Energy production and consumption are the largest source of carbon dioxide emissions. Given the global energy revolution, planning a high-carbon and clean park-integrated energy system (IES) is crucial. This paper addresses this by constructing a system carbon emission flow model based on power carbon flow density, establishing a demand response revenue model according to relevant policies, and creating a multi-energy system coupling model including cogeneration units, photovoltaic, hydrogen energy storage, and other devices. The paper also establishes an objective function of system cost optimization, carbon emission optimization, and economic and environmental benefit trade-off optimization under the constraints of system electricity, heat power balance, and state of charge of the hydrogen storage tank. Finally, the CPLEX tool of YALMIP is used to solve the problem. The influence of demand response, carbon flow and hydrogen energy storage on capacity configuration optimization is analyzed, and the optimal configuration scheme is proposed to ensure the system’s economy and reduce carbon emissions.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Research on Capacity Optimization Configuration of Integrated Energy System in Smart Park Considering Carbon Flow and Demand Response

  • Yuqi Wang,
  • Ji Ke,
  • Yue Hao,
  • Yu Miao,
  • Yaohua Yin,
  • Xueshu Xing

摘要

Energy production and consumption are the largest source of carbon dioxide emissions. Given the global energy revolution, planning a high-carbon and clean park-integrated energy system (IES) is crucial. This paper addresses this by constructing a system carbon emission flow model based on power carbon flow density, establishing a demand response revenue model according to relevant policies, and creating a multi-energy system coupling model including cogeneration units, photovoltaic, hydrogen energy storage, and other devices. The paper also establishes an objective function of system cost optimization, carbon emission optimization, and economic and environmental benefit trade-off optimization under the constraints of system electricity, heat power balance, and state of charge of the hydrogen storage tank. Finally, the CPLEX tool of YALMIP is used to solve the problem. The influence of demand response, carbon flow and hydrogen energy storage on capacity configuration optimization is analyzed, and the optimal configuration scheme is proposed to ensure the system’s economy and reduce carbon emissions.