Research On Load Dispatch Of Thermal Power Plant Based On CBI

With the rapid development of coal-fired power for decades,the optimization of load distribution for the whole power plant as well as economic and safe operation of power system is becoming more and more important.Task in the current energy conservation and emissions reduction increasingly grim situation,how to reduce energy costs has become a coal-fired power plant power generation enterprise mainly consider the problem.At the same time,in the process of thermal power generation,gas emit a lot of pollution,cause serious damage to human survival environment,and has become an important factor.In addition,power grid dispatch system in order to guarantee the stability of the power load,the scheduling system in the thermal power unit load response speed put forward higher requirements.As a result,the optimized load distribution considering the cost of energy consumption and environmental pollution of minimizing the cost at the same time,also need to study how to make the factory to complete the instruction power load of the shortest time.Therefore,the use of multi-objective optimization of load distribution compared with the single goal optimal load distribution is more practical significance.Firstly,this paper analyzes various factors influencing CBI in thermal power plant according to the calculation model of comprehensive benefit index(CBI),and calculates CBI by taking a thermal power plant as an example.Through qualitative analysis and quantitative calculation,the main controllable factors influencing CBI for the energy cost and the environmental cost.It is pointed out that these two kinds of costs need to be considered in the establishment of the load optimal scheduling model.Secondly,according to the analysis of factors influencing CBI,this paper establishes a multi-objective optimal load distribution mathematical model based on energy cost,environmental cost and load response speed.Aiming at this model,the optimization algorithm multi-objective gravitational search algorithm is proposed,and the solution repairing strategy is introduced to solve the problem that the result falls into the infeasible solution region.The optimal Pareto solution set is based on the base point and entropy.Methods the optimal solution was obtained.Finally,according to the actual example,using MATLAB software to optimize the population size and the maximum iteration number of the algorithm in the homogeneity,the breadth of distribution and the optimization speed.The optimal population size and the maximum iteration times are 200 and 250.The simulation results show that,on the one hand,the proposed algorithm has a great advantage in homogeneity,breadth and speed of optimization compared with NSGA-? and AIMA algorithm.On the other hand,the proposed algorithm compared with the AGC directive energy consumption costs reduced by 0.15-0.25 million/h.Environmental cost difference is small and the difference is generally within ±0.06 million/h.The total load time has increased and increasing time is generally less than 2min.Therefore,the algorithm proposed in this paper can reduce the energy cost of power plant while satisfying the real-time requirement of load dispatching and the cost of controlling environmental protection.The optimization effect is significant.