Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks

TL;DR

This paper introduces a probabilistic voltage sensitivity method for preemptive voltage monitoring in unbalanced distribution networks, enhancing prediction accuracy and enabling better voltage control amidst renewable energy fluctuations.

Contribution

It presents a novel low-complexity, data-driven probabilistic approach for voltage violation prediction in unbalanced grids, improving upon traditional load flow methods.

Findings

Achieves over 95% accuracy in predicting voltage violations.

Effectively predicts voltage distribution considering renewable energy sources.

Validates approach on IEEE 37 node system with solar integration.

Abstract

With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cause random voltage fluctuations as their output power depends on weather conditions. Conventional voltage control schemes such as tap changers and capacitor banks lack the foresight required to quickly alleviate voltage violations. Thus, there is an urgent need for effective approaches for predicting and mitigating voltage violations as a result of random fluctuations in power injections. This work proposes a novel voltage monitoring approach based on low-complexity, data-driven probabilistic voltage sensitivity analysis. The usefulness of this work is not only in predicting voltage violations in unbalanced distribution grids, but also in opening up the door for optimal voltage control. Using system data and forecasts, the proposed approach predicts the distribution of system node voltages which is then used to to identify nodes that may violate the nominal operational limits with high probability. The method is tested on the IEEE 37 node distribution system considering integrated distributed solar energy sources. The method is validated against the classic load flow based method and offers over 95\% accuracy in predicting voltage violations.