电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2013年
22期
98-102
,共5页
谐波状态估计%相量量测%混合量测%量测配置%粒子群算法
諧波狀態估計%相量量測%混閤量測%量測配置%粒子群算法
해파상태고계%상량량측%혼합량측%량측배치%입자군산법
harmonic state estimation%phasor measurement%mixed measurement%measurement configuration%particle swarm optimization algorithm
为增加谐波量测数据的冗余度，提高线性谐波状态估计的可观测度，基于 PMU量测数据和SCADA量测数据构成混合量测数据，应用于谐波状态估计，建立非线性谐波状态估计的数学模型。将该非线性数学模型改写为灵敏度模型，并转化为优化问题，应用粒子群算法求解。算例分析表明，非线性谐波状态估计的灵敏度模型是有效的，应用优化算法求解是切实可行的，混合量测数据能提高谐波状态估计的可观测度。
為增加諧波量測數據的冗餘度，提高線性諧波狀態估計的可觀測度，基于 PMU量測數據和SCADA量測數據構成混閤量測數據，應用于諧波狀態估計，建立非線性諧波狀態估計的數學模型。將該非線性數學模型改寫為靈敏度模型，併轉化為優化問題，應用粒子群算法求解。算例分析錶明，非線性諧波狀態估計的靈敏度模型是有效的，應用優化算法求解是切實可行的，混閤量測數據能提高諧波狀態估計的可觀測度。
위증가해파량측수거적용여도，제고선성해파상태고계적가관측도，기우 PMU량측수거화SCADA량측수거구성혼합량측수거，응용우해파상태고계，건립비선성해파상태고계적수학모형。장해비선성수학모형개사위령민도모형，병전화위우화문제，응용입자군산법구해。산례분석표명，비선성해파상태고계적령민도모형시유효적，응용우화산법구해시절실가행적，혼합량측수거능제고해파상태고계적가관측도。
To increase the redundancy of measurement data and improve the observability of linear harmonic state estimation, mixed measurements acquired from PMU and SCADA are used to build the mathematical model of non-linear harmonic state estimation. Then, it is rewritten as a sensitivity model, transformed into an optimization problem, and solved by particle swarm optimization algorithm. Example analysis shows the sensitivity model of non-linear harmonic state estimation is efficient. PSO algorithm can be used to solve this optimization problem. Mixed measurements are helpful to improve the accuracy of harmonic state estimation.
