Multi-Objective Optimization for Volt-Var Parameter Tuning: Reducing Losses and Voltage Unbalance in Distribution Systems

The integration of distributed energy resources (DERs) into power grids requires new methodologies to optimize and efficiently control distribution network parameters. This paper presents a multi-objective optimization approach to enhance the operation of distribution networks with high penetration of distributed generation (DG). The proposed method jointly optimizes the active power output of dispatchable DG units and the Volt-Var control parameters of photovoltaic (PV) inverters to minimize power losses and voltage unbalance, ensuring compliance with the 2% limit set by Brazilian regulations. The optimization problem is solved using NSGA-II (Non-dominated Sorting Genetic Algorithm II) and MOPSO (Multi-Objective Particle Swarm Optimization), with three-phase power flow analysis performed using OpenDSS integrated into a Python-based framework. Simulations on the IEEE 123-bus system demonstrate that coordinated control of intermittent and dispatchable sources improves voltage profiles, reduces system losses, and significantly mitigates voltage unbalance.