dynamic reconfiguration model is proposed. The merits of distribution buses are determined to participate in the proposed model. The uncertainty of the problem is considered by Hong’s 2m PEM. Dynamic reconfiguration is fulfilled to increase the flexibility of MGs versus uncertainty. EMA is utilized to solve the proposed cost-reliability based framework.
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