Statistical Methods in Measuring the Emergency Condition Parameters in Networks with Distributed Energy Resources

Abstract

The paper presents an analysis of algorithms for the digital processing of current and voltage signals used in the measurement (estimation) of power flow parameters in electric power systems. The study identifies disadvantages that limit the application of widely used methods for digital processing of emergency operating parameters in networks with distributed energy resources. It also indicates how the connection of heterogeneous distributed energy resources to medium- and low-voltage networks affects the operation of the protective relay and emergency control devices. The findings prove the efficiency of statistical approaches in measuring (estimating) the emergency condition parameters when power quality indices fluctuate and show the influence of various distorting factors. Flow diagrams of measuring elements that allow the maximum likelihood estimation are presented with examples demonstrating the estimation of the emergency condition parameters. We have developed an algorithm for the functioning of a multichannel measuring element with digital signal processing. It enables simultaneous estimation of several voltage parameters and has high accuracy when frequency changes and power quality indices deviate from the rated values. The simulation modeling results suggest the possibility of a sizeable reduction in measurement (estimate) error and an increase in the speed of estimation of the emergency condition parameters by the maximum likelihood method.