Distributed generation equipment improves renewable energy utilization and economic benefits through an energy storage system (ESS). However, dominated by short-term data, the configuration of long-period ESS capacity is absent based on the dynamic change of load, which leads to a large deviation from the expected return. Considering the system characteristics of lack of data and less information, after introducing the grey theory, we propose a new long-term capacity configuration method for ESS and establish the long-term grey forecasting model (GFM) of user load, improving the basic forecasting model to improve the accuracy of the long-term forecasting model. Then, the scheduling model is established with the maximum economic and social benefits as the optimization objective. Based on the forecast data of the improved grey forecasting model (IGFM), the hierarchical solution method is used to solve the scheduling model. Finally, the parameters are configured based on the service life of the equipment and the expected rate of return. The simulation results show that higher accuracy is realized in the improved prediction model, and the improved algorithm gets higher convergence speed and precision. Apart from that, the nonlinear correlation trend of the EES return rate between the capacity and life cycle is revealed. Compared with the ESS configuration in a short period, this study provides more comprehensive and accurate data support for the capacity configuration of the ESS, reducing the error between the actual return and the expected return significantly.

In order to improve the ability to detect and identify topological errors and measurement errors, and further enhance the rapidity and reliability of substation state estimation, this paper proposes a threephase linear state estimation method for substations based on zero impedance model. Firstly, for the shortcomings of the traditional regularized weighted residual method with many cycles and slow calculation speed, improvements are made to improve the rapidity of state estimation while suppressing the residual flooding phenomenon. Based on this, the zero-impedance model of the substation makes full use of the threephase telemetry and telecommunication state data to establish the power measurement equation for zeroimpedance initial power state estimation, and proposes a discrimination method to identify measurement errors and topological errors and to determine the state of the switching circuit breakers. Based on the secondary power state estimation, a voltage measurement equation is established based on the voltage measurement information to estimate the substation voltage state. The simulation results show that the method can accurately identify and locate the simultaneous measurement errors and topology errors, and can also identify individual measurement errors, thus improving the estimation accuracy of state estimation.