基于大数据与粒子群的清洁能源协同优化调度方法

Collaborative optimization scheduling method of clean energy based on big data and particle swarm optimization

为解决清洁能源系统运行节点因存在延迟调度,而影响清洁能源协同优化调度效果的问题。为避免该问题,本文提出基于大数据技术与粒子群算法的清洁能源协同优化调度方法。根据清洁能源协同运行特点,利用大数据技术分析作业参数,并设计运行节点延迟调度策略,然后构建清洁能源系统输出功率调度模型。将最大运营利益和最小弃能成本作为优化目标,构建清洁能源协同优化调度模型,再采用粒子群算法进行求解,得到最优调度方案。实验结果表明:本文方法可以获取较优的清洁能源协同调度结果。

If there is a delay in the operation node of the clean energy system,it will affect the effect of collaborative optimization scheduling of clean energy.To avoid this problem,a collaborative optimization scheduling method of clean energy based on big data technology and particle swarm optimization algorithm is proposed.According to the operation characteristics of the clean energy system,the big data technology is used to analyze the operation parameters,the operation node delay scheduling strategy is desgined,and then the output power scheduling model is constructed.Taking the maximum operating benefit and the minimum energy discarding cost as the optimization objectives,a collaborative optimization scheduling model of clean energy system is constructed,and then the particle swarm optimization algorithm is used to solve the model to obtain the optimal scheduling scheme.The experimental results show that this method can obtain better results of clean energy collaborative scheduling.