基于改进场景聚类算法的海上风电储能优化配置研究

Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm

在平滑海上风电出力波动的应用需求下,提出一种储能优化配置方法。利用小波包分解算法对海上风电出力曲线进行分解,得到储能系统全年功率响应曲线。采用基于云模型和模糊C均值聚类算法相结合的改进场景聚类算法,对储能全年功率响应曲线进行聚合,生成储能功率响应典型场景。以储能年综合成本最低为目标,构建储能优化配置模型。采用粒子群算法对海上风电储能优化配置模型进行求解,最后通过算例仿真对所提方法和模型进行分析验证。结果表明:所提模型和方法能综合考虑海上风电场侧储能的实际运行特性,可有效指导海上风电场的储能配置和建设规划。

As demands on smoothing the output fluctuation of offshore wind power increase,this paper proposes an optimal configuration method for offshore wind power storage.The wavelet packet decomposition algorithm is used to process the output curve of the wind power,and an annual power response curve of the power storage system is obtained.In addition,the paper adopts an improved scene clustering algorithm combining a cloud model with a fuzzy c-means clustering algorithm to aggregate the annual power response curve and generate typical scenes of the power response.Furthermore,to minimize the annual comprehensive cost of the power storage,the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model.Finally,the proposed method and model are analyzed and verified by typical examples.The results show that the proposed model and method can comprehensively consider the actual operating characteristics of the power storage system on the side of offshore wind farms and effectively guide the power storage configuration and construction planning of offshore wind farms.