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Demand response management of community integrated energy system: A multi-energy retail package perspective

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  • Gao, Hongjun
  • Zhao, Yinbo
  • He, Shuaijia
  • Liu, Junyong

Abstract

The community integrated energy system (CIES) is becoming an effective way to improve the energy utilization efficiency and reduce the carbon emission. Demand response in a CIES may be more challenge with the participation of multi-energy consumers. In this paper, we propose a novel multi-energy retail package mechanism, which provides a new perspective for demand response management in CIES. Firstly, we describe the operation rules of the energy retail package mechanism proposed in this paper, aiming at promoting the electricity and gas loads peak shaving and the electricity load valley filling in electricity-gas CIES. Secondly, a bi-level optimization model is built to optimize a set of packages with different response requirements and discounts for different consumers. The lower model adopts Multinomial Logit theory to simulate the consumer's package selecting and energy use behavior when facing different energy retail packages while the upper model optimizes package parameters with the objective of maximizing CIES operator increased benefit. Finally, the effectiveness of the energy retail package mechanism designed in this paper for demand response management is verified through example analysis.

Suggested Citation

  • Gao, Hongjun & Zhao, Yinbo & He, Shuaijia & Liu, Junyong, 2023. "Demand response management of community integrated energy system: A multi-energy retail package perspective," Applied Energy, Elsevier, vol. 330(PA).
    • Handle: RePEc:eee:appene:v:330:y:2023:i:pa:s0306261922015355
    DOI: 10.1016/j.apenergy.2022.120278
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    1. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.

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