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Evaluation of Photovoltaic Consumption Potential of Residential Temperature-Control Load Based on ANP-Fuzzy and Research on Optimal Incentive Strategy

Author

Listed:
  • Siyue Lu

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Teng Li

    (Department of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Xuefeng Yan

    (Department of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Shaobing Yang

    (Department of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Temperature-control loads, such as residential air conditioners (ACs) and electric water heaters (EWHs), have become important demand response resources in the power system. However, due to the impact of various factors on users’ response behavior, it has been difficult for power grid operators to accurately evaluate the response potential under complex factor relationships to derive optimal incentive strategy. Therefore, it cannot achieve a win-win economic benefit between the grid and users. In this paper, a method combining Analytic Network Process (ANP) and Fuzzy logical inference is proposed to predict the user’s willingness firstly by taking residential AC load as an example. The weight of each factor affecting users’ willingness is analyzed, and main factors are selected as inputs of fuzzy logic inference to derive the willingness of the resident to actively regulate the AC. Then, this method is applied in evaluating the response potential of certain residential area in Beijing according to the survey. By further considering users’ house size and the sacrificed comfort temperature under the incentive strategy, the power potential curve of the AC load under different incentives is obtained by using the first-order equivalent thermal parameter (ETP) model and the regulation willingness. Finally, with the objective of maximizing the consumption of the photovoltaic (PV) power, the optimal operation is achieved through the coordinated regulation of residential ACs and EWHs based on the potential curve, and the corresponding optimal incentive strategy for the flexible temperature-control loads is obtained. Simulation results show that the optimal incentive strategy proposed not only increases the PV consumption ratio to 98.35% with an increase of 24.71%, but also maximizes the economic benefits of both sides of the power grid and users. This method of deriving incentive strategy can be used as a reference for grid companies to formulate the incentive strategy to realize optimal operation, such as the maximum new energy consumption.

Suggested Citation

  • Siyue Lu & Teng Li & Xuefeng Yan & Shaobing Yang, 2022. "Evaluation of Photovoltaic Consumption Potential of Residential Temperature-Control Load Based on ANP-Fuzzy and Research on Optimal Incentive Strategy," Energies, MDPI, vol. 15(22), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8640-:d:976118
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    References listed on IDEAS

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    1. Ryan S. Montrose & John F. Gardner & Aykut C. Satici, 2021. "Centralized and Decentralized Optimal Control of Variable Speed Heat Pumps," Energies, MDPI, vol. 14(13), pages 1-18, July.
    2. Hamid Iftikhar & Eduardo Sarquis & P. J. Costa Branco, 2021. "Why Can Simple Operation and Maintenance (O&M) Practices in Large-Scale Grid-Connected PV Power Plants Play a Key Role in Improving Its Energy Output?," Energies, MDPI, vol. 14(13), pages 1-29, June.
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    Cited by:

    1. Siyue Lu & Baoqun Zhang & Longfei Ma & Hui Xu & Yuantong Li & Shaobing Yang, 2023. "Economic Load-Reduction Strategy of Central Air Conditioning Based on Convolutional Neural Network and Pre-Cooling," Energies, MDPI, vol. 16(13), pages 1-22, June.
    2. Bartosz Radomski & Tomasz Mróz, 2023. "Application of the Hybrid MCDM Method for Energy Modernisation of an Existing Public Building—A Case Study," Energies, MDPI, vol. 16(8), pages 1-18, April.

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