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Peak load management based on hybrid power generation and demand response

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  • Yu, Dongmin
  • liu, Huanan
  • Bresser, Charis

Abstract

Industrial customers of electric energy can obtain the energy from different sources such as electricity market, reciprocal agreements, small-scale turbines, batteries, wind generation, solar panel generation and the demand response program (DeRP) participants. Due to volatilities in electricity market, the overall price of energy provision for industrial consumers cannot be determined. In this work, a new optimization approach is developed for modeling the uncertainty of pool yield rate. Also, a new operation method of risk-averse proposed and contrasted with risk-neutral method is suggested. In this process, DeRP is utilized in order to decrease the overall price of electric energy for industrial customers. To show the efficiency of proposed method, fare comparison is presented between the deterministic approach and proposed optimization model with and without considering the DeRP. Obtained results show that, implementing the DeRP, the energy provision costs are reduced using risk-neutral and risk-averse approaches, respectively.

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  • Yu, Dongmin & liu, Huanan & Bresser, Charis, 2018. "Peak load management based on hybrid power generation and demand response," Energy, Elsevier, vol. 163(C), pages 969-985.
    • Handle: RePEc:eee:energy:v:163:y:2018:i:c:p:969-985
    DOI: 10.1016/j.energy.2018.08.177
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    2. Roldán-Blay, Carlos & Escrivá-Escrivá, Guillermo & Roldán-Porta, Carlos, 2019. "Improving the benefits of demand response participation in facilities with distributed energy resources," Energy, Elsevier, vol. 169(C), pages 710-718.
    3. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2019. "Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations," Applied Energy, Elsevier, vol. 237(C), pages 695-707.
    4. Luo, X.J. & Fong, K.F., 2019. "Development of integrated demand and supply side management strategy of multi-energy system for residential building application," Applied Energy, Elsevier, vol. 242(C), pages 570-587.
    5. Tian, Xiaoge & Chen, Weiming & Hu, Jinglu, 2023. "Game-theoretic modeling of power supply chain coordination under demand variation in China: A case study of Guangdong Province," Energy, Elsevier, vol. 262(PA).
    6. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).

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