基于优化GA-PSO方法的高渗透工业电站鲁棒性控制  

Robust Control of High-Permeability Industrial Power Plants Based on the Optimised GA-PSO Approach

作　　者：靳艾静 Jin Aijing(Hengshui Power Supply Branch,State Grid Power Co.,Ltd.,Hengshui Hebei 053000,China)

机构地区：[1]国网河北省电力有限公司衡水供电分公司,河北衡水053000

出　　处：《现代工业经济和信息化》2024年第8期166-168,共3页Modern Industrial Economy and Informationization

摘　　要：为了弥补传统粒子群(PSO)算法风电出力鲁棒调度较低的问题,通过以遗传算法(GA)来优化PSO的方式设计了一种基于优化GA-PSO方法的高渗透电站鲁棒性控制。通过PSO算法与交叉变异相融合形式来实现PSO快速收敛的效果,避免粒子产生局部最优。研究结果表明:该鲁棒控制方法表现出了比传统控制模式更强鲁棒性,保证电站实现安全稳定控制目标。持续提高风电场的数量后,风电场分布范围也进一步扩大,提升了风电出力稳定性,降低了电站冲击程度,造成系统风险成本发生显著降低。该方法具备PSO快速收敛优势,消除了粒子存在局部最优的缺陷。In order to make up for the problem of low robust scheduling of wind power output of traditional particle swarm(PSO)algorithm,a high permeability power station robustness control based on optimised GA-PSO method is designed by optimising PSO way through genetic algorithm(GA).Through the PSO algorithm and cross-variance fusion form to PSO fast convergence effect,to avoid particles produce local optimal.The results of the algorithmic research carried out show that the robust control method in this paper exhibits stronger robustness than the traditional control mode,ensuring that the power plant achieves the safe and stable control goal.After continuously improving the number of wind farms,the distribution range of wind farms is also further expanded,which improves the stability of wind power output,reduces the degree of impact of the power station,resulting in a significant reduction in the cost of system risk.The method has the advantage of fast convergence of PSO and eliminates the defect of the existence of local optimum of particles.

关 键 词：电站 自动控制 粒子群算法 遗传算法 鲁棒性 风险成本 

分 类 号：TP17[自动化与计算机技术—控制理论与控制工程]