A Modular Algorithm Based on the Minimum-Cost-Path Problem for Optimizing LTC Operations in Photovoltaic Integrated Distribution Systems

Abstract

This paper presents a novel modular voltage control algorithm for optimal scheduling of a distribution system’s load tap changers to minimize the number of tap changes while maintaining a voltage deviation (VD) around a desired target. To this end, a bi-objective optimal voltage regulation (OVR) problem is addressed in two distinct stages. First, the operational constraint on the load tap changer is removed to form a single-objective OVR problem relating to the voltage. The solution obtained in this stage is ultimately utilized to determine the penalty value assigned to the distance from the optimal (solely in terms of voltage) control value. In the second stage, the optimal scheduling problem is formulated as a minimum-cost-path problem, which can be efficiently solved via dynamic programming. This approach allows the identification of optimal scheduling that considers both the voltage-related objective as well as the number of load tap changer switching operations with no added computational burden beyond that of a simple voltage optimization problem. The method imposes no restriction on the load tap changer’s operation and is tested under two different target functions on the standard IEEE-123 test case. The first attains a nominal voltage with a 0.056 p.u. voltage deviation and the second is the well-known conservation voltage reduction (CVR) case with a 0.17 p.u. voltage deviation. The method is compared to an evolutionary-based algorithm and shows significant improvement in the voltage deviation by a factor of 3.5 as well as a computation time acceleration of two orders of magnitude. The paper demonstrates the effectiveness and potential of the proposed method as a key feature in future cutting-edge OVR methods.