Microgrid Optimization: Efficient, Reliable, Equitable, and Autonomous Renewable Energy

Overview

Microgrids are small power grids that generate their own electricity and supply a local load. Renewable microgrids must find a way to distribute the variable energy generated throughout the day to the changing load and storage. Microgrid optimization includes implementing techniques to make this balance as energy-efficient as possible. My project models a microgrid at a small scale to observe the balance between generation, storage, and load when optimization strategies like maximum power point tracking (MPPT), and a battery safety feedback loop are implemented to make an autonomous and efficient renewable microgrid. Microgrids are a versatile and customizable way to integrate renewable energy and achieve energy equity. Microgrids will help us reach our sustainability goals and make energy more accessible and adaptable to the diversity of people's lifestyles and environments. My final model consisted of 2 30W solar panels for generation, 3 5V and 1 12V fans for the load, and 6 3.7V LiPo batteries as storage. One of the central goals of this project was to implement optimization strategies to make the microgrid as efficient and safe as possible, which is crucial to its longevity and reliability. The main optimization strategies I implemented were Maximum Power Point Tracking (MPPT) and a battery safety feedback loop. Being efficient with the power generated was critical, especially considering this project was done in winter. MPPT calculates the voltage and current the system should run at to yield the most power. MPPT was implemented at the center of the renewable microgrid, the Solar Power Manager, which moved and stored power where it was needed. In high irradiance, solar energy powered the load and charged the batteries; In the darkness, the battery-powered the load. If solar generation wasn't sufficient, those batteries would also power the load. In shaping the loads, the 5V load fans were programmed to peak in the morning and night, modeling a residential load. The 12V load, which represented an industrial load, ran at a more constant load but would change in accordance with the batteries' voltage, facilitated by the battery safety feedback loop. If the battery voltage was high, the industrial load ran at full capacity; if the battery voltage was low, the industrial load decreased to half or completely shut off. The Solar Power Manager had an efficiency of 80%. From my model, I was able to display how all the elements of the microgrid interacted in different conditions over many days as the model evolved.

Competition history

• AJAS 2025 Category not listed

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