摘要
Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation(DA) system for safe operation and control. The design of optimal feeder terminal units(FTU)placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation(SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function(PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy(CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology.
Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation（DA） system for safe operation and control. The design of optimal feeder terminal units（FTU）placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation（SE）, typically include the following two main shortcomings： 1） only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2） few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function（PDF）. The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy（CMA-ES）. Case studies demonstrate the feasibility and effectiveness of the proposed methodology.
基金
supported by the National Natural Science Foundation of China(Grant No.51677025)
State Grid Corporation of China(Grant No.52110417000A)
Research Innovation Program for College Graduates(Grant No.KYLX16_0212)
National Key Research&Development Project of China(Grant No.2017YFB0902801)
