OPTIMIZATION OF RENEWABLE ENERGY STORAGE SYSTEMS FOR STABLE POWER MANAGEMENT

Abstract

The increasing integration of renewable energy sources into electrical power networks has created new challenges in maintaining a continuous balance between generation and demand. Solar photovoltaic and wind generation are environmentally attractive, but their output varies with weather conditions and can introduce voltage fluctuations, frequency deviations, renewable-energy curtailment and increased stress on distribution networks. Energy storage systems provide an effective means of addressing these problems by absorbing surplus renewable generation and releasing stored energy when generation is insufficient. However, the technical benefit of storage depends strongly on its capacity, charging and discharging schedule, state-of-charge limits and control strategy. This study investigates an optimization-based approach for renewable energy storage management in a distribution network containing photovoltaic, wind, battery storage and variable electrical loads. A multi-objective optimization model is developed to reduce grid power fluctuations, voltage and frequency deviations, renewable-energy curtailment, battery degradation, and peak power demand. A modified IEEE 33-bus distribution network is considered as the simulation platform, while a particle swarm optimization-based procedure is employed for determining suitable storage capacity and operational scheduling. The optimized system is compared with renewable generation without storage and with a conventionally controlled battery storage system. Simulation results indicate that coordinated optimization of storage substantially improves voltage regulation, reduces frequency variation, decreases peak grid demand, and permits a larger proportion of renewable generation to be used locally. The study demonstrates that energy-storage optimization should consider both economic and stability-related objectives rather than focusing only on storage capacity. Such coordinated control can contribute to more reliable, flexible, and renewable-intensive electrical distribution systems.