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Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Author

Listed:
  • Qingwu Gong

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Jiazhi Lei

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Hui Qiao

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Jingjing Qiu

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

Abstract

The intermittency and variability of permeated distributed generators (DGs) could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not supplied), PLC (probability of load curtailment), EFLC (expected frequency of load curtailment), and SI (severity index)—were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs’ output power, an improved PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

Suggested Citation

  • Qingwu Gong & Jiazhi Lei & Hui Qiao & Jingjing Qiu, 2017. "Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution," Sustainability, MDPI, vol. 9(4), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:491-:d:94040
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    References listed on IDEAS

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    1. Qunli Wu & Chenyang Peng, 2016. "Comprehensive Benefit Evaluation of the Power Distribution Network Planning Project Based on Improved IAHP and Multi-Level Extension Assessment Method," Sustainability, MDPI, vol. 8(8), pages 1-18, August.
    2. Huiru Zhao & Sen Guo, 2015. "External Benefit Evaluation of Renewable Energy Power in China for Sustainability," Sustainability, MDPI, vol. 7(5), pages 1-23, April.
    3. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
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    Cited by:

    1. Kao-Yi Shen & Gwo-Hshiung Tzeng, 2018. "Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications," Sustainability, MDPI, vol. 10(5), pages 1-7, May.
    2. Roman Korab & Marcin Połomski & Marcin Smołka, 2022. "Evaluating the Risk of Exceeding the Normal Operating Conditions of a Low-Voltage Distribution Network due to Photovoltaic Generation," Energies, MDPI, vol. 15(6), pages 1-35, March.
    3. Prehoda, Emily W. & Schelly, Chelsea & Pearce, Joshua M., 2017. "U.S. strategic solar photovoltaic-powered microgrid deployment for enhanced national security," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 167-175.
    4. Jordehi, A. Rezaee, 2018. "How to deal with uncertainties in electric power systems? A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 145-155.
    5. Qingshan Xu & Yifan Ding & Aixia Zheng, 2017. "An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability," Sustainability, MDPI, vol. 9(5), pages 1-20, May.

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