Space-cooling is dominating building energy use in warm regions. Integrating on-site PV generation with cooling systems is a potential building-scale decarbonization solution. However, designing the system to ensure cost-effectiveness and reliability is challenging since it requires solving a highly non-linear design and dispatch problem. This paper proposes a solution strategy to the design problem of an integrated multi-chillers system with PV, and ice thermal and battery storage to reduce emissions and annual system costs. The proposed strategy adopts a bi-level optimization approach eliminating the need for simplistic models. The upper level employs particle swarm optimization to determine storage and chillers' capacities and types, while the lower level solves the dispatch problem using mixed-integer linear programming. To validate the proposed strategy and decarbonization solution, the model was applied to a generic residential building in Qatar and was exposed to a varying range of carbon pricing. The results highlight the potential for deep decarbonization in regions with abundant solar resources and high cooling needs. In Qatar, the model suggests a moderate carbon pricing range of $75–125/ton of CO for deep decarbonization. The developed model demanded reasonable computational resources with an execution time of less than 1 h and exhibited stability with consistent convergence.

中文翻译：

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设计具有热能和电池存储功能的冷却系统，以增强与现场光伏的集成

空间制冷在温暖地区的建筑能源使用中占据主导地位。将现场光伏发电与冷却系统集成是一种潜在的建筑规模脱碳解决方案。然而，设计系统以确保成本效益和可靠性具有挑战性，因为它需要解决高度非线性的设计和调度问题。本文针对带有光伏、冰热和电池存储的集成多冷水机组系统的设计问题提出了一种解决策略，以减少排放和年度系统成本。所提出的策略采用双层优化方法，消除了对简单模型的需要。上层采用粒子群优化来确定存储和冷却器的容量和类型，而下层使用混合整数线性规划解决调度问题。为了验证所提出的策略和脱碳解决方案，该模型被应用于卡塔尔的一栋普通住宅建筑，并接受了不同范围的碳定价。研究结果凸显了太阳能资源丰富和冷却需求高的地区深度脱碳的潜力。在卡塔尔，该模型建议深度脱碳的碳定价范围为每吨二氧化碳 75-125 美元。所开发的模型需要合理的计算资源，执行时间小于 1 小时，并且表现出一致收敛的稳定性。