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  • 标题:The Capacity Optimization of Wind-Photovoltaic-Thermal Energy Storage Hybrid Power System
  • 本地全文:下载
  • 作者:Jingli Li ; Wannian Qi ; Jun Yang
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2019
  • 卷号:118
  • 页码:1-6
  • DOI:10.1051/e3sconf/201911802054
  • 出版社:EDP Sciences
  • 摘要:This paper proposes a Wind-Photovoltaic-Thermal Energy Storage hybrid power system with an electric heater. The proposed system consists of wind subsystem, photovoltaic subsystem, electric heater, thermal energy storage and steam turbine unit. The electric heater is used to convert the redundant electricity from wind or photovoltaic subsystem into heat, which is stored in thermal energy storage. When the system output is less than the load demand, thermal energy storage system releases heat to generate electricity. In this paper, the optimal objective is to minimize the levelized cost of energy and maximize the utilization rates of renewable energy and transmission channel. The fitness function is compiled according to the scheduling strategy, and the capacity optimization problem is solved by particle swarm optimization algorithm in MATLAB. The case analysis show that the proposed system can effectively increase the utilization rate of renewable energy and transmission channel.
  • 其他摘要:This paper proposes a Wind-Photovoltaic-Thermal Energy Storage hybrid power system with an electric heater. The proposed system consists of wind subsystem, photovoltaic subsystem, electric heater, thermal energy storage and steam turbine unit. The electric heater is used to convert the redundant electricity from wind or photovoltaic subsystem into heat, which is stored in thermal energy storage. When the system output is less than the load demand, thermal energy storage system releases heat to generate electricity. In this paper, the optimal objective is to minimize the levelized cost of energy and maximize the utilization rates of renewable energy and transmission channel. The fitness function is compiled according to the scheduling strategy, and the capacity optimization problem is solved by particle swarm optimization algorithm in MATLAB. The case analysis show that the proposed system can effectively increase the utilization rate of renewable energy and transmission channel.
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