The Application Of Ant Colony Algorithm In Wind-solar Complementary Power System

Because of the shortage of fossil fuels,people becomes everincreasingly attention to the using of new energy. Solar energy and wind have good prospects in the new energy resources power generation.They are both clean and renewable resources but they also have the weakness of energy density low and the characteristics of strong randomicity.Because of this,wind or solar power difficult to have a stable power output alone.Wind-solar complementary system rational utilization of the wind and solar natural complementary for load provides a fairly good electrical energy. The complementary system include wind-power unit,solar power units and hybrid energy storage unit.How do we make the wind and solar complementary function get sufficient play on the premise of assurance of most economic. It is the important indicators to measure system superiority.Increase the power supply reliability and reduce system costs is the optimization of two complementary scenery conflict objectives.This paper first introduce some basic knowledge of solor power unite and the relationship of photovoltaic array angle and pv array electricity output,some basic knowledge of wind-power unit and mainly relationship of the installation height and the air blower fan capacity,energy storage mode, energy storage type characteristics in hybrid energy storage unit and the method of battery capacity calculation.Then established the system optimization mathematical model.Ant colony algorithm is introduced to optimize system loss of power supply probability and cost.The fan number,solar photovoltaic array parallel, the parallel battery number, fan installation height and solar obliquity for are optimal variables.And confirm the scope of these variables. Ant colony algorithm is a new kind of simulated evolutionary algorithm,it has the advantage of simple modle, better adaptable, positive feedback and solution global. This paper established the system optimization diagram apply parameter optimization and business problems cleverly combined together. According to the fitness between ant and objective function for pheromone updates.Using ant colony cooperation mechanism for global search search optimal variable winging good path. Rank the ants after the completion of the iteration.it is a optimal solution set when the topσant corresponding variables formed together. Rank the ants after the completion of the iteration.It is a optimal solution set when the topσant corresponding variables formed together.this paper draw piont for theσants LPSP and CWPB,then determine the best ant though tangent method.Last,the paper enumerate calculation example for verifing the suggested algorithm, summarizes the full-text and prospec tthe exsited problems.