Journal of Electrical Engineering and Technology

  • 제12권1호
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  • Pages.53-63
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  • 2017
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  • 1975-0102(pISSN)
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  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation

  • Cui, Wei (Dept. of Electrical Engineering, Chongqing University) ;
  • Yan, Wei (Dept. of Electrical Engineering, Chongqing University) ;
  • Lee, Wei-Jen (Dept. of Electrical Engineering, The University of Texas at Arlington) ;
  • Zhao, Xia (Dept. of Electrical Engineering, Chongqing University) ;
  • Ren, Zhouyang (Dept. of Electrical Engineering, Chongqing University) ;
  • Wang, Cong (Dept. of Electrical Engineering, Chongqing University)
  • 투고 : 2015.12.11
  • 심사 : 2016.09.01
  • 발행 : 2017.01.02
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초록

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

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피인용 문헌

  1. Volt/Var Control for Power Grids With Connections of Large-Scale Wind Farms: A Review vol.6, pp.2169-3536, 2018, https://doi.org/10.1109/ACCESS.2018.2832175