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Bi-level optimization design strategy for compressed air energy storage of a combined cooling, heating, and power system
Journal of Energy Storage ( IF 8.9 ) Pub Date : 2020-07-07 , DOI: 10.1016/j.est.2020.101642
Ke Li , Xingguo Wei , Yi Yan , Chenghui Zhang

Multi-energy flow coupling, along with system design and operation mismatching, is an essential issue that restricts the development of a combined cooling, heating, and power (CCHP) system. To achieve a comprehensive cascade utilization of energy, a new CCHP system based on an internal combustion engine and compressed air energy storage (CAES) is proposed in this study. This system takes advantage of its multi-interface CAES, which not only enhances the correlation between thermoelectric systems but also improves the flexibility of multi-energy joint scheduling of CCHP systems. Considering the coupling relation between the equipment capacity and the operation mode, a bi-level optimization method is proposed for this system. The upper level optimizes the active equipment capacity of the system to reduce economic costs and increase the energy-saving. The lower level regards the daily energy consumption cost and primary energy saving ratio as the target to optimize the system operation mode and the equipment output planning. By applying the bi-level optimization method with direct joint optimization, the overall optimization and matching of the system capacity configuration and the working mode are realized. In addition, the priority relationship between the upper and lower levels of the optimization objectives is considered. Finally, a case study is provided to verify the effectiveness of the bi-level optimization method.



中文翻译:

制冷,供暖和动力系统组合的压缩空气储能的双层优化设计策略

多能流耦合以及系统设计和操作失配是一个至关重要的问题,它限制了冷却,加热和功率联合(CCHP)系统的开发。为了实现能源的综合级联利用,本研究提出了一种基于内燃机和压缩空气储能(CAES)的新型CCHP系统。该系统利用其多接口CAES的优势,不仅增强了热电系统之间的相关性,而且还提高了CCHP系统的多能量联合调度的灵活性。考虑设备容量与运行方式之间的耦合关系,提出了一种针对该系统的双层优化方法。上层优化了系统的活动设备容量,以降低经济成本并增加节能。下级将日常能耗成本和一次节能率作为优化系统运行方式和设备产量计划的目标。通过将双层优化方法与直接联合优化相结合,实现了系统容量配置和工作模式的整体优化与匹配。另外,考虑了优化目标的上层和下层之间的优先级关系。最后,提供了一个案例研究来验证双层优化方法的有效性。实现了系统容量配置和工作模式的整体优化与匹配。另外,考虑了优化目标的上层和下层之间的优先级关系。最后,提供了一个案例研究来验证双层优化方法的有效性。实现了系统容量配置和工作模式的整体优化与匹配。另外,考虑了优化目标的上层和下层之间的优先级关系。最后,提供了一个案例研究来验证双层优化方法的有效性。

更新日期:2020-07-07
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