South Korean researchers enhance microgrid optimisation for power balancing

Scientists from South Korea’s Incheon National University have developed new optimisation model to improve microgrid operation in response to unexpected changes in power supply and demand.

A team of researchers from Incheon National University, led by assistant professor Jongheon Lee, has developed a new optimisation model to improve the operation of microgrids under uncertain conditions.

According to the researcher, the enhanced model not only boosts the efficiency and reliability of microgrids but also offers scalable solutions for the real world.

Microgrids, localised energy systems that provide stable power supply, especially in remote or disaster-prone areas, are becoming more essential with the transition to renewable energy sources, such as solar or wind.

However, managing these systems is challenging due to the uncertainties in energy supply and demand, such as power outages or fluctuations in energy usage, and stochastic islanding — situations where parts of the power grid unexpectedly become isolated, disrupting the power supply.

According to the researchers, traditional methods for optimising microgrid operations, such as multistage models, are computationally expensive and impractical for real-world use. These models consider different scenarios over time, but the complexity increases exponentially, making their application difficult at a large scale.

The researchers have simplified these models while maintaining their effectiveness, by reducing the number of possible scenarios and introducing a process called replanning, where the optimisation model adapts over time as new information emerges.

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The researchers add that the new microgrid optimisation model approach significantly reduced the computational burden, enabling them to be more efficient in real-world settings.

Said assistant professor Lee in a release: “Our goal was to create a method that makes microgrid operation more adaptable and cost-effective, especially in regions with unreliable grids or frequent disruptions.

“By simplifying the models and using replanning, we can achieve effective operation plan without the heavy computational cost.”

Microgrids can also act as essential backup energy source in remote and rural areas where stable grid access is unreliable, ensuring continuous power during outages or natural disasters. With the new models, these microgrids can operate more efficiently, minimising energy waste and overproduction.

Dr Lee explained: “As renewable energy sources like solar and wind are often unpredictable, balancing these fluctuations is crucial. Our models help manage these uncertainties, ensuring a more stable energy supply.”

Additionally, these solutions are beneficial to cities, where the energy demand is rising, and grids are under strain. Scalable optimisation models can improve the overall energy management. Adapting to changes in supply and demand in real time helps boost grid resilience, supporting the transition to sustainable energy. Moreover, these models are flexible, making them suitable for both small and large systems.

The original research findings were made available online in the paper Scalable optimization approaches for microgrid operation under stochastic islanding and net load.