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Open Access

Time-efficient Strategic Power Dispatch for District Cooling Systems Considering Evolution of Cooling Load Uncertainties

Ge Chen, Biao Yan, Hongcai Zhang( ), Dongdong Zhang, Yonghua Song
State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macau, Macau 999078, China
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Abstract

District cooling system (DCS) provides centralized chilled water to multiple buildings for air conditioning with high energy-efficiency and operational flexibility. It is one of the most popular cooling systems for large buildings in modern cities and an important demand response source for power systems. In order to enhance its energy efficiency and utilize its flexibility, strategic operation is indispensable. However, finding an optimal policy for DCS operation is a challenging task because of the high inter-connectivity among components. The evolution of cooling load uncertainties further increases the difficulties. This paper addresses the aforementioned challenges by proposing a novel optimal power dispatch model for DCS. The proposed model optimizes water temperature and mass flow rates simultaneously to improve the energy efficiency as much as possible. It also explicitly describes the uncertainty accumulation and propagation. Chance-constrained programming is employed to guarantee the cooling service quality. We further propose a more time-efficient formulation to overcome the computational intractability caused by the non-smooth and non-convex constraints. Numerical experiments based on a real DCS confirm that a time-efficient formulation can save about half of solution time with negligible cost increase.

Keywords

HVACDistrict cooling systemcooling power dispatchdemand-side flexibilitychance-constrained programming

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CSEE Journal of Power and Energy Systems
Volume 8 Issue 5,
September 2022
Pages 1457-1467
DOI: 10.17775/CSEEJPES.2020.06800
Cite this article:
Chen G, Yan B, Zhang H, et al. Time-efficient Strategic Power Dispatch for District Cooling Systems Considering Evolution of Cooling Load Uncertainties. CSEE Journal of Power and Energy Systems, 2022, 8(5): 1457-1467. https://doi.org/10.17775/CSEEJPES.2020.06800

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Received: 12 December 2020
Revised: 21 February 2021
Accepted: 27 April 2021
Published: 10 September 2021
© 2020 CSEE
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