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Fuzzy Load-Shedding Strategy Considering Photovoltaic Output Fluctuation Characteristics and Static Voltage Stability

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  • Sheng Li

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
    School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

  • Zhinong Wei

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Yanan Ma

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

Abstract

Based on the equilibrium point equations of a classic three-node system integrated with a large-scale photovoltaic cell (PV) power plant, the impact of PV output fluctuation on the saddle-node bifurcation (SNB) was derived and analyzed. When PV runs in a unity power factor and the PV output active power P pv is not too large (several hundred MW and below), the PV output fluctuation has little effect on the SNB point position and load margin index, so that the load margin index can be calculated online using the SNB point at P pv = 0 pu. On the other hand, the local reactive power compensation in the load center can effectively raise the load bus voltage and make the voltage stability problem become more concealed; the traditional under-voltage load-shedding (UVLS) strategy only carries out load shedding when the bus voltage amplitude is below the specified value and cannot effectively maintain the system static voltage stability in some occasions. In this paper, a fuzzy load-shedding strategy considering the impact of PV output fluctuations for the large-scale PV grid-connected system was designed, taking the load bus voltage amplitude and load margin index as fuzzy input variables, and the load-shedding command as a fuzzy output variable. Nine fuzzy IF-THEN rules were extracted for the fuzzy controller and the corresponding practical calculation method of load-shedding quantity was put forward. The simulation results of the classic three-node system and IEEE 14-bus system, both with a 100 MW PV power plant, verified the effectiveness of the fuzzy load-shedding controller whose input variable load margin index was calculated using the SNB point when the PV active power output was 0. The designed fuzzy load-shedding strategy can compensate for the defect—that the traditional UVLS strategy cannot effectively guarantee the system static voltage stability—and it can be widely used in power grids integrated with PV power plants whose scales are at a level of several hundred MW and below.

Suggested Citation

  • Sheng Li & Zhinong Wei & Yanan Ma, 2018. "Fuzzy Load-Shedding Strategy Considering Photovoltaic Output Fluctuation Characteristics and Static Voltage Stability," Energies, MDPI, vol. 11(4), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:779-:d:138539
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    References listed on IDEAS

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    1. Shun Li & Fei Tang & Youguo Shao & Qingfen Liao, 2017. "Adaptive Under-Frequency Load Shedding Scheme in System Integrated with High Wind Power Penetration: Impacts and Improvements," Energies, MDPI, vol. 10(9), pages 1-16, September.
    2. Yu Li & Masato Ishikawa, 2017. "An Efficient Reactive Power Control Method for Power Network Systems with Solar Photovoltaic Generators Using Sparse Optimization," Energies, MDPI, vol. 10(5), pages 1-14, May.
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    Cited by:

    1. Sheng Li & Can Zhang & Jili Zuo, 2023. "Long-Term Voltage Stability Bifurcation Analysis and Control Considering OLTC Adjustment and Photovoltaic Power Station," Energies, MDPI, vol. 16(17), pages 1-17, September.
    2. Sheng Li & Yuting Lu & Yulin Ge, 2023. "Static Voltage Stability Zoning Analysis Based on a Sensitivity Index Reflecting the Influence Degree of Photovoltaic Power Output on Voltage Stability," Energies, MDPI, vol. 16(6), pages 1-18, March.
    3. Weiming Zhang & Tinglong Pan & Dinghui Wu & Dezhi Xu, 2020. "A Novel Command-Filtered Adaptive Backstepping Control Strategy with Prescribed Performance for Photovoltaic Grid-Connected Systems," Sustainability, MDPI, vol. 12(18), pages 1-17, September.

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