A Unified PSO–RHC Framework for Multi-Objective Optimization of PV–BESS Operation in Distribution Systems Under Uncertainty
Year: 2026
Type: article
Abstract: High photovoltaic (PV) penetration introduces rapid variability, voltage deviations, and increased real-power losses in distribution networks, necessitating control strategies that remain effective under forecast uncertainty. This paper presents a unified Particle Swarm Optimization-based Receding-Horizon Control (PSO-RHC) framework for optimal coordination of multiple Battery Energy Storage Systems (BESSs) in a PV-rich distribution feeder. The controller employs a receding-horizon structure—using horizon-based forecasts, constraint enforcement, and stepwise decision updates—while PSO serves as the optimization engine that computes BESS power setpoints at each prediction step. Deterministic PV and load forecasts are perturbed with stochastic noise to emulate realistic uncertainty, and each candidate solution is evaluated using a forward–backward sweep load-flow model. Simulation results on the IEEE-69 bus system show that the proposed PSO-RHC scheme reduces total daily energy losses from 1467.50 kWh to 1310.19 kWh (10.72% reduction), improves weakest-bus voltages by 1–4%, and maintains all BESS units within operational limits. The normalized objective components remain small (below 0.5%), indicating balanced operation without excessive cycling. These findings demonstrate the effectiveness and simulation-level effectiveness of PSO-based receding-horizon control for enhancing distribution-network performance under uncertain and dynamic PV conditions.
Source: Mathematics
DOI: 10.3390/math14142584
Authors: Ahmad Eid, Sulaiman Almohaimeed
Institution: Qassim University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7169603259