Research On Unit Combination And Operation Strategy With Wind Power

Unit commitment is an important research issue for economic dispatch of electric power and generation planning.Under the situation of the power industry with the increasing proportion of new energy and electricity,it is of great significance to study unit commitment to improve the stability of power grid operation and the ability to absorb new energy and electricity.At the same time,thermal power generating units also need to provide flexibility to improve peak load regulation capability under variable load operation.This paper firstly introduces the mathematical model of unit commitment problem and applies Lagrange relaxation algorithm to solve unit commitment problem,and analyses the results of the example.In order to overcome the shortcomings of Lagrange relaxation algorithm,sine-cosine algorithm is introduced to improve the Lagrange relaxation algorithm,after that the improved SCA-LR algorithm is applied to solve unit commitment problem.With the random search and global optimization advantage of sine-cosine algorithm,the randomness of Lagrangian multiplier updating process is increased,and the search ability of Lagrangian relaxation algorithm to the optimal solution is improved.Subsequently,in order to solve the problem that traditional unit commitment strategy's difficulty to adapt to the fast changing demand of daily load in the future,a coordinated operation strategy of multi-unit is proposed.By using more accurate wind power data in the day,SCA-LR algorithm is applied to make unit commitment updated in different periods.Compared with the previous unit commitment strategy,this strategy can better adapt to fluctuating wind power.On the basis of the above research,this paper studies how to improve the operation flexibility of power units when responding to the changing load instructions of power grid,and optimizes the operation mode of steam distribution.Aiming at the phenomenon that the load of steam turbine unit's flow characteristics changes and the control effect becomes worse.Data mining is used to analyze the historical data generated during the operation of steam turbines.A mathematical model between the key operational indicators of steam distribution mechanism of steam turbines is established by using the neural network algorithm,and the actual operational data are used to calculate specific cases.In this paper,several examples are used to demonstrate the proposed algorithm and method.