文献类型：期刊文献

英文题名：Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization

作者：Yang, Wenjun[1];Guo, Jia[2];Vartosh, Aris[3]

通讯作者：Yang, WJ[1]

机构：[1]Henan Univ Econ & Law, Sch E Commerce & Logist Management, Zhengzhou 450000, Henan, Peoples R China;[2]Zhengzhou Sias Univ, Dept Elect & Informat, Zhengzhou 450000, Henan, Peoples R China;[3]Arian Co, EED, Yerevan, Armenia

第一机构：河南财经政法大学电子商务与物流管理学院

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Sch E Commerce & Logist Management, Zhengzhou 450000, Henan, Peoples R China.|[104849]河南财经政法大学电子商务与物流管理学院;[10484]河南财经政法大学;

年份：2022

卷号：311

外文期刊名：APPLIED ENERGY

收录：;EI(收录号：20220711630128);Scopus(收录号：2-s2.0-85124411241);WOS:【SCI-EXPANDED(收录号:WOS:000772051400007)】；

语种：英文

外文关键词：Group optimization; Demand management; Electric vehicles; Hybrid energy system; Electricity market

摘要：The present paper aims to present a comprehensive multi-objective optimization model for energy management in local multi-energy systems in the presence of plug-in electric vehicles (PEVs), seeking to achieve the maximized profit of the operators of the local multi-energy systems and minimized CO2 emission at the same time. This problem involves technology transfer in local multi-energy systems and finding the PEVs charge/discharge optimization strategies in order to maximize the operators' profit and, in the meantime, reduce the CO2 emission. It can be solved by formulating a multi-purpose objective and can be dealt with by formulating a multi objective programming problem through accurate modeling of mutual dependencies between the energy carriers. To solve this problem, a Modified Group Search Optimization (MGSO) algorithm is used based on the decomposition system. By the proposed structure, the local and global search is improved significantly. As indicated by the results of the effectiveness test of the optimization framework for maximizing the operator's profit and, meanwhile, reducing the CO2 emission, this objective is achievable through optimal coordination of multiple energy carriers in local multi-energy systems and effective management of the flexibility collected at both supply and demand sides.The simulation has been investigated in different scenarios. Obtained numerical analysis shows that the base case signifies the best case in terms of maximization of the local multi-energy systems operator's profit through the optimized charging and discharging approaches of the PEVs. Also, in all scenarios, the profit of operator reductions by 5%-15% as compared with the base case. On the other hand, the best case scenario from an environmental point of view is provided by a scenario categorized with electric vehicles excluding under environmental optimization. In fact, CO2 emissions are reduced 7% compared to the emissions of base case.