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Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

Author

Listed:
  • Pengwei Cong

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Wei Tang

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Lu Zhang

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Bo Zhang

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Yongxiang Cai

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

Abstract

With large-scale integration of distributed energy resources (DERs), distribution networks have turned into active distribution networks (ADNs). However, management risks and obstacles are caused by this in due to renewable energy generation (REG) forecasting errors. In this paper, a day-ahead active power scheduling method considering REG forecast errors is proposed to eliminate the risks, minimize the costs of distribution companies and achieve optimal power flow. A hierarchical coordination optimization model based on chance constrained programming is established to realize day-ahead optimal scheduling of active power in ADNs coordinated with network reconfiguration, achieving an optimal solution of network topologies and DER outputs. The hierarchical method includes three levels: the first level provides initial values, and multiple iterations between the second and third level are used to solve the multi-period mixed integer nonlinear optimization problem. The randomness due to REG forecast errors is tackled with chance constrained programming in the scheduling procedure. The hybrid particle swarm optimization algorithm is employed to solve the proposed model. Simulation results verify the validity of the proposed method with an improved 33 nodes distribution network.

Suggested Citation

  • Pengwei Cong & Wei Tang & Lu Zhang & Bo Zhang & Yongxiang Cai, 2017. "Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors," Energies, MDPI, vol. 10(9), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1291-:d:110155
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    References listed on IDEAS

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    1. Fei Chen & Dong Liu & Xiaofang Xiong, 2017. "Research on Stochastic Optimal Operation Strategy of Active Distribution Network Considering Intermittent Energy," Energies, MDPI, vol. 10(4), pages 1-23, April.
    2. Firas M. F. Flaih & Xiangning Lin & Mohammed Kdair Abd & Samir M. Dawoud & Zhengtian Li & Owolabi Sunday Adio, 2017. "A New Method for Distribution Network Reconfiguration Analysis under Different Load Demands," Energies, MDPI, vol. 10(4), pages 1-19, April.
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    Cited by:

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    2. Yajing Gao & Yanping Sun & Xiaodan Wang & Feifan Chen & Ali Ehsan & Hongmei Li & Hong Li, 2017. "Multi-Objective Optimized Aggregation of Demand Side Resources Based on a Self-organizing Map Clustering Algorithm Considering a Multi-Scenario Technique," Energies, MDPI, vol. 10(12), pages 1-20, December.
    3. Byeong-Cheol Jeong & Dong-Hwan Shin & Jae-Beom Im & Jae-Young Park & Young-Jin Kim, 2019. "Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid," Energies, MDPI, vol. 12(6), pages 1-20, March.
    4. Xiao Han & Ming Zhou & Gengyin Li & Kwang Y. Lee, 2017. "Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium," Energies, MDPI, vol. 10(12), pages 1-17, December.
    5. Kalyani Makarand Kurundkar & Geetanjali Abhijit Vaidya, 2023. "Stochastic Security-Constrained Economic Dispatch of Load-Following and Contingency Reserves Ancillary Service Using a Grid-Connected Microgrid during Uncertainty," Energies, MDPI, vol. 16(6), pages 1-25, March.
    6. Yu Zhang & Xiaohui Song & Yong Li & Zilong Zeng & Chenchen Yong & Denis Sidorov & Xia Lv, 2020. "Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility," Energies, MDPI, vol. 13(22), pages 1-13, November.
    7. Chong Chen & Xuan Zhou & Xiaowei Yang & Zhiheng He & Zhuo Li & Zhengtian Li & Xiangning Lin & Ting Wen & Yixin Zhuo & Ning Tong, 2018. "Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads," Energies, MDPI, vol. 11(4), pages 1-22, April.
    8. Xiuyun Wang & Yibing Zhou & Junyu Tian & Jian Wang & Yang Cui, 2018. "Wind Power Consumption Research Based on Green Economic Indicators," Energies, MDPI, vol. 11(10), pages 1-24, October.
    9. Yu Shi & Fei Lv & Xuefeng Gao & Minglei Jiang & Huan Luo & Ruhang Xu, 2023. "A Bi-Level Optimal Operation Model for Small-Scale Active Distribution Networks Considering the Coupling Fluctuation of Spot Electricity Prices and Renewable Energy Sources," Energies, MDPI, vol. 16(11), pages 1-26, June.

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