Abstract
In order to solve the coordination problem between the economy and the stabilization effect of energy storage system, a capacity optimization model based on energy storage to suppress the violent fluctuation of wind power is proposed, and a multi-objective function with the maximum wind power dissipation capacity and the minimum operating cost of energy storage system is established. Considering the average annual cost and penalty cost of the whole life cycle, an evaluation index with correlation coefficient as the fitting degree is proposed, and the reference power of wind farm grid connection is optimized by particle swarm algorithm. Using the operation data of Qidong Wind Farm in Jiangsu Province, the theoretical validity is verified, the coordination is improved to the greatest extent, and the capacity demand for energy storage system is reduced.
Highlights
The additional energy storage system can improve the power fluctuation of wind turbines and improve the power quality and wind power acceptance capacity
The balance between energy storage economy and power stabilization effect is the most important reason that restricts the improvement of the energy storage system from the stabilization effect of wind power fluctuations
The objective function is to find the relationship between energy storage economy and stabilization effect, reduce wind abandonment, and improve the grid's acceptance of wind power [3]
Summary
The additional energy storage system can improve the power fluctuation of wind turbines and improve the power quality and wind power acceptance capacity. The economy of energy storage is negatively related to the energy storage capacity. The larger the capacity, the better the stabilization effect of wind power fluctuations and the worse the economy. The balance between energy storage economy and power stabilization effect is the most important reason that restricts the improvement of the energy storage system from the stabilization effect of wind power fluctuations. It is necessary to adopt the optimization algorithm and establish a multi-objective capacity optimization model
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