Analysis of State Estimation Accuracy in Distribution Networks Using Pseudo- Measurement Selection and Real Measurement Incorporation

In this paper, we investigate computationally efficient methodologies for generating pseudo-measurements with the aim of selecting the set of pseudo-measurements that can achieve maximum state estimation accuracy for a given network. We analyze the impact of various information sources for residential and demand-response load pseudo- measurements. Additionally, we examine three meteorological approaches to approximate photovoltaic output. By preforming numerical experiments across four real Hungarian low- voltage supply areas, we present the scenarios that yield the maximum state estimation accuracy for each load, which can be conveniently incorporated into any industrial application.