Electric energy substitution scheme prediction method and device based on Gaussian regression combination prediction model

Abstract

The invention discloses an electric energy substitution scheme prediction method and device based on a Gaussian regression combination prediction model, and the method comprises the steps: receiving prediction targets of different energy substitution schemes of an energy substitution conversion enterprise, and obtaining frequent item sets of various types of targets; building a Gaussian regressioncombined prediction model by adopting a Gaussian regression process; carrying out clustering prediction on the frequent item sets of various targets of different energy substitution schemes, and carrying out linear combination on prediction target values to obtain an annual cost value prediction target value; based on the principle that the annual cost values are equal, obtaining the boundary electricity price of the electric energy substitution scheme, calculating uncertainty estimation of the electric energy substitution scheme, and obtaining a prediction result of the electric energy substitution scheme; and performing data feedback based on the prediction result, comparing the data with actual data received by a related business application platform of the power system, adjusting parameters of the Gaussian regression combination prediction model, and performing electric energy replacement scheme prediction by adopting the Gaussian regression combination prediction model after parameter adjustment.

Description

technical field [0001] The disclosure belongs to the technical field of energy substitution, and relates to a method and device for predicting electric energy alternatives based on a Gaussian regression combination forecasting model. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] At present, my country is facing increasingly serious and urgent problems of energy shortage and environmental damage. In order to promote enterprises to reduce resource dissipation and improve environmental quality, it is urgent to carry out research on industrial energy substitution in response to the needs of power companies to promote energy substitution by energy-consuming enterprises. However, in the process of equipment installation, transformation, and upgrading, energy transformation enterprises have problems such as large engineering volume, slow profi...

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Problems solved by technology

However, in the process of equipment installation, transformation, and upgrading, energy transformation enterprises have problems such as large engineering volume, slow profitability, and high replacement costs. Therefore, there is great resistance to the implementation of energy alternatives. Make dynamic cost forecasts for various energy alternatives based on market dynamic information, incentive mechanisms, and users' demand for energy alternatives, and forecast electric energy alternatives with electricity consumption as the main body

[0004] However, the inventor found in the research and development process that in the prediction of electric energy alternatives, the traditional statistical method not only consumes a lot of labor, but also has a large error in the prediction accuracy. It is necessary to propose a method for the prediction accuracy and prediction efficiency. A set of effective scientific forecasting methods

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