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A novel approach for multi-objective cost-peak optimization for demand response of a residential area in smart grids

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  • Haider, Haider Tarish
  • Muhsen, Dhiaa Halboot
  • Al-Nidawi, Yaarob Mahjoob
  • Khatib, Tamer
  • See, Ong Hang

Abstract

In this paper, an optimal load scheduling model of household appliances for smart home energy management considering demand response for different pricing schemes is proposed. Henry gas solubility optimization method is used to obtain optimal load scheduling solutions, and then these solutions are sorted using VIKOR multi-criteria decision making method. Multiple pricing schemes have been used such adaptive consumption level pricing scheme and time of use. The use of multiple pricing scheme is to compare the results of customers cost saving obtained. The results show, the proposed method a saves more than 80% and 76% of end-user energy cost for time of use and adaptive consumption level pricing scheme respectively. Meanwhile, the peak load of end-user is reduced by 55% for the baseline operation. The outcomes of this paper are also compared with other works in the literature in order to validate the proposed method. It is concluded in this research that the proposed method provides essential saving for energy cost and demand's peak power as well as keeps acceptable range of customer inconvenience level.

Suggested Citation

  • Haider, Haider Tarish & Muhsen, Dhiaa Halboot & Al-Nidawi, Yaarob Mahjoob & Khatib, Tamer & See, Ong Hang, 2022. "A novel approach for multi-objective cost-peak optimization for demand response of a residential area in smart grids," Energy, Elsevier, vol. 254(PB).
  • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s0360544222012634
    DOI: 10.1016/j.energy.2022.124360
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    References listed on IDEAS

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    Cited by:

    1. Kanakaraj Parangusam & Ramesh Lekshmana & Tomas Gono & Radomir Gono, 2023. "Evolution of a Summer Peak Intelligent Controller (SPIC) for Residential Distribution Networks," Energies, MDPI, vol. 16(18), pages 1-18, September.
    2. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    3. Mota, Bruno & Faria, Pedro & Vale, Zita, 2022. "Residential load shifting in demand response events for bill reduction using a genetic algorithm," Energy, Elsevier, vol. 260(C).
    4. Liu, Youquan & Li, Huazhen & Zhu, Jiawei & Lin, Yishuai & Lei, Weidong, 2023. "Multi-objective optimal scheduling of household appliances for demand side management using a hybrid heuristic algorithm," Energy, Elsevier, vol. 262(PA).

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