Foreign-Developed PSO for Power System Optimization Focusing on Fuel Consumption Reduction

The foreign-developed Particle Swarm Optimization (PSO) algorithm is applied to power system optimization with a primary focus on reducing fuel consumption. Implementing this optimization algorithm enables improved energy utilization efficiency through strategic adjustments to power system control parameters, thereby decreasing fuel usage and minimizing environmental impact. The PSO algorithm operates as a swarm intelligence-based optimization technique that mimics bird flock foraging behavior to search for optimal solutions. In power optimization scenarios, developers typically implement PSO using fitness functions that calculate fuel consumption rates, with particle positions representing potential control strategies. Key implementation components include velocity updates using cognitive and social parameters, position adjustments through iterative calculations, and global best solution tracking. The algorithm facilitates identification of optimal control strategies by continuously evaluating solutions against fuel efficiency metrics, ultimately achieving significant fuel consumption reduction targets through systematic parameter optimization.