Microgrid management and control system during grid connected and autonomous operation modes

• Control Objectives • Enhancing MPPT for Photovoltaic Systems: Improve energy extraction efficiency through an advanced MPPT system. • Optimizing MPPT for Wind Systems: Eliminate the need for a wind speed measuring device in the TSR method, while maintaining performance. • DC-Link Voltage Regulation: Ensure stable microgrid operation by accurately controlling the DC-link voltage. • Energy Management Requirements and Criteria • Reducing Operational Costs: Optimize energy use and minimize wastage to lower costs. • Load Prioritization: Distribute energy efficiently by prioritizing loads based on importance and available electrical energy. • Improved Generation System Operation: Enhance solar and wind power generation efficiency by controlling output power during transitions out of MPPT mode, reducing the need for damping loads. Microgrids are recognized as essential for integrating renewable energy sources, offering enhanced efficiency, increased resilience, and reduced dependence on centralized power systems. An integrated solution was developed by combining advanced control and energy management systems for hybrid microgrids operating in both isolated and grid-connected modes. The main contributions include: (i) a novel control strategy designed to enhance Maximum Power Point Tracking (MPPT) for wind turbine and photovoltaic (PV) systems through the application of Artificial Neural Networks (ANN). This strategy enables maximized energy utilization, precise regulation of DC-link voltage, reduced reliance on additional sensors, and improved dynamic and long-term performance; and (ii) an energy management system configured to ensure reliable operation by optimizing load prioritization and balancing energy supply and demand. In contrast to conventional approaches, the proposed system eliminates the need for damping loads to maintain power balance by implementing a dedicated mechanism that exits MPPT mode during surplus energy production. Validation was conducted through comprehensive simulations under various climatic conditions, confirming reduced power ripples, improved energy efficiency, accurate DC-link voltage regulation, and effective power balancing-thereby ensuring reliable and efficient microgrid performance.

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Publication Details

Journal
Franklin Open
Published
2025-08-28
DOI
https://doi.org/10.1016/j.fraope.2025.100346
Citations
1
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.21
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article

Microgrid management and control system during grid connected and autonomous operation modes

Abdelhadi Raihani, Khaled H. Ahmed, Kissaoui Mohammed, ATIFI Youness et al.
1 citations
Franklin Open
Microgrid Control and Optimization
1.21
article

Microgrid management and control system during grid connected and autonomous operation modes

Abdelhadi Raihani, Khaled H. Ahmed, Kissaoui Mohammed, ATIFI Youness, ERRAKKAS Khalid
article en
1 citations

Abstract

• Control Objectives • Enhancing MPPT for Photovoltaic Systems: Improve energy extraction efficiency through an advanced MPPT system. • Optimizing MPPT for Wind Systems: Eliminate the need for a wind speed measuring device in the TSR method, while maintaining performance. • DC-Link Voltage Regulation: Ensure stable microgrid operation by accurately controlling the DC-link voltage. • Energy Management Requirements and Criteria • Reducing Operational Costs: Optimize energy use and minimize wastage to lower costs. • Load Prioritization: Distribute energy efficiently by prioritizing loads based on importance and available electrical energy. • Improved Generation System Operation: Enhance solar and wind power generation efficiency by controlling output power during transitions out of MPPT mode, reducing the need for damping loads. Microgrids are recognized as essential for integrating renewable energy sources, offering enhanced efficiency, increased resilience, and reduced dependence on centralized power systems. An integrated solution was developed by combining advanced control and energy management systems for hybrid microgrids operating in both isolated and grid-connected modes. The main contributions include: (i) a novel control strategy designed to enhance Maximum Power Point Tracking (MPPT) for wind turbine and photovoltaic (PV) systems through the application of Artificial Neural Networks (ANN). This strategy enables maximized energy utilization, precise regulation of DC-link voltage, reduced reliance on additional sensors, and improved dynamic and long-term performance; and (ii) an energy management system configured to ensure reliable operation by optimizing load prioritization and balancing energy supply and demand. In contrast to conventional approaches, the proposed system eliminates the need for damping loads to maintain power balance by implementing a dedicated mechanism that exits MPPT mode during surplus energy production. Validation was conducted through comprehensive simulations under various climatic conditions, confirming reduced power ripples, improved energy efficiency, accurate DC-link voltage regulation, and effective power balancing-thereby ensuring reliable and efficient microgrid performance.

Franklin OpenVol. 12
Université Hassan II Mohammedia (MA), University of Hassan II Casablanca (MA)
Affordable and clean energy
Openalex Percentile: Top 17%
Microgrid Control and Optimization
1.21
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