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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions

Author

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  • Zhen Wang

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Engineering and Technology Research Center of Urbanization, Wuhan 430074, China)

  • Jiaxuan Wang

    (China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chenxi Lv

    (China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The number of high-rise residential buildings in China has a large base and rapid growth, with huge energy-saving potential. Most of the existing research focuses on the use of renewable energy to reduce energy consumption and optimize energy systems. When optimizing the renewable energy system configuration of residential buildings for solar-air source heat pump systems, the optimization algorithm and the setting of parameter ranges will have an impact on the optimization results. Therefore, to make up for the shortcomings of a single optimization process, this study proposes a joint solution based on simulations and multi-stage multi-objective optimization to improve the energy efficiency of the system and maximize economic benefits. This method was applied to perform energy consumption and economic optimization analyses for typical high-rise residential buildings in four cities in China (Shanghai, Nanjing, Wuhan, Chongqing) characterized by hot summers and cold winters. First, DeST software is used to model and calculate the building load. Then, TRNSYS software is used to establish a system simulation model. Next, the GenOpt program and the Hooke–Jeeves algorithm are used to perform the first stage of optimization with the lowest annual cost value as the objective function. Finally, MATLAB software and the NSGA-II algorithm are used to perform the second stage of optimization with the lowest annual cost value and the highest system energy efficiency ratio as the objective function, respectively. Moreover, the TOPSIS method is used to evaluate and sort the Pareto optimal solution sets to obtain the optimal decision solution. Overall, the two-stage optimization of the solar-air source heat pump system brings multiple benefits and a more significant improvement in overall performance compared to a single-stage optimization. In terms of energy utilization efficiency, the tilt and azimuth adjustments in the first stage allow the collectors to be better oriented towards the sun and to absorb solar energy more fully. This helps to improve the energy utilization efficiency of the system. For the economy of the system, the increase in the collector area and the reduction in the heat production of the air source heat pump in the second stage, as well as the increase in the volume of the water tank, have combined to reduce the operating costs of the system and improve its economy. Results demonstrate that the proposed two-stage optimization significantly improves the overall performance of the solar-air source heat pump system across all four cities, providing a robust framework for sustainable urban residential energy systems. This is a positive aspect for sustainability and environmental friendliness. Taken together, the two-stage optimization improves the performance of the system in a more comprehensive manner compared to the single-stage optimization.

Suggested Citation

  • Zhen Wang & Jiaxuan Wang & Chenxi Lv, 2024. "Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions," Energies, MDPI, vol. 17(24), pages 1-22, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6414-:d:1548097
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    References listed on IDEAS

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