基于改进聚类算法的清洁能源互联网源网荷储协调控制研究

A Study on the Load and Storage Coordination Control of Clean Energy Internet Source Network Based on Improved Clustering Algorithm

为促进清洁能源互联网的节能减排,提高网络供电可靠性和清洁能源的消纳能力,提出基于改进聚类算法的清洁能源互联网源网荷储协调控制方法。通过样本密度调整次胜者受罚的竞争学习算法(rival penalized competitive learning,RPCL)的节点权值,提出改进RPCL聚类算法;依据网络节点间的关联关系,利用改进RPCL聚类算法计算清洁能源互联网的可靠性;构建源网荷储协调控制模型,经引入收缩因子的改进粒子群算法对模型进行求解,获取最佳源网荷储协调控制结果。实验表明:所提方法可在随机性与选择性攻击环境下提高清洁能源互联网的网络连通度,提升网络连接可靠度,降低源网荷储控制能耗;同时,可提高清洁能源的消纳能力,降低互联网运行成本。

To promote energy conservation and emission reduction of the clean energy internet and improve the reliability of the network power supply,a coordinated control method of clean energy internet source network load and storage based on improved clustering algorithm is proposed to improve the reliability of clean energy internet and clean energy consumption capacity in different environments.First of all,the node weight of Rival Penalized Competitive Learning(RPCL)is adjusted by sample density,and an improved RPCL clustering algorithm is proposed.Secondly,according to the association relationship between network nodes,the reliability of the clean energy internet is calculated using the improved RPCL clustering algorithm.Finally,the source network charge-storage coordination control model is constructed,and the model is solved by the improved particle swarm optimization algorithm with the contraction factor to obtain the best source network charge-storage coordination control results.The experiment shows that the proposed method can improve the network connectivity of the clean energy internet under random and selective attack environments,improve the network connection reliability,reduce the energy consumption of source network load storage control,and improve the clean energy consumption capacity and reduce the internet operation cost.