Cleaner energy microgrids under market power and limited regulation in developing countries

A research team led by Elsa Bou Gebrael and Majd Olleik has published a novel AI-driven framework addressing a critical gap in energy access for developing nations. Their paper, 'Cleaner energy microgrids under market power and limited regulation in developing countries,' introduces a bi-level game-theoretic model. This AI system simulates a market where a profit-maximizing diesel generator company (DGC) controls a neighborhood microgrid, while a regulator sets price caps to protect households. The model uniquely accounts for the real-world market power of these private monopolies, a factor often neglected in purely techno-economic microgrid studies.

The model was applied to a high-resolution empirical case study from Lebanon, where unreliable national grids make diesel microgrids common. Results demonstrate that intelligent regulatory intervention—specifically capping prices and setting feed-in tariffs for solar—can dramatically shift the energy mix. Under base conditions, the model increased the renewable energy share from 0% to 60% by enabling households with solar PV systems to feed excess power into the microgrid. Crucially, at higher simulated budgets or greater solar adoption rates, the renewable share approached 100%, while also significantly boosting household economic surplus (HES). This provides a data-backed policy blueprint for regulators to leverage distributed solar and break the stranglehold of polluting diesel generators.