Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation

Abstract

Electric spring (ES) is a novel smart grid technology developed to facilitate the integration of renewable generation by controlling the demand of non-critical loads (NCLs). The utilization of ES to provide a single service such as voltage or frequency regulation, validated in a setup consisting of a single ES, has been extensively investigated. However, to take full advantage of this technology, it is necessary to develop control strategies to coordinate the operation of multiple distributed ESs to provide multiple services in power systems. To this end, this paper presents a rolling-optimization control strategy to coordinate the operation of multiple ESs for voltage regulation, congestion management and cost minimization of the real-time deviations from the scheduled energy exchanges with the grid in microgrids with renewable generation. The strategy is for centralized implementation, and includes a probabilistic optimal power flow-based optimization engine that finds the voltage references of ESs for each control interval taking into account generation variability and uncertainties. NCLs consist of electric water heaters, which are modeled taking into account physical constraints and the hot water demand. Simulations were carried out in two test systems with 14 and 33 buses.