Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Abstract

Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs to automate and optimize the three-phase balancing decision making, this paper introduces a robust look-ahead optimization framework that pursues balanced phases in the presence of demand-side uncertainties. We show that look-ahead moving window optimization can reduce imbalances among phases at the cost of a limited number of phase swapping operations. Case studies quantify the improvements of the proposed methods compared with conventional deterministic phase balancing. Discussions on possible benefits of the proposed methods and extensions are presented.

Phase Swapping Load Balancing Algorithms, Comprehensive Survey

“…The method reaches to 14.3% phase imbalance degree less than that achieved in the case of rich-data low voltage networks. In [33], the authors applied the robust optimization technique to lessen the unbalancing in the feeders with a minimum number of swapping for the low voltage networks with uncertain data. The uncertainty is coming from the penetration of PVs and the electric vehicle in the distribution networks that regarded a variable load with high inconstant data.…”

Optimal placement of phase‐reconfiguration devices in low‐voltage distribution network with residential PV generation

“…As residential customers are mostly regarded as loads with constant powers, the presented method may lead to an ineffective strategy. A robust method is presented in [16] to further take load profile uncertainty into account. However, network constraints were not taken into account either, which may lead to violated operational constraints.…”