Study On Unit Combination Optimization Model And Method Considering Periodic Operation

The unit commitment problem(UCP)is an important issue in the economic dispatching of power systems,and it plays an important role in power research.Reasonable combination and economic distribution can not only extend the service life of the unit but also bring significant economic and environmental benefits.With the further reform of the electricity market and the large-scale integration of new energy sources,the objective function and constraints of this problem will be more complicated,which will bring difficulties to its solution.This paper studies and improves the unit combination optimization problem.The main work contents are as follows:Firstly,the mathematical model of unit commitment optimization problem is described.This paper demonstrates the existence of adjacent day effects in thermal power units,and illustrates the impact of today's plan on the next day's plan.At present,most of the models consider the effect of yesterday and neglect the effect of the next day.They only seek the best benefit or the lowest cost on today.Their calculation results often lead to the situation that the degree of optimization is low or even has no solution on the next day.Under the condition that the operation of the power plant is basically unchanged in a short time,it is difficult to ensure that the existing model can be solved for several consecutive days.Based on the above considerations,a periodic operation model is proposed.Considering the effect of today's results on the next day,the calculation results are optimal under the condition of periodic repetitive operation.Secondly,the principle of hybrid leaping frog algorithm is introduced.The greedy model is used to evolve the best individual and the worst individual at the same time,and the local chaotic search of the best individual is carried out to enhance its local search ability.The leaping frog behavior is analyzed and the Step-Changing method is adopted to enable it to search in the global scope and enhance its global search ability.Finally,the two-layer frog leaping algorithm is used to solve the unit commitment optimization problem.The inner layer uses the continuous frog leap algorithm to solve the economic load distribution,uses a new initialization strategy to ensure the feasibility of particles,and uses the two-dimensional jump of particles to make them evolve without breaking the constraints.The outer layer uses the integer leaping frog algorithm to solve the unit commitment problem,and the repair strategy is used to deal with the shortest startup and shutdown time constraints.Firstly,a 10-machine example is used to verify the improved algorithm.By comparing with the results of the existing literature,it shows that the algorithm has high efficiency and accuracy for solving unit commitment problems.The results show that the periodic operation model can not only guarantee the periodic repetitive operation,but also the solution of the model is better than that of the classical model under certain conditions.At the same time,it is proved that the calculation results of the classical model today do not have the characteristics of repetitive operation,and it is difficult to ensure that there are solutions for continuous multi-day continuous calculation using the classical model,which further verifies the influence between adjacent days.Therefore,it can be shown that the periodic operation model can not only ensure the feasibility of the cycle,but also take into account the economic benefits of the cycle.