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Integrating flexible demand response toward available transfer capability enhancement

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  • Hou, Lingxi
  • Li, Weiqi
  • Zhou, Kui
  • Jiang, Qirong

Abstract

Available transfer capability (ATC) has been widely adopted as a crucial measure to guarantee free and reliable power trading. The existing literature generally evaluates the ATC of a power grid considering inelastic load. However, the impacts of responsive load have not yet been systematically explored, which underestimates the ability of demand side resources in ATC enhancement. Therefore, we propose a two-stage ATC evaluation framework in this paper integrating flexible demand response (FDR). In the first stage, i.e., a day-ahead market, a demand side bidding scheme is developed in which electricity users can make flexible choices to participate in demand response (DR) programs according to their preferences. In this paper, FDR is categorized into three typical patterns: (i) deferrable DR, (ii) switchable DR and (iii) adjustable DR. The objective is to minimize the total generation and dispatch costs, while respecting the constraints for FDR, the minimal accommodation of renewable energy, the inter-area power trading, etc. Then based on generation and demand side bidding, a day-ahead unit commitment model is formulated to schedule thermal generators, interchange power and FDR. In the second stage, a real-time ATC evaluation model based on the aforementioned unit commitment results is proposed to quantify the contributions of FDR on ATC enhancement. Case studies based on IEEE 14-bus system and a provincial power grid in China demonstrate that FDR can effectively improve real-time ATC by load shifting and peak shaving, and facilitate the accommodation of renewable energy.

Suggested Citation

  • Hou, Lingxi & Li, Weiqi & Zhou, Kui & Jiang, Qirong, 2019. "Integrating flexible demand response toward available transfer capability enhancement," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  • Handle: RePEc:eee:appene:v:251:y:2019:i:c:98
    DOI: 10.1016/j.apenergy.2019.113370
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    References listed on IDEAS

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    Cited by:

    1. Yuwei Zhang & Wenying Liu & Yue Huan & Qiang Zhou & Ningbo Wang, 2020. "An Optimal Day-Ahead Thermal Generation Scheduling Method to Enhance Total Transfer Capability for the Sending-Side System with Large-Scale Wind Power Integration," Energies, MDPI, vol. 13(9), pages 1-19, May.
    2. Jiang, Tao & Li, Xue & Kou, Xiao & Zhang, Rufeng & Tian, Guoda & Li, Fangxing, 2022. "Available transfer capability evaluation in electricity-dominated integrated hybrid energy systems with uncertain wind power: An interval optimization solution," Applied Energy, Elsevier, vol. 314(C).
    3. Zhu, Yansong & Liu, Jizhen & Hu, Yong & Xie, Yan & Zeng, Deliang & Li, Ruilian, 2024. "Distributionally robust optimization model considering deep peak shaving and uncertainty of renewable energy," Energy, Elsevier, vol. 288(C).
    4. Guo, Zhilong & Xu, Wei & Yan, Yue & Sun, Mei, 2023. "How to realize the power demand side actively matching the supply side? ——A virtual real-time electricity prices optimization model based on credit mechanism," Applied Energy, Elsevier, vol. 343(C).
    5. Dan Zhou & Qi Zhang & Yangqing Dan & Fanghong Guo & Jun Qi & Chenyuan Teng & Wenwei Zhou & Haonan Zhu, 2022. "Research on Renewable-Energy Accommodation-Capability Evaluation Based on Time-Series Production Simulations," Energies, MDPI, vol. 15(19), pages 1-15, September.
    6. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    7. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    8. Dai, Xuemei & Li, Yaping & Zhang, Kaifeng & Feng, Wei, 2020. "A robust offering strategy for wind producers considering uncertainties of demand response and wind power," Applied Energy, Elsevier, vol. 279(C).

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