M-ulti-objective operation strategy for a PV-integrated hybrid UPS-ESS using predictive heuristics and receding-horizon control-Seong-Soo Jeong-Department of Electrical and Computer Engineering The Graduate School Sungkyunkwan University

 

Abstract 

 A Multi-Objective Operation Strategy for a PV-Integrated Hybrid UPS–ESS using Predictive Heuristics and Receding-Horizon Control In recent industry, the adoption of renewable energy using photovoltaics (PV) has been promoted as part of efforts to address climate change. In precision manufacturing facilities, an uninterruptible power supply (UPS) is required to respond to momentary voltage sags and outages, and an energy storage system (ESS) is essential to compensate for the intermittent output of PV. Accordingly, this study investigates a multi-objective control strategy for a hybrid UPS–ESS (HUE) system integrated with PV. Short-term forecasts of load and PV generation are performed using a Long Short-Term Memory (LSTM) model. Based on these forecasts, the minimum state of charge (SOC) required to secure HUE reserve power and the target SOC for system operation are calculated at each time step. Subsequently, the weights of each objective function are derived using Multi-Criteria Decision Making (MCDM), and a real-time operation strategy is constructed by combining predictive heuristics and Receding-Horizon Control (RHC). The predictive heuristic determines charge and discharge actions under operational constraints, while RHC updates the control decision at each time step by incorporating both forecasted and actual values. The proposed control aims to maintain an adequate SOC headroom for UPS readiness, suppress grid peaks to reduce electricity costs, and limit unnecessary SOC fluctuations that accelerate battery degradation. Simulation results demonstrate that the proposed multi-objective operation strategy combining predictive heuristics and RHC outperforms the comparison scenarios in terms of SOC stability, grid operation reliability, and cost efficiency.