Probabilistic Unit Commitment in Renewable Smart Islands Incorporating Plug-In Electric Vehicles and energy storage devices

The importance of optimal unit commitment in microgrids lies in its ability to balance the fluctuating supply and demand, ensure efficient utilization of available resources, and maintain grid stability while minimizing costs and maximizing renewable energy integration. Thus, the problem of probabilistic unit commitment in renewable smart islands, incorporating plugin electric vehicles (PEVs), photovoltaic units, and energy storage devices (ESDs), is of significant importance for achieving efficient and reliable operation of renewable energy systems. This work aims to address the challenges posed by uncertainty in renewable energy generation. The unscented transform is used to capture and model this uncertainty, while the teacher learning based optimization method serves as the optimization algorithm. The proposed methodology is evaluated using an IEEE standard test case to assess its effectiveness. The results demonstrate the successful optimization of unit commitment decisions and the incorporation of the dynamic characteristics of PEVs and ESDs.