Analysis And Research On Parameter Characteristics Of Natural Gas Station Generator Sets

In recent years,with the rapid growth of the global population and the rapid increase in the degree of modernization,energy shortages and environmental quality problems have become increasingly prominent.Natural gas is widely used as a clean and efficient energy source.Therefore,natural gas stations have received much attention as energy supply in the event of a sudden interruption of utility power.In view of the problems of excessive capacity,low station load rate,low efficiency of generator set operation and waste of resources in the selection process of natural gas station generators,this paper proposes a method for selecting the capacity of the generator set,analyzes the relationship between the parameters of the natural gas station and the capacity of the generator set,and discusses the modeling and flow using two prediction algorithms.The capacity of the natural gas station generator set is predicted,and the error prediction analysis of the predicted result determines the ideal prediction model.This paper studies the generator set from the design point of view with the common parameters on the generator data sheet,selects the data-generator capacity that is not fixed on the data sheet,discusses the extent to which the natural gas station's gas consumption,covering area,geographical location,and power properties affect the capacity of the generator set,and constructs the BP neural network generator capacity prediction model.The flow of the genset capacity prediction model is established by the principle,topology and algorithm of BP neural network.The detailed process of model construction is analyzed,which provides a theoretical basis for the selection of generator capacity of natural gas station field project.To some extent,it saves design costs and production costs.This paper analyzes the natural gas station system and generator set,studies the parameters of the generator set of the natural gas station and the parameters of the natural gas station related to the capacity of the generator set by using the data of the generator set,selects the parameters of the natural gas station field which has great influence on the capacity of the generator set as sampling data,and constructs the capacity prediction model of the support vector machine generator set.The flow of the prediction model of the capacity of the generator set is formed by the principle of the support vector machine algorithm,the mathematical derivation using the optimal classification hyperplane,and the kernel function and the parameter optimization algorithm.Both BP neural network and support vector machine prediction algorithms use MATLAB experimental platform for modeling and simulation.Through the quantitative error analysis of simulation results,the optimal theoretical prediction model for generator capacity analysis is provided.