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Emergency Dispatch Approach for Power Systems with Hybrid Energy Considering Thermal Power Unit Ramping

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  • Buxiang Zhou

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

  • Jiale Wu

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

  • Tianlei Zang

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

  • Yating Cai

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

  • Binjie Sun

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

  • Yiwei Qiu

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    Intelligent Electric Power Grid Key Laboratory of Sichuan Province, Sichuan University, Chengdu 610065, China)

Abstract

Future power systems will face more extreme operating condition scenarios, and system emergency dispatch will face more severe challenges. The use of distributed control is a well-designed way to handle this. It enables multi-energy complementation by means of autonomous communication, which greatly improves the flexibility of the grid. First, in the context of global energy conservation and emission reduction, this paper adopts the energy usage method of “renewable energy is the main source of energy, supplemented by thermal power and energy storage” to reduce the system abandoned wind (light) rate while supplementing the energy storage capacity. Second, a consensus algorithm is added to the system while considering the coordination between thermal units and energy storage. An “interface” for autonomous communication between thermal units and energy storage is created using the incremental cost of each agent. To address the recurring issue of power imbalance during emergency dispatch of the system, the consensus algorithm is enhanced so that the communication interval varies with the unit rate. This is based on the climbing characteristics of each thermal power unit. Finally, the effectiveness of the proposed method is verified in an IEEE-30 bus system.

Suggested Citation

  • Buxiang Zhou & Jiale Wu & Tianlei Zang & Yating Cai & Binjie Sun & Yiwei Qiu, 2023. "Emergency Dispatch Approach for Power Systems with Hybrid Energy Considering Thermal Power Unit Ramping," Energies, MDPI, vol. 16(10), pages 1-25, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4213-:d:1151512
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    References listed on IDEAS

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    1. Elkazaz, Mahmoud & Sumner, Mark & Naghiyev, Eldar & Pholboon, Seksak & Davies, Richard & Thomas, David, 2020. "A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers," Applied Energy, Elsevier, vol. 269(C).
    2. Zhilin Lyu & Xiao Yang & Yiyi Zhang & Junhui Zhao, 2020. "Bi-Level Optimal Strategy of Islanded Multi-Microgrid Systems Based on Optimal Power Flow and Consensus Algorithm," Energies, MDPI, vol. 13(7), pages 1-19, March.
    3. Zhang, Zhaoyi & Shang, Lei & Liu, Chengxi & Lai, Qiupin & Jiang, Youjin, 2023. "Consensus-based distributed optimal power flow using gradient tracking technique for short-term power fluctuations," Energy, Elsevier, vol. 264(C).
    4. Chi Cao & Jun Xie & Dong Yue & Chongxin Huang & Jixiang Wang & Shuyang Xu & Xingying Chen, 2017. "Distributed Economic Dispatch of Virtual Power Plant under a Non-Ideal Communication Network," Energies, MDPI, vol. 10(2), pages 1-18, February.
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    Cited by:

    1. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.
    2. Tianlei Zang & Xiaoning Tong & Chuangzhi Li & Yahui Gong & Rui Su & Buxiang Zhou, 2025. "Research and Prospect of Defense for Integrated Energy Cyber–Physical Systems Against Deliberate Attacks," Energies, MDPI, vol. 18(6), pages 1-57, March.

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