کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6859372 1438701 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong's point estimate method
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong's point estimate method
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 99, July 2018, Pages 481-492
نویسندگان
, ,