Research On Constraint Handling Method For Economic Dispatch Of Power System

With the rapid development of modern society and economy,the demand for electric energy is increasing day by day,the construction of power system is strengthened and the scale is becoming larger and larger.The economic dispatch of power system takes the lowest power supply cost or energy consumption of the whole network as the objective function.It is an important tool for realizing the economic operation of power system.It has been a scientific method in the operation process and a dispatching principle widely adopted by various countries in the world so far.Economic dispatch of power system is a constrained optimization problem with high dimension,non-convexity and non-linearity,so it is very difficult to solve the problem,especially to deal with the coupling constraints.Centralized dispatching has long been the mainstay of power system in China,which will make it more difficult to solve the economic dispatch problem of power system.It is urgent to find an effective method to solve the economic dispatch problem of large power grid.In order to solve the above problems,this paper uses the incremental rate of unit consumption and penalty function to handle the constraints and optimize the solution of economic dispatch problem.The main work is as follows:Firstly,the model of power system economic dispatch problem is established,and the basic theory involved in this paper is analyzed,including the content of constraints,the traditional processing methods of constraints and the particle swarm optimization and differential evolution algorithm used in this experiment,which lay the foundation for the following research work.Secondly,for the economic dispatching model without considering the valve point effect,in each iteration,a new constraint handling method is proposed.In each iteration,according to the different situations of the system power needs to be up or down,using the consumption increment rate of each unit,the violation of equality constraints is regularly allocated to the output of each unit,and the constraints are satisfied through continuous cycle.The traditional particle swarm optimization algorithm and the traditional differential evolution algorithm are used,and six examples of 6 units,15 units,20 units,38 units,110 units and 140 units are simulated.It is proved that this method can effectively reduce the generation cost,avoid the generation of a large number of invalid solutions,reduce the calculation time of the algorithm and improve the efficiency of the solution.Finally,a new constraint handling method is proposed for the economic dispatching model considering the valve point effect.A multi-stage penalty function with penalty factor increasing with the number of iterations is designed.In each iteration,the violation amount of the equality constraint is allocated to each unit according to the output proportion of each unit,so as to promote the satisfaction of the equality constraint.The differential evolution algorithm is used,where the mutation operator linearly increases with the number of iterations,and the crossover operator linearly decreases with the number of iterations.Three examples are used.The simulation results of this method are compared with those of static penalty function and multi-stage penalty function without output allocation.The effectiveness and superiority of this method are verified.By comparing this method with other existing methods for solving economic dispatching problems,it is proved that this method can significantly solve stability on the premise of guaranteeing reasonable accuracy.