Enhancing Voltage Compliance in Distribution Network Under Cloud and Edge Computing Framework

Abstract

While high penetration of DER significantly helps facilitate the decarbonization of the electric power grid, it also brings unexpected operational challenges, among which voltage compliance has been a significant concern. To address this issue, the efficient load profile forecast, the operational framework and related strategies are critical challenges that need to be addressed urgently. Hence, this paper presents the cloud-edge computing-based framework to effectively operate a coupled medium-voltage (MV) and low-voltage (LV) distribution network. The high computational efficiency in cloud computing and low data latency in edge computing are presented and explored to coordinate the day-ahead and intraday operations ranging different framework layers. Under the framework, a customer-level forecasting algorithm is employed to predict both day-ahead and real-time load profiles. Next, an optimization model based on unbalanced-three phase optimal power flow is proposed and solved by an efficient and accurate linearization-based approach that considers the controllability of on-line tap changers, distributed static var generator and the PV inverters. Simulations based on an extensive mocked MV-LV distribution network and show the proposed forecasting method is adopted in the real-time operations in terms of high accuracy, and demonstrate the efficiency of the proposed method in enhancing the voltage compliance in the network.