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Combining model-based and model-free methods for stochastic control of distributed energy resources

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  • Chen, Yue
  • Lin, Yashen

Abstract

Modern distribution systems are experiencing a fast transformation with the growing penetration of distributed energy resources (DERs). Along with the economic and environmental benefits of DERs, challenges arise to address the uncertainties caused by their inherent volatility. If properly coordinated, however, DERs have the potential to provide the controllability that grid operators need. In the paper, we propose a hierarchical control framework that combines the model-based and model-free methods for stochastic DER control in distribution systems. The upper-level scheduler considers a chance-constrained optimal power flow problem (model-based) that schedules DER setpoints to minimize the operational cost and maintain the operating reserve. The lower-level distributed DER controllers absorb real-time disturbances and uncertainties using the extremum seeking control (model-free) to achieve grid objectives. The combination of model-based and model-free methods allows us to take the advantages of both methods to effectively manage the uncertainty in distribution systems. The proposed work is demonstrated on the IEEE 13-node feeder.

Suggested Citation

  • Chen, Yue & Lin, Yashen, 2021. "Combining model-based and model-free methods for stochastic control of distributed energy resources," Applied Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316019
    DOI: 10.1016/j.apenergy.2020.116204
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    References listed on IDEAS

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    1. Grover-Silva, Etta & Heleno, Miguel & Mashayekh, Salman & Cardoso, Gonçalo & Girard, Robin & Kariniotakis, George, 2018. "A stochastic optimal power flow for scheduling flexible resources in microgrids operation," Applied Energy, Elsevier, vol. 229(C), pages 201-208.
    2. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Liao, Siyang & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao, 2018. "Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources," Applied Energy, Elsevier, vol. 211(C), pages 237-248.
    3. Fang, Xin & Cui, Hantao & Yuan, Haoyu & Tan, Jin & Jiang, Tao, 2019. "Distributionally-robust chance constrained and interval optimization for integrated electricity and natural gas systems optimal power flow with wind uncertainties," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Wei, Jingdong & Zhang, Yao & Wang, Jianxue & Cao, Xiaoyu & Khan, Muhammad Armoghan, 2020. "Multi-period planning of multi-energy microgrid with multi-type uncertainties using chance constrained information gap decision method," Applied Energy, Elsevier, vol. 260(C).
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    Cited by:

    1. Lei, Xingyu & Yang, Zhifang & Zhao, Junbo & Yu, Juan, 2022. "Data-driven assisted chance-constrained energy and reserve scheduling with wind curtailment," Applied Energy, Elsevier, vol. 321(C).

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