储能科学与技术

• 储能系统与工程 •    

并网且上网模式下含复合储能CCHP系统能量管理策略优化研究

陈程, 林仕立, 胡安信, 张先勇   

  1. 广东技术师范大学自动化学院，广东省 广州市 510180
  • 收稿日期:2024-06-07 修回日期:2024-06-27

Research on energy management strategy optimization of CCHP system with composite energy storage in grid-connected and power export mode

Cheng CHEN, Shili LIN, Anxin HU, Xianyong ZHANG   

  1. School of Automation, GuangDong Polytechnic Normal University, Guangzhou, 510180, Guangdong, China
  • Received:2024-06-07 Revised:2024-06-27

摘要：

冷热电联供系统(Combined Cooling Heating and Power, CCHP)是工业产业园区、建筑用户能源利用过程实现双碳目标的重要举措。针对CCHP系统产用能不平衡、设备耦合相关、并网且上网模式等影响，本文构建了含电池储能系统和水箱蓄热系统的CCHP系统，并以运行成本和燃料消耗量作为目标建立CCHP系统能量管理策略的多目标优化函数；在此基础上，重点考虑约束条件和拥挤度算子对非支配排序遗传算法(Non-dominated Sorting Genetic Algorithm-II, NSGA-II)搜索性能的影响，并利用改进型NSGA-II算法实现CCHP系统能量管理策略的优化求解。结果表明：在并网且上网模式下，含复合储能CCHP系统相比无储能CCHP系统，夏季典型日可节约日运行成本和燃料消耗分别为0.88%和2.16%；冬季典型日可分别节约27.7%和7.31%，年运行成本和年总能量消耗则分别可减少了11.5%和4.7%，可知基于改进型NSGA-II算法所获得的含复合储能CCHP系统能量管理策略具有较好的能量调控性能。冷热电联供系统(Combined Cooling Heating and Power, CCHP)是工商业、建筑用户能源利用过程实现双碳目标的重要举措。针对CCHP系统产用能不平衡、设备耦合相关、并网且上网模式等影响，本文构建了含电池储能系统和水箱蓄热系统的CCHP系统，并以运行成本和燃料消耗量作为目标建立CCHP系统能量管理策略的多目标优化函数；在此基础上，重点考虑约束条件和拥挤度算子对非支配排序遗传算法(Non-dominated Sorting Genetic Algorithm-II, NSGA-II)的影响，并利用改进型NSGA-II算法实现CCHP系统能量管理策略的优化求解。结果表明：在并网且上网模式下，含复合储能CCHP系统相比无储能CCHP系统，基于改进型NSGA-II算法所获得的能量管理策略年运行成本可减少11.5%，年总能量消耗可减少4.7%，具有较好的能量调控性能。

关键词: 冷热电联供, 并网且上网, 复合储能, 改进型NSGA-II算法

Abstract:

Combined Cooling Heating and Power (CCHP) is an important measure for industrial parks and building users to achieve dual carbon goals in their energy utilization process. Aiming at the impact of energy imbalance, equipment coupling, grid connection and online access mode in CCHP system, this paper constructs a CCHP system with battery energy storage system and water tank thermal storage system, and establishes a multi-objective optimization function of CCHP system energy management strategy with operating cost and fuel consumption as the target; on this basis, the influence of constraints and congestion operator on the search performance of non-dominated sorting genetic algorithm (NSGA-II) is considered, and the improved NSGA-II algorithm is used to realize the optimization solution of CCHP system energy management strategy. The results show that in the grid-connected and online mode, the CCHP system with composite energy storage can save 0.88% and 2.16% of daily operating cost and fuel consumption respectively on typical days in summer compared with the CCHP system without energy storage; it can save 27.7% and 7.31% respectively on typical days in winter, and the annual operating cost and annual total energy consumption can be reduced by 11.5% and 4.7% respectively. It can be seen that the energy management strategy of the CCHP system with composite energy storage obtained based on the improved NSGA-II algorithm has good energy regulation performance.Combined Cooling Heating and Power (CCHP) is an important measure for achieving dual carbon goals in the energy utilization process of industrial, commercial and building users. Aiming at the influence of energy imbalance, equipment coupling, grid-connected and online mode of CCHP system, this paper constructs a CCHP system with battery energy storage system and water tank thermal storage system, and establishes a multi-objective optimization function of CCHP system energy management strategy with operating cost and fuel consumption as the target; on this basis, the influence of constraints and congestion operator on non-dominated sorting genetic algorithm (NSGA-II) is considered, and the improved NSGA-II algorithm is used to realize the optimization solution of CCHP system energy management strategy. The results show that under the grid-connected and power export, the annual operating cost of the energy management strategy of CCHP system with composite energy storage can be reduced by 11.5%, and the annual total energy consumption can be reduced by 4.7%, which has better energy management performance.

Key words: combined cooling, heating and power, grid connection and power export, composite energy storage, improved NSGA-II algorithm

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