CN-122022141-A - Energy-saving and emission-reduction measure determining method based on carbon emission prediction

CN122022141ACN 122022141 ACN122022141 ACN 122022141ACN-122022141-A

Abstract

The invention relates to the technical field of energy conservation and emission reduction, and discloses a method for determining energy conservation and emission reduction measures based on carbon emission prediction, which comprises the following steps: dividing the emission data set to obtain a training set, a verification set and a test set, constructing a prediction model by using the training set and the test set to obtain a trained prediction model, and predicting based on the trained prediction model to obtain a prediction result. The invention breaks through the limitation of the traditional static model, captures the causal relationship of the evolution of the multivariable time along with time through the emission coefficient, provides support for prediction, forms closed loop cooperation with the intervention, realizes the prediction of the medium-long emission trend based on the prediction model weighted by the emission coefficient, combines the generation model embedded with the energy conservation constraint to design the intervention measures, ensures that the measure combination strictly follows the physical rule, evaluates the technical maturity, the cost benefit, the social acceptance and the policy compliance through the multidimensional scoring matrix, and forms the whole-flow scientific guide from the prediction to the measure landing.

Inventors

REN JUAN
LIU PENGCHENG
LU HAIRONG

Assignees

湖南星普森信息技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260120

Claims (10)

1. An energy conservation and emission reduction measure determining method based on carbon emission prediction, which is characterized by comprising the following steps: S101, acquiring energy consumption data, industrial production value data and meteorological data, preprocessing the energy consumption data and the industrial production value data to obtain energy consumption and industrial yield respectively, and carrying out standardized processing on the energy consumption, the industrial yield and the meteorological data to obtain an emission data set; S102, dividing an emission data set to obtain a training set, a verification set and a test set, constructing a prediction model by using the training set and the test set to obtain a trained prediction model, and predicting based on the trained prediction model to obtain a prediction result; s103, generating an initial measure combination based on a prediction result, constructing a multidimensional scoring function, scoring the initial measure combination to obtain a scoring matrix and a decision suggestion, and adjusting the initial measure combination in combination with the decision suggestion; S104, checking the adjusted initial measure combination, and feeding back a checking result to the prediction model.
2. The method for determining the energy conservation and emission reduction measures based on the carbon emission prediction according to claim 1, wherein the obtaining the training set, the verification set and the test set comprises: Dividing the emission data set according to time sequence to obtain an initial training set, a verification set and a test set; Constructing a sliding window for dividing the training set, and sliding the training set by taking a quarter as a step length to form the training set; And acquiring the latest historical data for the verification set and the test set to be respectively filled, and constructing a sliding window to divide the filled verification set and test set to obtain the verification set and test set.
3. The method for determining the energy conservation and emission reduction measures based on the carbon emission prediction according to claim 1, wherein the construction of the prediction model in the prediction model by using the training set and the test set comprises a prediction layer and a measure layer; the specific steps of training the prediction layer are as follows; inputting a training set, optimizing network weights through back propagation, wherein a loss function is a negative log likelihood loss and KL divergence term, and the formula is as follows: In To become posterior distribution of variation Log likelihood expectation of the lower observation data y, Representing a variational posterior distribution With a priori distribution L is the current batch loss value, For the network weight, y is the carbon emission, X is the input feature; Weighting the network Updating, wherein the calculation formula is as follows: wherein: is the learning rate; and verifying by using the verification set, and selecting the verification set with the minimum loss as a prediction layer.
4. The method for determining the energy conservation and emission reduction measures based on the prediction of the carbon emission as recited in claim 3, wherein the predicting based on the trained prediction model comprises: Calculating emission coefficients by adopting a gradient method to obtain an emission coefficient matrix, inputting the energy consumption and the emission coefficient matrix into a trained prediction model, and obtaining predicted emission through a prediction formula, wherein the prediction formula is as follows: wherein: As the emission coefficient of the variable i at time t, Representing the value of the input variable at time t, Is a random error term.
5. The method for determining the energy conservation and emission reduction measures based on the carbon emission prediction as recited in claim 3, wherein the prediction layer comprises an input layer, a hidden layer and a first output layer; The hidden layers comprise a first hidden layer and a second hidden layer, and each contain an activation function; The first output layer includes a carbon emission prediction branch and an emission coefficient matrix branch.
6. The energy saving and emission reduction measure determining method based on carbon emission prediction according to claim 3, wherein the measure layer includes an encoder, a decoder, and a second output layer; the encoder includes three fully connected layers, and the decoder includes an embedded energy conservation constraint layer and three fully connected layers.
7. The method for determining the energy conservation and emission reduction measures based on the prediction of the carbon emission as claimed in claim 1, wherein the constructing the multi-dimensional scoring function comprises: wherein: Represents success rate of similar projects, Representing the investment recovery period and the net present value evaluation, Represents the degree of satisfaction of society, For compliance scoring a, b, c, d represents the corresponding weights, respectively.
8. The method for determining the energy saving and emission reduction measures based on the carbon emission prediction according to claim 1, wherein the verifying the adjusted initial measure combination includes: the influence of the adjusted initial measure combination is calculated by adopting a difference method, and the calculation formula is as follows: wherein: in order to predict the amount of emissions before a measure is implemented, Indicating the emission coefficient corresponding to the measure, Representing the adjustment amplitude of the adjusted measure; and then verifying the energy conversion efficiency through the first law of thermodynamics to carry out physical consistency verification on the measure parameters.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the energy saving and emission reduction measure determination method based on carbon emission prediction according to any one of claims 1 to 8 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed, implements the energy saving and emission reduction measure determination method based on carbon emission prediction as set forth in any one of claims 1 to 8.

