基于改进粒子群算法的风光储协同规划技术

Wind and Landscape Storage Collaborative Planning Technology Based on Improved Particle Swarm Optimization

为提高现有新能源规划模型设计合理性,优化模型求解算法,补充相关约束条件,针对风电、光伏分布式电源以及储能系统的出力特性和运行特点进行分析,建立风、光、储的数学模型。分析可再生能源接入配电网后,自身间歇性和波动性特点对配电网的综合影响。利用储能系统具有稳定振荡、负荷调峰、延缓设备改造等特点,提出合理配置可再生能源和储能系统,提高配电网安全性、稳定性和经济性的规划思路。综合考虑运行成本、碳排放量及网损指标等目标函数,通过改进粒子群算法确定分布式电源及储能系统最优选址和容量。最后,应用改进的粒子群算法对模型进行求解,并在IEEE33节点系统进行仿真,通过实际算例验证所提风光储协同规划方案的有效性。

In order to improve the rationality of the design of the existing new energy planning model,the model solving algorithm was optimized and the relevant constraints were supplemented.According to the output characteristics and operation characteristics of wind power,photovoltaic distributed power generation and energy storage system,the mathematical model of wind,light and storage is established.The comprehensive impact of renewable energy on the distribution network by its own intermittent and fluctuating characteristics after it is connected to the distribution network is analyzed.The energy storage system has the characteristics of stable oscillation,load peak regulation,and delayed equipment transformation,and the planning idea of rational allocation of renewable energy and energy storage system to are put forward improve the safety,stability and economy of the distribution network.The objective functions such as operating cost,carbon emissions and network loss index are comprehensively considered,and the optimal site selection and capacity of distributed power generation and energy storage system are determined by improving the particle swarm algorithm.Finally,the model is solved by the improved particle swarm algorithm and simulated in the IEEE33 node system,and the effectiveness of the proposed collaborative planning scheme of wind,solar and storage is verified by practical examples.