Research On Optimal Load Distribution Of Thermal Power Units With Large Scale Wind Power Connected To Power Grid

With the increase of energy demand and fossil energy consumption,the development of clean energy is imperative.In China’s energy policy,with the vigorous development of the power industry,large-scale wind power integration into the grid has become the main trend,and the problem is the impact of large-scale wind power integration on the stable operation of the power system.In the case that the traditional unit commitment problem can not meet the development needs,the research on wind power thermal power unit commitment problem must keep pace with the times to meet the new challenges Challenge.In this context,this paper mainly does the following research:1.The characteristics of thermal power and wind power are analyzed,and the wind power prediction model is established based on the random ness and intermittence of wind power.On the basis of traditional unit commitment research,the wind power thermal power unit commitment model is established by considering the characteristics of wind power,so as to establish positive and negative rotatin g reserve constraint conditions to overcome the impact of wind power integration,and lay the foundation for subsequent research.2.Considering that it is necessary to optimize the start-up and stop states and load distribution of units respectively in the process of unit commitment problem processing,the hierarchical solution thinking of Benders Decomposition algorithm is very suitable for solving the unit commitment problem.In this paper,an improved Benders Decomposition algorithm is proposed to solve the wind turbine thermal unit commitment problem.The start-up and stop states of units are determined by the main problem,and the load distribution of units is solved by the subproblem The algorithm is simplified by the way of sub problem decomposition.To a certain extent,the problem of decoupling difficulty in the process of solving the algorithm is solved,and the scale of solving is reduced while the efficiency is improved.The effectiveness of the new algorithm is proved by the simulation of a 10 m achine system.3.This paper proposes an improved particle swarm optimization algorithm to solve the wind power thermal power unit commitment problem,improves the discrete particle swarm optimization algorithm,improves the algorithm by redefining a serie s of variables such as position and speed,improves the convergence and search ability of the algorithm,and applies it to optimize the start-up and stop state of the unit;then applies the continuous particle swarm optimization algorithm to optimize the l oad distribution of the unit To make the unit operation meet a series of constraints such as power balance.In addition,the performance of algorithm optimization under different wind power penetration is analyzed.By comparing the optimization results of improved Benders Decomposition Algorithm and improved particle swarm optimization algorithm under two different conditions of low wind power penetration and high wind power penetration,it is concluded that the improved Benders Decomposition algorithm can ensure the safe operation of the system when dealing with the situation of low wind power penetration,while the improved particle swarm optimization algorithm can not When dealing with the situation of high wind power penetration,the method takes into account the economy and reliability of the system.