Comprehensive subway energy consumption forecasting method based on time sequence

Abstract

The invention discloses a comprehensive subway energy consumption forecasting method based on a time sequence. The comprehensive subway energy consumption forecasting method based on the time sequence directly uses sample data of a subway energy management system to build a total subway energy consumption forecasting model based on the time sequence. The comprehensive subway energy consumption forecasting method based on the time sequence gives sufficient consideration to the subway energy consumption periodicity, builds the forecasting model according to the energy consumption forecasting time, and combines a long autoregression model method with a nonlinear least square method to estimate parameters, wherein the long autoregression model method is used for the primary parameter estimation, and the nonlinear least square method is used for the precise parameter estimation. The comprehensive subway energy consumption forecasting method based on the time sequence uses the data recorded in the subway energy management system to directly build the subway energy consumption forecasting model based on the time sequence, does not need to spend energy to research the energy consumption structure of the subway system and avoids the influence to the subway energy consumption forecasting precision due to incomplete consideration to energy consumption influence factors.

Description

technical field [0001] The invention relates to a method for predicting subway energy consumption, which belongs to the field of energy consumption prediction, in particular to a method for predicting subway energy consumption based on time series. Background technique [0002] Urban rail transit is an important part of the urban public transportation system. It has the characteristics of large capacity, fast speed, high punctuality, small footprint, and low pollution. It can well solve the current urban traffic congestion problem. With the launch of a large number of subway projects across the country, the operating kilometers of subways have risen sharply. Improving energy utilization efficiency is of great significance for reducing subway operating costs, protecting the environment, and saving energy and reducing emissions. In the subway energy-saving method, the scientific analysis and reasonable prediction of energy consumption not only help to optimize the control stra...

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Problems solved by technology

[0005] Aiming at the flaws of the existing prediction models and the nonlinearity of the subway energy consumption structure itself, the present invention proposes a way to use the recorded data of the subway energy management system to establish a subway energy consumption prediction model based on time series statistics without having to consider the subway energy consumption structure. The method of energy consumption structure composition of the system

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