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A Smart Method for Multi-zonal Virtual Power Plant Scheduling with Presence of Electric Vehicles | ||
Modeling and Simulation in Electrical and Electronics Engineering | ||
مقاله 2، دوره 1، شماره 2 - شماره پیاپی 4، آبان 2021، صفحه 9-20 اصل مقاله (1.85 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22075/mseee.2021.20727.1048 | ||
نویسندگان | ||
Zahra Moravej* 1؛ Saeid Molaei2؛ Alireza Jodaei2 | ||
1Semnan University | ||
2semnan university | ||
تاریخ دریافت: 07 تیر 1399، تاریخ بازنگری: 08 اردیبهشت 1400، تاریخ پذیرش: 21 شهریور 1400 | ||
چکیده | ||
Microgrids are practical views of integration of distributed generations (DGs) into distribution systems. In this regard, utilizing appropriate technologies and accurate recognition of energy generation and storage systems, as well as optimal scheduling for these resources are of the paramount importance in microgrids. Therefore, connection of DG resources and storages to the grid in the form of virtual power plant in order to increase efficiency and owners’ interest has attracted significant attention of researchers and distribution network operators. This research presents a model for optimal day-ahead scheduling of heat-power generation units in a multi-zonal virtual power plant (VPP). This VPP includes a number of combined heat-power generations, distribution network loads, and electrical vehicles with smart charging as well as energy storages. In order to approach the reality of distribution systems, uncertainty related to behavior of electrical vehicles was modeled with Monte-Carlo simulation while uncertainties of generation and electrical/thermal loads were modeled using a probabilistic method. Matlab software and swarm robotics search & rescue (SRSR) has been used as an optimization tool in this paper. The results confirmed the effectiveness of the proposed method. | ||
کلیدواژهها | ||
renewable energy sources؛ energy storage؛ combined heat and power generation؛ virtual power plant؛ load uncertainty؛ electric vehicles | ||
آمار تعداد مشاهده مقاله: 226 تعداد دریافت فایل اصل مقاله: 249 |