Minimal Investment Installation Planning of Smart Meters for Load Balancing Using a Data‐Driven Approach

Abstract

Switching the phase of selected single-phase customers is an effective way to mitigate the load imbalance problem in low-voltage networks. Methods for finding a better phase configuration inevitably require measuring individual load consumption and prior knowledge of the customer-transformer connection. However, during the early implementation stages of smart grids with low smart meter penetration, this information is often incomplete or unavailable. Only a few data-driven approaches can be applied in these situations. This paper presents a new strategy for load balancing under limited smart meter availability conditions. It proposes acquiring, installing, and using the minimum number of smart meters to reduce the required investment. Using data from the newly installed meters, the methodology estimates customers' phase and substation connections. It also identifies those that should be switched to reduce the imbalance while minimizing the number of changes. The proposed method is validated through simulations using real data from different neighborhoods in Tucumán, Argentina. Results show that significant imbalance reduction can be achieved by installing smart meters for only 30% of customers and switching the phases for up to 15% of them.