Optimal Power Flow Scheduling for All-electric Ship Power System based on Improved Whale Algorithm
摘要
As the shortage of fossil fuels intensifies, governments are increasingly focused on reducing fuel consumption. Given that the shipping industry consumes substantial amounts of fuel annually, it is imperative to minimize this consumption. The advent of all-electric ships represents a promising solution to the current environmental crisis. However, the computational complexity of energy scheduling poses significant challenges in achieving optimal scheduling for all-electric ship power systems. To address this critical issue, an optimization strategy utilizing the Improved Whale Optimization Algorithm (IWOA) is proposed. First, a model of the all-electric ship power system, which includes the generator, propulsion system, and service load, is established. Building on this model, an optimization strategy is developed to reduce operational costs and power losses. To enhance the performance of the Whale Optimization Algorithm (WOA), the Levy flight strategy and the concept of average individuals are introduced to mitigate the risk of converging to local optima and to facilitate escape from such conditions. Finally, two distinct cases are tested to evaluate the effectiveness of the proposed optimization strategy. Upon verification, the improved whale algorithm effectively avoids the issue of local optima that commonly affects traditional whale algorithms, thereby enhancing the stability of the algorithm. Furthermore, the algorithm demonstrates its capability to address the energy scheduling problem, achieving a minimum reduction of