Abstract
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 CO2 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.
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