Distributed Generator Rescheduling Optimalization In Sangihe Island Using Unit Commitment Based on Firefly Algorithm

Optimization problem in remote areas had been a problem that could not be fully fixed and adjusted the field. This research focuses on optimizing distributed generator rescheduling in Sangihe Island, a remote region with power generation and distribution challenges. The primary aim is to enhance efficiency, reliability, and cost-effectiveness. This research proposes integrating the Unit Commitment (UC) problem with the Firefly Algorithm (FA). Sangihe Island's power system comprises diverse generators, including renewables (photovoltaic) and diesel. To tackle dynamic conditions, we meticulously formulate the UC problem, addressing on/off states and power outputs while considering economic and technical constraints. We use the Firefly Algorithm, renowned for its ability to handle complex problems efficiently. Real-world data validation demonstrates substantial improvements in operational efficiency, cost reduction, and reliability. Comparative analysis confirms the Firefly Algorithm-based Unit Commitment's superiority in addressing the island's unique challenges. From the result, the approach offers an innovative method for Sangihe Island's distributed generator rescheduling, had increased the cost efficiency by IDR15175663 per day or 5.44% more cost efficient for an entire island.