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A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment

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Listed:
  • Zhe Zhang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Hang Yang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Xianggen Yin

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Jiexiang Han

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Yong Wang

    (Guangzhou Power Supply Company, Ltd., Guangzhou 510000, China)

  • Guoyan Chen

    (Guangzhou Power Supply Company, Ltd., Guangzhou 510000, China)

Abstract

The traditional load-shedding models usually use global optimization to get the load-shedding region, which will cause multiple variables, huge computing scale and other problems. This makes it hard to meet the requirements of timeliness in on-line power system operation risk assessment. In order to solve the problems of the present load-shedding models, a load-shedding model based on sensitivity analysis is proposed in this manuscript. By calculating the sensitivity of each branch on each bus, the collection of buses which have remarkable influence on reducing the power flow on over-load branches is obtained. In this way, global optimization is turned to local optimization, which can narrow the solution range. By comprehensively considering the importance of load bus and adjacency principle regarding the electrical coupling relationship, a load-shedding model is established to get the minimum value of the load reduction from different kinds of load buses, which is solved by the primal dual interior point algorithm. In the end, different cases on the IEEE 24-bus, IEEE 300-bus and other multi-node systems are simulated. The correctness and effectiveness of the proposed load-shedding model are demonstrated by the simulation results.

Suggested Citation

  • Zhe Zhang & Hang Yang & Xianggen Yin & Jiexiang Han & Yong Wang & Guoyan Chen, 2018. "A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment," Energies, MDPI, vol. 11(4), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:727-:d:137704
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    References listed on IDEAS

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    1. Anna Rita Di Fazio & Mario Russo & Sara Valeri & Michele De Santis, 2016. "Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources," Energies, MDPI, vol. 9(10), pages 1-16, October.
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    Cited by:

    1. Pau Casals-Torrens & Juan A. Martinez-Velasco & Alexandre Serrano-Fontova & Ricard Bosch, 2020. "Assessment of Unintentional Islanding Operations in Distribution Networks with Large Induction Motors," Energies, MDPI, vol. 13(2), pages 1-25, January.
    2. Biyun Chen & Haoying Chen & Yiyi Zhang & Junhui Zhao & Emad Manla, 2019. "Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems," Energies, MDPI, vol. 12(6), pages 1-18, March.
    3. Amir Abdel Menaem & Rustam Valiev & Vladislav Oboskalov & Taher S. Hassan & Hegazy Rezk & Mohamed N. Ibrahim, 2020. "An Efficient Framework for Adequacy Evaluation through Extraction of Rare Load Curtailment Events in Composite Power Systems," Mathematics, MDPI, vol. 8(11), pages 1-21, November.
    4. Michael Felix Pacevicius & Marilia Ramos & Davide Roverso & Christian Thun Eriksen & Nicola Paltrinieri, 2022. "Managing Heterogeneous Datasets for Dynamic Risk Analysis of Large-Scale Infrastructures," Energies, MDPI, vol. 15(9), pages 1-40, April.

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