Abstract
As the penetration of distributed wind power in the distribution network continues to increase, the uncertainty of its output has a serious impact on the stable operation of the distribution network. It is difficult to meet the voltage regulation requirements when the wind power fluctuates frequently only by relying on shunt capacitors. Therefore, a coordinated optimization planning method based on soft open point (SOP) and shunt capacitors is proposed. Firstly, the bidirectional generative adversarial network (BIGAN) is used to characterize the uncertainty of wind power output and generate typical scenarios of wind power output. Secondly, a multi-objective optimization planning model of SOP and shunt capacitors is proposed based on the scene analysis method; Then, a solution strategy based on the improved elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed. Finally, the proposed planning model and solution are verified and analyzed in the improved IEEE 33-bus system.
Highlights
Wind energy is a kind of renewable energy, which is widely distributed and non-emission
The coordination of soft open point (SOP) and shunt capacitor should be considered in the optimal planning of distribution network
A large number of researches have considered the influence of wind power output uncertainty in distribution network optimization planning
Summary
Different from image generation, the wind power data learned by Bigan is affected by physical factors such as atmosphere and spatial relationship of power generation units. The historical wind power data is input, and Bigan independently learns the statistical rules of the input data, and trains the encoder, generator and discriminator. After reaching or approaching the Nash equilibrium, the trained model is used to generate the data which accords with the statistical distribution characteristics of the original data.
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