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Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand

Author

Listed:
  • Wanlei Xue

    (Economic & Technological Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China)

  • Xin Zhao

    (Economic & Technological Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China)

  • Yan Li

    (Economic & Technological Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China)

  • Ying Mu

    (Economic & Technological Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China)

  • Haisheng Tan

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yixin Jia

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Xuejie Wang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Huiru Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yihang Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model.

Suggested Citation

  • Wanlei Xue & Xin Zhao & Yan Li & Ying Mu & Haisheng Tan & Yixin Jia & Xuejie Wang & Huiru Zhao & Yihang Zhao, 2023. "Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand," Energies, MDPI, vol. 16(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1625-:d:1059742
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    References listed on IDEAS

    as
    1. Muhammad Babar Rasheed & Nadeem Javaid & Ashfaq Ahmad & Mohsin Jamil & Zahoor Ali Khan & Umar Qasim & Nabil Alrajeh, 2016. "Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing," Energies, MDPI, vol. 9(8), pages 1-25, July.
    2. Liang, Yong-Liang & Guo, Chen-Xian & Li, Ke-Jun & Li, Ming-Yang, 2021. "Economic scheduling of compressed natural gas main station considering critical peak pricing," Applied Energy, Elsevier, vol. 292(C).
    3. Zhao, Yihang & Zhou, Zhenxi & Zhang, Kaiwen & Huo, Yaotong & Sun, Dong & Zhao, Huiru & Sun, Jingqi & Guo, Sen, 2023. "Research on spillover effect between carbon market and electricity market: Evidence from Northern Europe," Energy, Elsevier, vol. 263(PF).
    4. Feihu Hu & Xuan Feng & Hui Cao, 2018. "A Short-Term Decision Model for Electricity Retailers: Electricity Procurement and Time-of-Use Pricing," Energies, MDPI, vol. 11(12), pages 1-18, November.
    5. Rama Curiel, José Adrián & Thakur, Jagruti, 2022. "A novel approach for Direct Load Control of residential air conditioners for Demand Side Management in developing regions," Energy, Elsevier, vol. 258(C).
    6. Yang, Hufang & Jiang, Ping & Wang, Ying & Li, Hongmin, 2022. "A fuzzy intelligent forecasting system based on combined fuzzification strategy and improved optimization algorithm for renewable energy power generation," Applied Energy, Elsevier, vol. 325(C).
    7. Charwand, Mansour & Gitizadeh, Mohsen, 2018. "Optimal TOU tariff design using robust intuitionistic fuzzy divergence based thresholding," Energy, Elsevier, vol. 147(C), pages 655-662.
    8. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    9. Lanot, Gauthier & Vesterberg, Mattias, 2021. "The price elasticity of electricity demand when marginal incentives are very large," Energy Economics, Elsevier, vol. 104(C).
    10. Yu, Yanghao & Du, Ershun & Chen, Zhichao & Su, Yibo & Zhang, Xianfeng & Yang, Hongbin & Wang, Peng & Zhang, Ning, 2022. "Optimal portfolio of a 100% renewable energy generation base supported by concentrating solar power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    11. Huilan Jiang & Bingqi Liu & Yawei Wang & Shuangqi Zheng, 2014. "Multiobjective TOU Pricing Optimization Based on NSGA2," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-8, July.
    12. Venizelou, Venizelos & Philippou, Nikolas & Hadjipanayi, Maria & Makrides, George & Efthymiou, Venizelos & Georghiou, George E., 2018. "Development of a novel time-of-use tariff algorithm for residential prosumer price-based demand side management," Energy, Elsevier, vol. 142(C), pages 633-646.
    13. Utama, Christian & Troitzsch, Sebastian & Thakur, Jagruti, 2021. "Demand-side flexibility and demand-side bidding for flexible loads in air-conditioned buildings," Applied Energy, Elsevier, vol. 285(C).
    14. Zabaloy, Maria Florencia & Viego, Valentina, 2022. "Household electricity demand in Latin America and the Caribbean: A meta-analysis of price elasticity," Utilities Policy, Elsevier, vol. 75(C).
    15. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
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    Cited by:

    1. Diandian Hu & Tao Wang, 2023. "Optimizing Power Demand Side Response Strategy: A Study Based on Double Master–Slave Game Model of Multi-Objective Multi-Universe Optimization," Energies, MDPI, vol. 16(10), pages 1-16, May.
    2. Julio A. de Bitencourt & Daniel P. Bernardon & Henrique S. Eichkoff & Vinicius J. Garcia & Daiana W. Silva & Lucas M. Chiara & Renan L. B. Gomes & Sebastian A. Butto & Solange M. K. Barbosa & Alejandr, 2023. "An Alternative Regulation of Compensation Mechanisms for Electric Energy Transgressions of Service Quality Limits in Dispersed and Seasonal Areas," Energies, MDPI, vol. 16(15), pages 1-26, July.
    3. Peipei You & Sitao Li & Chengren Li & Chao Zhang & Hailang Zhou & Huicai Wang & Huiru Zhao & Yihang Zhao, 2023. "Price-Based Demand Response: A Three-Stage Monthly Time-of-Use Tariff Optimization Model," Energies, MDPI, vol. 16(23), pages 1-20, November.

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