Collaborative Energy Management Optimization Toward a Green Energy Local Area Network
Publication in refereed journal


摘要Rapid economic development has been observed worldwide, which has caused environmental problems to worsen. Thus, the Energy Internet (EI), which accesses renewable energy and provides high-quality power services, has recently become a hot issue. As a subnet of the EI, an energy local area network (ELAN) consists of renewable power generation equipment, controllable distributed power generation equipment, storage systems, electric vehicles, and a large number of loads. Energy management is required for economic, environmental, and safety considerations. This paper proposes an energy management optimization model that addresses ELAN operations and includes pollution treatment fees; this model provides intelligent control of the charging and discharging of plug-in hybrid electric vehicles (PHEVs). This model achieves a nonlinear energy management optimization for an ELAN. To promote optimal performance, an improved comprehensive learning particle swarm optimization (CLPSO) algorithm is presented; it combines Tabu Search (TS) and CLPSO to avoid local optima. To verify the performance of our model, two experimental scenarios are built. The simulation results show that our energy management optimization model fulfills the optimal allocation of energy and that the PHEV intelligent charging/discharging strategy promotes economic benefits for the network.
著者Jin Qi, Chunyuan Lai, Bin Xu, Yanfei Sun, Kwong-Sak Leung
期刊名稱IEEE Transactions on Industrial Informatics
頁次5410 - 5418
關鍵詞Pollution, Energy management, Optimization, Job shop scheduling, Green products, Load modeling, Economics

上次更新時間 2020-25-10 於 03:12