Multi-objective DE Algorithm And Its Application In Dynamic Economic Environment Scheduling

With the increasing environmental pollution and the consumption of fossil energy and other fuels,the environmental and economic dispatching of power system has become the focus of scholars’ research.The environmental and economic dispatching of power system is a complex multi-objective optimization problem with constraints.It aims at the minimum of fuel cost and pollutant emissions at the same time.This paper mainly studies the problem of power system dynamic economic environment scheduling,and establishes the mathematical model of power system dynamic economic environment scheduling to connect the wind turbine system,using optimization algorithm.The main findings are as follows:Based on the design of the multi-objective differential evolution algorithm,the selection operator of the algorithm is improved,and the selection operator is redesigned by the Pareto optimal theory to apply the algorithm to the multi-objective optimization problem.In order to improve the traditional differential evolution algorithm,the adaptive scaling factor is used to replace the fixed value,and the parameters change with the number of iterations.By adding the quadratic variation link,the problem of local optimization can be solved further.Compared with other multi-objective optimization algorithms,the improved multi-objective differential evolution algorithm has good convergence speed and distribution.Mathematical modeling and problem solving for dynamic economic environment scheduling of thermal power units are carried out.In the modeling process,the influence of the valve point effect and network loss on the operation state of power system,the climbing speed of the unit and the power demand of different time periods are considered.Through two system experiments consisting of 10 coal-fired power units,it can be concluded that the multi-objective differential evolution algorithm can effectively solve the scheduling problem of coal-fired power units,and the output of the units can make the fuel cost of the system and the emission of polluting gases relatively low.In this paper,a mathematical model is set up for the dynamic economic environment scheduling of power system with wind turbine.Considering the unpredictability and volatility of wind turbine output,some constraints such as rotating reserve capacity caused by wind turbine uncertainty are added to the scheduling model of thermal turbine power system.The dynamic economic environment transfer model of power system with wind turbine is solved by using the multi-objective differential evolution algorithm.Compared with the processing result of thermal power unit,the power system dispatching with wind power unit can obtain lower system fuel cost and emit less polluting gas,and can save energy and reduce emissions.In conclusion,this paper designs a multi-objective differential evolution algorithm and proves its convergence speed and distribution by test function.Modeling and solving the dynamic economic environment scheduling problem of thermal power system and the problem after joining the wind power unit,the system fuel morning report and pollution gas emission are reduced,and the output of the unit with the best effect is obtained.