Optimal Operation Of Wind-light-heat-hydropower Combined System In Solar Thermal Power Station

With the development of China's new clean energy industry,a large number of wind and solar power stations are connected to the power grid,while wind and solar power have the characteristics of volatility,intermittency and strong randomness,which bring great difficulties for the power grid to accept wind and solar power.How to effectively suppress the fluctuation of wind and solar energy and reduce the impact of new energy on the power grid has attracted the attention of many scholars.The photothermal power station with heat storage function provides a new solution to the problem of new energy grid connection with its high energy utilization rate and efficient energy storage function.However,complex energy conversion exists in the photothermal power station,which brings some difficulties to modeling and optimal scheduling.Therefore,how to schedule with reasonable strategy and how to find the solution of complex model are urgent problems to be dealt with.This paper first introduces the composition of the combined generation system and the basic principle of each part,and analyzes the role of the energy storage capacity of the photothermal power station in the combined system.This paper analyzes the power characteristics,actual output and the correlation with load change of wind power plant and photothermal power station,and especially introduces its energy storage system and energy storage model.Finally,the objective function and various constraints of the combined generation system are summarized,and the scheduling model of the combined generation system is established.In order to solve the single objective optimization problem with constraints established above,this paper improves the particle swarm optimization(CCRPSO)with resident particles by dynamically adjusting learning factors and inertial weights,aiming at the disadvantages of particle swarm optimization(PSO)which is prone to precocity and being trapped in the local optimum.By means of penalty function method,the constraint condition is integrated into the objective function and transformed into an unconstrained optimization problem.In order to verify the feasibility of the improved algorithm in this paper,the model and algorithm,the MATLAB software platform of simulation carried out to verify the established model,and since I joined united and did not j oin the solar-thermal power system output of each part before and after the improvement of algorithm,the convergence speed,and three aspects of the economic benefits of the combined power system dispatching comparative analysis,the results show that the proposed joint wind,sunlight,water,electric power system scheduling strategy can effectively improve the economic benefit of the joint system;In this paper,the improved particle swarm optimization algorithm with resident particles can significantly improve the convergence speed and accuracy of the algorithm.