Research On Multi-Objective Optimization Of Trough CSP System Based On Chaos Genetic Algorithm

With the consumption of primary energy and the deterioration of the environment,people begin to make use of new energy to generate electricity and connect to the grid.China has a unique advantage in the quantity of solar energy and wind resources,but due to the vast geographical area of China,there are great differences in climate change and mountain and river landtorms throughout the year,which are especially limited by the natural environment.Combined grid connection of landscape can slow down the phenomenon of wind and light abandoning and improve the utilization rate of energy.Based on the above background,the main research contents of this paper are as follows:In this paper,the power generation principle and basic structure of the trough photothermal power station are described at first,and the mathematical model of its heat collecting part,heat storage part and power generation part is established with MATLAB simulation platform to form a complete basic model of the trough photothermal power station.The illumination intensity of typical days in four seasons was selected for simulation input.T he results show that different light intensity has great influence on the output of trough solar power station.Then,the genetic algorithm is improved.Aiming at the disadvantages of genetic algorithm,such as high dependence on initial value,slow convergence speed and easy to fall into local optimum,Logistic mapping can cause chaos in feasible region and fast convergence speed,etc.,to improve the genetic algorithm of chaos,and put forward chaos geneticalgorithm.Different evaluation functions and testing systems are used to verify the feasibility and superiority of chaos genetic algorithm.The results show that the chaotic genetic algorithm converges quickly and jumps out of the local optimum easily.Then,a multi-objective optimization model for a combined wind-solar power generation objective function of maximum absorption,minimum peak/valley difference of load and maximum benefit.The analytic hierarchy process(AHP)is used to convert multiple targets into a single target to determine the influence of different weight ratios on the optimization results.Then,the superiority of chaos genetic algorithm in multi-objective optimization of power system is verified under IEEE-33 by using the objective function with the same weight ratio.Finally,this paper takes a certain area of Qinghai province as the background,carries on the multi-objective optimization of the optimization model of scenery combined power generation to verify the practical example.The effect of different proportional weights on multi-objective optimization is verified.