OPTIMIZED PI CONTROL FOR POWER FLOW AND DC LINK VOLTAGE REGULATION IN A PV-WIND-BATTERY MICROGRID USING GREY WOLF OPTIMIZATION

• Date: 2025
• Main Authors: Mogilicharla, Veera Narasimha Murthy, Gudapati, Sambasiva Rao
• Format: Article
• Language: English
• Published: Institute of Renewable Energy National Academy of Sciences of Ukraine 2025
• Subjects: Grey Wolf Optimization (GWO); PI Controller Tuning; Power Flow Control; DC Link Voltage Regulation; PV-Wind-Battery Microgrid; Voltage Source Converter (VSC) Control
• Online Access: https://ve.org.ua/index.php/journal/article/view/572
• Journal Title: Vidnovluvana energetika

Microgrids have become essential in modern power systems, enabling reliable and sustainable energy distribution while operating independently or with the main grid. The growing integration of renewable sources like photovoltaic (PV) and wind energy, along with battery storage, necessitates advanced control strategies for efficient power management and grid stability. This paper presents an optimized power flow control strategy for a PV-Wind-Battery hybrid microgrid using a Voltage Source Converter (VSC) to regulate active and reactive power while maintaining DC link voltage stability. A Proportional-Integral (PI) controller plays a crucial role in ensuring system performance under varying conditions. However, conventional PI tuning is challenging due to the nonlinear nature of renewable energy sources. To overcome this, an optimized tuning approach based on the Grey Wolf Optimization (GWO) algorithm is proposed. Inspired by the social structure and hunting behaviour of grey wolves, GWO efficiently balances exploration and exploitation to determine optimal control gains. The PV system employs Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT), while an adaptive P&O MPPT strategy is used for wind energy to maximize power extraction. The battery storage system dynamically switches between charging and discharging to maintain power balance. The GWO-based PI controller is compared with conventional methods, including Ziegler-Nichols (ZN), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Simulation results demonstrate superior transient response, reduced steady-state error, and minimized power fluctuations. Additionally, Total Harmonic Distortion (THD) analysis confirms lower harmonic distortion, enhancing power quality and system reliability, making GWO a promising approach for microgrid optimization.