Strategic Energy Storage Allocation In Distribution Network For Energy Cost Reduction And Voltage Profile Improvement

The integration of renewable energy sources (RES) and battery energy storage systems (BESS) into electrical power distribution systems (EPDS) is growing rapidly, but presents challenges like increased energy losses, voltage deterioration, and rising costs. This paper proposes a multi-objective optimization framework for optimal BESS allocation in EPDS to reduce costs and improve voltage profiles. Using a genetic algorithm, Non-dominated Sorting Genetic Algorithm III (NSGA-III), it balances objectives while considering system and battery constraints. Python’s Pandapower and DEAP (Distributed Evolutionary Algorithms in Python) libraries are used for power flow analysis and optimization. The model is validated on a medium-voltage radial network with high renewable energy sources (RES) penetration, showing significant showing significant gains in network performance and highlight the potential for battery energy storage systems (BESS) to become standard components in modern power systems.