Control of microgrids is a crucial aspect in ensuring their proper functioning and optimal performance. It involves the implementation of various control strategies and algorithms to manage the power flow, balance supply and demand, and maintain system stability.
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During the presentation of the project, Cape Verde''s National Director for Industry, Trade and Energy, Rito Évora, announced that the energy storage centre is scheduled to be operational by 2030, with the aim of injecting 7% of renewable energy into the national public grid and.
In this project the monitoring system is based on the Graphical User Interface which provides the facility to monitor and control the micro grid from remote location.
This study analyzes how we can monitor different variables, such as the active power, reactive power, power factor, total harmonic distortion and frequency in the loads of a microgrid, using high-precision power meters.
These self-contained power systems combine renewable sources like wave, solar, and wind energy with advanced control systems - essentially creating electrical islands that dance on the ocean's surface.
The process typically includes: Mounting solar panels and routing wiring to a central electrical point. Connecting the battery storage system with inverters and charge controllers.
To enhance the controllabil-ity and flexibility of the IBRs, this paper proposed an adaptive PQ control method with a guaranteed response trajectory, combining model-based analysis, physics-informed reinforcement learning, and power hardware-in-the-loop (HIL) experiment.
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