文献类型：期刊文献

英文题名：Stochastic optimization for energy economics and renewable sources management: A case study of solar energy in digital twin

作者：Gao, Jiaxi[1];Huang, Haiyan[1,2]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Smart Mfg Energy & Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2023

卷号：262

外文期刊名：SOLAR ENERGY

收录：;EI(收录号：20233214490699);WOS:【SCI-EXPANDED(收录号:WOS:001047308800001)】；

语种：英文

外文关键词：Stochastic optimization; Moth flame optimization algorithm; Microgrid; Energy management; Optimal power flow; Solar digital twin

摘要：As power system might be damaged and even shut down due to the high uncertainty effects, they are always challenged by the high load variations. This study proposes a novel technique for managing power in microgrids (MGs) that have stochastic loads in the presence of high penetration of renewable energy sources. It is likely that the security of the users will be violated as a result of centralized optimization techniques that require considerable computing power. Conversely, in distributed methods, each load and generation are presumed to be linked to a single bus, thereby neglecting the electrical grid and its limitations. Due to this, the suggested distributed energy management strategy (EMS) decomposes the optimization problem into two levels, involving the MG centralized controller, local controllers, distribution network, and related restrictions. Because it is impossible to predict the loads precisely, the loads are regarded as stochastic variables which are modeled using probabilistic approach. The moth flame optimization algorithm is used to solve the optimization problem. A distributed EMS has been developed that integrates solar/photovoltaic (PV) units, wind turbines, diesel generators, and batteries in a digital twin area. Based on the simulations, the suggested distributed EMS is shown to be efficient and useful for the practical studies.