Study On Heliostat Aim Point Optimization Strategy Of Concentrating Solar Power Tower System

With the widespread application of solar energy,concentrating solar power technology gets a vigorously development,as one of the forms of development and utilization of solar energy.The technology uses several heliostats to collect sunlight on the concentrator,and uses thermal energy of the working medium to drive the steamer and then drive the generator to generate electricity.Heliostats and concentrator are used to concentrate and collect light and complete the photothermal conversion process.Its efficiency and performance have a great impact on whole power system.Meanwhile,the aim point optimization strategy determines concentrating efficiency and working state of concentrator.In order to ensure the safe and efficient of the concentrator and heliostat field,this study dose a in-depth research on heliostat aim point optimization strategy of concentrating solar power tower system.The works are as follows:(1)Based on knowledge of automatic control theory,this paper analyses control principle and method of heliostat aim point optimization system.And the shape and heat quantity of reflected spot of heliostat are analyzed with considering the non-parallel characteristics of sunlight,cosine effect and atmospheric transmittance.(2)Considering that solar power tower system is susceptible to the influence of time,weather and other factors,this paper divides heliostat aiming optimization process into "static optimization" and "dynamic optimization",and uses "aiming point moving method" to achieve"dynamic optimization" process.Based on heat flux of the concentrator’s surface,this paper defines two parameters,i.e.,heliostat field heat spillover rate and approximate standard deviation of heat flux.And establishes a double optimization function with minimum heat flux spillover rate and minimum approximate standard deviation of heat flux to ensure the safe and efficient operation of the concentrator.(3)By analyzing and comparing the existing optimization algorithms,this paper uses antcolony algorithm to solve "static optimization" process and BP neural network is used to solve"dynamic optimization".And establishes optimization model of heliostat aiming system based on these two algorithms and compiles optimization program for different interference factors.The optimization results show that the optimization function and the optimization algorithm in this study have high accuracy and feasibility to satisfy safe and efficient operation of concentrator,and have an important significance for improving the safe and reliable operation of the whole power generation system.