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Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads

Author

Listed:
  • Xiao Gong

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China)

  • Fan Li

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China)

  • Bo Sun

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China)

  • Dong Liu

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China)

Abstract

Combined cooling, heating, and power (CCHP) systems are a promising energy-efficient and environment-friendly technology. However, their performance in terms of energy, economy, and environment factors depends on the operation strategy. This paper proposes a multi-energy complementary CCHP system integrating renewable energy sources and schedulable heating, cooling, and electrical loads. The system uses schedulable loads instead of energy storage, at the same time, a collaborative optimization scheduling strategy, which integrates energy supply and load demand into a unified optimization framework to achieve the optimal system performance, is presented. Schedulable cooling and heating load models are formulated using the relationship between indoor and outdoor house temperatures. A genetic algorithm is employed to optimize the overall performance of energy, economy, and environment factors and obtain optimal day-ahead scheduling scheme. Case studies are conducted to verify the efficiency of the proposed method. Compared with a system involving thermal energy storage and demand response (DR), the proposed method exhibits a higher primary energy saving rate, greenhouse gas emission reduction rate, and operation costs saving rate of 7.44%, 6.59%, and 4.73%, respectively, for a typical summer day, thereby demonstrating the feasibility and superiority of the proposed approach.

Suggested Citation

  • Xiao Gong & Fan Li & Bo Sun & Dong Liu, 2020. "Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads," Energies, MDPI, vol. 13(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:918-:d:322215
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    References listed on IDEAS

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    6. Wenqiang Guo & Xinyi Xu, 2022. "Comprehensive Energy Demand Response Optimization Dispatch Method Based on Carbon Trading," Energies, MDPI, vol. 15(9), pages 1-17, April.

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