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Incorporating deep learning of load predictions to enhance the optimal active energy management of combined cooling, heating and power system

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  • Zhou, Yuan
  • Wang, Jiangjiang
  • Liu, Yi
  • Yan, Rujing
  • Ma, Yanpeng

Abstract

The energy management of combined cooling, heating and power (CCHP) system is essential for simultaneously improving its energy and economic performances. However, the conventional operation strategies are mainly logical control, which passively adapts to users’ demands. This paper proposes an optimal economic energy dispatch model of the CCHP system incorporating deep learning of load predictions to fulfill active control strategy in dynamic programming. A cross linear optimization method with a half update strategy of component efficiencies is developed to solve and calculate the variable component efficiencies in the CCHP system. Compared to the genetic algorithm, the proposed method achieves better results and the convergence time is reduced by 93%. The model predictive control of the CCHP system in load predictions of an artificial neural network is combined to the dynamic programming to realize the active energy dispatch strategy. The effects of short-term prediction and long-term prediction on forecast performances and operation costs are discussed. The case study demonstrates that the ideal prediction horizon of 8 h is recommended to fully realize the active functions of energy storage devices in the CCHP system. The proposed active strategy with model predictive control reduces the operational cost by 3.66% compared to the passive control strategy.

Suggested Citation

  • Zhou, Yuan & Wang, Jiangjiang & Liu, Yi & Yan, Rujing & Ma, Yanpeng, 2021. "Incorporating deep learning of load predictions to enhance the optimal active energy management of combined cooling, heating and power system," Energy, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:energy:v:233:y:2021:i:c:s0360544221013827
    DOI: 10.1016/j.energy.2021.121134
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    as
    1. Zhou, Yuekuan & Zheng, Siqian, 2020. "Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities," Applied Energy, Elsevier, vol. 262(C).
    2. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2020. "Building thermal load prediction through shallow machine learning and deep learning," Applied Energy, Elsevier, vol. 263(C).
    3. Nelson, James R. & Johnson, Nathan G., 2020. "Model predictive control of microgrids for real-time ancillary service market participation," Applied Energy, Elsevier, vol. 269(C).
    4. Bartolucci, Lorenzo & Cordiner, Stefano & Mulone, Vincenzo & Santarelli, Marina, 2019. "Hybrid renewable energy systems: Influence of short term forecasting on model predictive control performance," Energy, Elsevier, vol. 172(C), pages 997-1004.
    5. Wang, Jian Qi & Du, Yu & Wang, Jing, 2020. "LSTM based long-term energy consumption prediction with periodicity," Energy, Elsevier, vol. 197(C).
    6. Kim, Min Jae & Kim, Tong Seop & Flores, Robert J. & Brouwer, Jack, 2020. "Neural-network-based optimization for economic dispatch of combined heat and power systems," Applied Energy, Elsevier, vol. 265(C).
    7. Ghersi, Djamal Eddine & Amoura, Meriem & Loubar, Khaled & Desideri, Umberto & Tazerout, Mohand, 2021. "Multi-objective optimization of CCHP system with hybrid chiller under new electric load following operation strategy," Energy, Elsevier, vol. 219(C).
    8. Chaudhary, Priyanka & Rizwan, M., 2018. "Energy management supporting high penetration of solar photovoltaic generation for smart grid using solar forecasts and pumped hydro storage system," Renewable Energy, Elsevier, vol. 118(C), pages 928-946.
    9. Li, Longxi & Yu, Shiwei & Mu, Hailin & Li, Huanan, 2018. "Optimization and evaluation of CCHP systems considering incentive policies under different operation strategies," Energy, Elsevier, vol. 162(C), pages 825-840.
    10. Song, Zhihui & Liu, Tao & Lin, Qizhao, 2020. "Multi-objective optimization of a solar hybrid CCHP system based on different operation modes," Energy, Elsevier, vol. 206(C).
    11. Wang, Jiangjiang & Han, Zepeng & Guan, Zhimin, 2020. "Hybrid solar-assisted combined cooling, heating, and power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    12. Rullo, P. & Braccia, L. & Luppi, P. & Zumoffen, D. & Feroldi, D., 2019. "Integration of sizing and energy management based on economic predictive control for standalone hybrid renewable energy systems," Renewable Energy, Elsevier, vol. 140(C), pages 436-451.
    13. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
    14. Wang, Jiangjiang & Yang, Ying & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Life cycle assessment (LCA) optimization of solar-assisted hybrid CCHP system," Applied Energy, Elsevier, vol. 146(C), pages 38-52.
    15. Tarragona, Joan & Fernández, Cèsar & de Gracia, Alvaro, 2020. "Model predictive control applied to a heating system with PV panels and thermal energy storage," Energy, Elsevier, vol. 197(C).
    16. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    17. Wang, Xuan & Shu, Gequn & Tian, Hua & Wang, Rui & Cai, Jinwen, 2020. "Operation performance comparison of CCHP systems with cascade waste heat recovery systems by simulation and operation optimisation," Energy, Elsevier, vol. 206(C).
    18. e Silva, Danilo P. & Félix Salles, José L. & Fardin, Jussara F. & Rocha Pereira, Maxsuel M., 2020. "Management of an island and grid-connected microgrid using hybrid economic model predictive control with weather data," Applied Energy, Elsevier, vol. 278(C).
    Full references (including those not matched with items on IDEAS)

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