Optimization On The Scheduling Of The Heliostat Field In A Solar Tower Power Plant

Solar tower power system is a kind of new energy utilization method suitable for large-scale power generation,and has broad development prospects.Among all the subsystems in it,the concerntrating and receiving subsystem composed of the heliostat field and the receiver is the front end of the whole power station.Its performance and efficiency have great influence on the operation of the power plant and even the total power output.The scheduling of the heliostat field directly determines the position of the aiming point on the receiver of each heliostat.In order to ensure the stable,efficient and safe operation of the heliostat field,it is of great practical significance to optimize the heliostat field scheduling to offer a reference for the actual operation of power plants.In this thesis,the scheduling of the heliostat field in a solar tower power plant is optimized.The main contributions of this thesis are as follows.The model describing the enery consumption generated by heliostat rotation is established.Based on the models,an optimization model of the heliostat field scheduling in a single moment is proposed.In this optimization model,the optimal objective is to maximize the total received energy minus the extra energy consumed when the aiming points change compared with the last scheduling time,and the uniform flux distribution is treated as a constraint.An Adaptive Genetic Algorithm with multi-bits mutation is designed to solve the optimization problem.The comparative analysis shows that the proposed method can achieve the desired objectives and is conducive to energy conservation.Considering the solving speed requirement of the heliostat field scheduling optimization problem and the potential parallelism of the genetic algorithm,the existing GPU and CUDA platform are used to implement the genetic algorithm in parallel,which greatly improves the real-time performance of the heliostat scheduling.The simulation results show that the optimal solution after GPU acceleration can improve the solving speed while ensure the solving quality.An optimization method of the heliostat field scheduling interval is also proposed,in which the total received solar energy minus the weighted total extra energy consumed during a desired optimization time period is maximized while the the uniform irradiance distribution is treated as a constaint.The original optimization problem is transformed into a nested form under certain conditions.The outer optimization problem is solved by tabu search algorithm and the inner optimization problem is the optimization problem of heliostat field scheduling in a single moment.The optimized scheduling interval can improve the efficiency of the power plant effectively.Finally,the influence of different parameters on optimal scheduling interval is analyzed.