Robust State Estimation of Active Distribution Networks Based on Improved IGG Weight Function

摘要

In the active distribution network, the distributed generator has some measurement or prediction errors. And the bad data in the measurement cannot be avoided. This paper proposes a method for robust state estimation based on improved IGG Weight Function, which is based on the adjustment of the weights of state estimation residuals, and which uses different weights to maintain accuracy, correct errors and eliminate bad data. The test results show that the method proposed in this paper is more accurate compared to estimates obtained through the weighted least square (WLS) method and unimproved IGG weight function method, both in the scenarios with measurement errors and bad data.