Optimization of wind-PV hybrid power system based on interactive multi-objective optimization algorithm

• Published in: 2012 International Conference on Measurement, Information and Control Vol. 2; pp. 853 - 856
• Main Authors: Tianpei Zhou, Wei Sun
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2012
• Subjects: Batteries; Configuration optimization; Genetic algorithm; Genetic algorithms; Hybrid power systems; Multi-objective optimization algorithm; Optimization; Particle swarm optimization; Particle swarm optimization algorithm; Photovoltaic systems; Wind power generation; Wind-PV hybrid power system
• ISBN: 9781457716010; 1457716011
• DOI: 10.1109/MIC.2012.6273421

The configuration optimization of wind-pv hybrid power system may consider as a problem of multi-object optimization problem, the optimization objective as minimizing system installation cost, subject to power reliability. It was a key how to reasonably settle the configuration to give full play to the superiority of hybrid power systems. Interactive multi-objective optimization algorithm based on preference was proposed in the calculation of the cost (objective) function minimization, the populations, composition of target weight value, was optimized by interactive genetic algorithm, the weighted single objective function was optimized by particle swarm optimization algorithm, which was applied to configuration optimization of wind-pv hybrid power systems. The result shows that the economic performance of the hybrid power system is superior to that of both the single photovoltaic power system and single wind power system under the prerequisite for satisfying the load demand.