Fractional-Order Particle Swarm Optimization for Sustainable Energy Management

Sustainable energy systems, which encompass both renewable energy and energy efficiency, aim to reduce reliance on finite resources such as fossil fuels while minimizing negative impacts on the environment and promoting economic and social development. Wind energy, in particular, is an increasingly important renewable source of energy that can help combat climate change and is cost-competitive with traditional sources of electricity. To maximize energy production, optimizing wind turbine layout is crucial and involves determining the optimal placement and configuration of turbines within a given space. This article proposes a novel approach called fractional-order particle swarm optimization (FOPSO) to address this problem and demonstrates that it outperforms other state-of-the-art optimization algorithms in terms of both solution quality and power generation efficiency.