Description

Energy-saving and emission-reduction measure determining method based on carbon emission prediction Technical Field The invention relates to the technical field of energy conservation and emission reduction, in particular to a method for determining energy conservation and emission reduction measures based on carbon emission prediction. Background The energy conservation and emission reduction means that by adopting effective technical means and management measures, the energy consumption is reduced, the emission of harmful waste gas is reduced, and the purposes of protecting the environment, coping with climate change and promoting sustainable development are achieved. This concept encompasses energy efficiency enhancement and pollutant emission control in a number of industries, construction, transportation, etc., including the promotion of high energy facilities, the optimization of production processes, the use of renewable energy, enhanced policy guidance, etc. The energy conservation and emission reduction are not only beneficial to enterprises to reduce the operation cost, but also can improve the air quality and protect the ecological environment, promote the economy to be transformed to the low-carbon and green directions, and are important strategies for realizing sustainable development. However, the prior art still has several obvious disadvantages, firstly, the limitation of the traditional static model makes it difficult to effectively capture the evolution of the dynamic causal relationship, so that the prediction accuracy is reduced when the new environment and the new challenge are handled, and secondly, the existing prediction and intervention measures are often disjointed, and an effective closed-loop cooperative mechanism is lacking, which means that after the carbon emission prediction is performed, the related intervention measures may not follow up in time or effectively, so that a gap is formed between policy execution and actual conditions, and the effect of the energy-saving and emission-reducing measures cannot be fully exerted. In addition, the traditional measure evaluation method is often focused on a single dimension, such as only focusing on the carbon emission quantity or the economic cost, but neglecting the comprehensive influence of multi-dimensional factors, the one-sided evaluation mode may cause underestimation or overestimation of the actual effect of the measure, thereby influencing the scientificity and effectiveness of the decision, so that the defects limit the rationality and the execution force of the energy-saving and emission-reduction measure to a certain extent, and more dynamic and comprehensive evaluation modes are urgently needed for effective decision support. Disclosure of Invention In order to overcome the defects in the prior art, the embodiment of the invention provides an energy-saving and emission-reduction measure determining method based on carbon emission prediction. In order to achieve the above purpose, the present invention provides the following technical solutions: An energy conservation and emission reduction measure determining method based on carbon emission prediction, the method comprising: S101, acquiring energy consumption data, industrial production value data and meteorological data, preprocessing the energy consumption data and the industrial production value data to obtain energy consumption and industrial yield respectively, and carrying out standardized processing on the energy consumption, the industrial yield and the meteorological data to obtain an emission data set; S102, dividing an emission data set to obtain a training set, a verification set and a test set, constructing a prediction model by using the training set and the test set to obtain a trained prediction model, and predicting based on the trained prediction model to obtain a prediction result; s103, generating an initial measure combination based on a prediction result, constructing a multidimensional scoring function, scoring the initial measure combination to obtain a scoring matrix and a decision suggestion, and adjusting the initial measure combination in combination with the decision suggestion; S104, checking the adjusted initial measure combination, and feeding back a checking result to the prediction model. The energy consumption data can be obtained through a volume 2019-2024 of energy statistics annual book of China Industrial park, and the industrial production value data can be obtained through a quarter GDP and a branch industrial production value; The energy consumption data is preprocessed by adopting energy conversion coefficients according to the general rule of comprehensive energy consumption calculation: Wherein, the energy index coefficient is electric power= 0.1229 kgce/kWh (kilogram standard coal/kilowatt hour), coal=0.7143 kgce/kg and natural gas= 1.3300 kgce/m3. The industrial production value data is preprocessed by adopting factory pric