Enhancing Energy Storage System Charging Controller for Smart Grids Stability: a Dragonfly Optimization Approach

Abstract

This study presents a new approach using the Dragonfly Algorithm (DA) optimization to improve the Energy Storage System (ESS) controller in a grid-tied Smart Grid (SG). The main objectives are to improve the voltage stability in the SG while minimizing the battery discharge rate. As a result, this approach improves the performance and lifetime of Battery ESS (BESS) connected to SGs by mitigating the effects of a high charge/discharging process frequency. Connecting BESSs and renewable energy is essential to ensuring energy supply continuity and, hence, robust grid functioning. The proposed method achieves a 30% reduction in battery discharge rate (from 80% to 50%), maintains grid voltage stability within a 4 V deviation, and keeps the energy price constant at 30 cents/kWh. This paper presents an optimization of SG operation control by improving BESS charging performance during fluctuations in energy supply and demand. The model simulation of SG connected to a 5 kV medium distribution system shows that the DA-optimized controller provides grid voltage stability with less depth of discharge in BESS at the same energy cost.