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Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization

Author

Listed:
  • Yang, Xiaohui
  • Wang, Xiaopeng
  • Deng, Yeheng
  • Mei, Linghao
  • Deng, Fuwei
  • Zhang, Zhonglian

Abstract

Integrated energy system (IES) plays an important role in realizing efficient use of clean energy. Considering the influence of various uncertainties, an IES scheduling model based on non-complete interval multi-objective fuzzy optimization is proposed to improve the operation efficiency of IES and to reduce the external impacts of IES. Firstly, the uncertainties of renewable energy, load and demand response are described by interval numbers, and a multi-objective optimization model considering satisfaction with electricity is proposed to guarantee the reduction of user experience loss in optimizing IES electricity load. Secondly, by analyzing the shortcomings of the traditional interval optimization methods and improving them, a non-complete interval multi-objective fuzzy optimization model is proposed in the day-ahead scheduling stage, which improves the operational efficiency of IES. In addition, an optimum interval cross section search model is proposed in the real-time scheduling stage to further improve the practicality of the proposed interval optimization model. The simulation results under typical day in summer show that compared with the traditional optimization model, the proposed model improves the economy, environmental protection, reliability and renewable energy consumption rate of IES by 2.51%, 13.07%, 5.03% and 8.17% respectively, which proves the effectiveness of the proposed model in optimization performance.

Suggested Citation

  • Yang, Xiaohui & Wang, Xiaopeng & Deng, Yeheng & Mei, Linghao & Deng, Fuwei & Zhang, Zhonglian, 2023. "Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization," Renewable Energy, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:renene:v:218:y:2023:i:c:s0960148123012041
    DOI: 10.1016/j.renene.2023.119289
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