Power Management for HRES using Model Predictive Control and Energy Storage Systems: A Comprehensive Analysis

Abstract

Renewable energy sources are pivotal in Industry 4.0, driving sustainable growth and reducing carbon footprints. They enhance energy efficiency and resilience, aligning with corporate sustainability goals. Incorporating diverse renewable energy sources into Hybrid Renewable Energy Systems (HRES) offers substantial potential for sustainably meeting rising energy demands. These systems enhance reliability and efficiency, aligning perfectly with corporate sustainability objectives. Embracing HRES positions companies at the forefront of innovation and environmental responsibility.

In the quest for sustainable energy solutions, the integration of Model Predictive Control (MPC) in Wind Energy Conversion Systems (WECS) and effective power management for Battery Energy Storage Systems (BESS) emerges as an advanced approach. The MPC addresses the limitations of conventional controllers by optimizing loading conditions and DC link voltage stability and minimizing power fluctuations. The advanced power management algorithm for BESS facilitates dynamic energy storage and distribution, enhancing system stability and reliability. The power generated from WECS-based MPC control reduces the power fluctuations when the battery is in charging mode.

The proposed work deals with the simulation analysis of MPC-based WECS and power management for WECS & BESS hybrid standalone power system to fed DC load and charging of BESS. Through simulation studies, the effectiveness of control strategies and MPC control operate satisfactorily with change in climatic conditions.