Power Management for Hybrid Micro Grids System

The significant advancements in electric energy utilization necessitate continuous power saving and high stability by production, transmission, and distribution companies. Additionally, the large-scale provision of electrical energy has resulted in significant environmental damage due to harmful gas emissions and escalating fossil fuel prices. To address these challenges, renewable energy production units such as wind, photovoltaic cells (PV), and Fuel Cells (FC) have been introduced to electrical systems. However, electrical energy production from renewable sources faces instability and intermittency due to their inherent nature. To mitigate these issues, solutions such as smart grids (SG), energy storage systems (ESS), and advancements in control and management methods have been proposed in the electrical energy sector. This study presents an energy management system (EMS) as a control technique for managing power flow in response to demand, supply, and storage conditions. The proposed hybrid microgrid energy system integrates two renewable energy sources-fuel cells (FC) and wind-along with a supercapacitor energy storage system, modeled using MATLAB/Simulink. These components are interconnected via a DC-bus, connected to the AC-bus through a voltage source inverter (VSI), enabling connection to the main grid to supply diverse loads in both island (off-grid) and grid-connected (on-grid) modes. The energy management strategy aims to ensure continuous power supply to the load by dispatching power during production drops and absorbing power during increases. Stability of the power supply is ensured through management and control techniques including Particle Swarm Optimization (PSO) and the Proportional Integral method (PI). Converters are employed to maintain voltage stability on the DC_Bus. A case study is conducted to evaluate the system's performance in both connected and islanding modes, considering variable loads and constant wind speed. The results demonstrate the effectiveness of the selected control strategies across different microgrid scenarios.