Optimal Design of Passive Power Filters Based on Knowledge-Based Chaotic Evolutionary Algorithm

Design of passive power filters shall meet the demand of harmonics suppression effect and economic target. However, traditional experience-based method has difficulty achieving the optimal solution because it only takes technology target into account. To solve the problem, two objectives including minimum total harmonics distortion of current and minimum cost for equipments are constructed. Taken capacitors in passive power filter as variables, such non-dominant objectives are transformed into single weighted objective. In order to achieve the optimal solution effectively, a novel evolutionary algorithm with knowledge-based chaotic mutation is proposed. The scale of mutation is adaptively adjusted based on logistic chaotic sequence according to current implicit knowledge describing the dominant space. Taken three-phase full wave controlled rectifier as harmonic source, simulation results show that filter designed by the proposed algorithm have better harmonics suppression effect and lower investment for equipments than filter designed by experience-based method.