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Customer satisfaction based reliability evaluation of active distribution networks

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  • Li, Gengfeng
  • Bie, Zhaohong
  • Xie, Haipeng
  • Lin, Yanling

Abstract

Reliability evaluation of active distribution networks (ADNs) considering customer satisfaction is studied in this paper. Operation optimization model of ADNs is established, which aims to maximize the operation benefit of ADNs using demand response. However, according to optimization decisions, customers may have to change their electricity consumption habit, which affects customer satisfaction and the reliability of customers and ADNs. Two customer satisfaction indices are defined therefore as constraints in the operation optimization to quantify these effects. By a Sequential Monte Carlo (SMC) simulation, the optimization processes is innovatively integrated into the reliability evaluation, and thus the impacts of customer satisfaction constraints are incorporated in reliability evaluation. Further, four new reliability indices are defined in this paper to visibly reflect their impacts. The presented models and methods are validated by extensive studies conducted on a standard test system. Evaluation results accurately quantify the impacts of customer satisfaction constraints on load profiles, reliability and economic performance of ADNs. Conclusions drawn from evaluation results can provide helpful insights for distribution system operators (DSOs) to effectively improve the reliability and operation economy of ADNs using demand resources.

Suggested Citation

  • Li, Gengfeng & Bie, Zhaohong & Xie, Haipeng & Lin, Yanling, 2016. "Customer satisfaction based reliability evaluation of active distribution networks," Applied Energy, Elsevier, vol. 162(C), pages 1571-1578.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1571-1578
    DOI: 10.1016/j.apenergy.2015.02.084
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    Cited by:

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    5. Xiao Han & Ming Zhou & Gengyin Li & Kwang Y. Lee, 2017. "Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium," Energies, MDPI, vol. 10(12), pages 1-17, December.
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    9. Zeng, Bo & Wei, Xuan & Zhao, Dongbo & Singh, Chanan & Zhang, Jianhua, 2018. "Hybrid probabilistic-possibilistic approach for capacity credit evaluation of demand response considering both exogenous and endogenous uncertainties," Applied Energy, Elsevier, vol. 229(C), pages 186-200.

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