Phase reassignment for load balance in low-voltage distribution networks

Abstract

Load balancing is one of the most widely used techniques to reduce losses and improve service quality in low-voltage networks. Many methods have been proposed, including the customer phase reassignment, which has multiple advantages. However, its application represents a real challenge if the data availability is limited (only a few variables from some nodes are measured). This paper presents a new method for load balancing on a three-phase feeder by switching the phase connection of single-phase customers. It is based on Deterministic Crowding, a variant of Genetic Algorithms with few and easily adjustable parameters. In contrast to related works, we establish an imbalance target value and minimize the number of customers required to switch. The proposed method requires the phase current profiles from only a percentage of the customers, reducing the number of smart meters necessary and the related investment. The method was validated using real data, analyzing different scenarios with different percentages of measured customers compared on the basis of imbalance index, neutral current, and transformer lifespan reduction. Results show a significant improvement in load balancing with few changes, even when only 30% of customers are measured.