An analysis method of electric energy substitution potential in a region based on GM grey prediction

Abstract

The invention provides a GM gray prediction electric energy substitution potential analysis method of a certain region, which relates to the electric power system field, and is invented for solving the problem that the electric energy substitution potential of the traditional region is difficult to synthetically consider a plurality of influence factors of load prediction, the prediction accuracyis low, and the electric energy substitution potential has no self-adaptive ability. The method of the invention comprises the following steps: determining an influence factor of the regional electricenergy substitution potential; Determine the analysis and calculation formula of electric energy substitution potential; Establish GM grey prediction model equation; Determine the correlation coefficient of the equation; Solve the response equation; Combined with the time response equation, the neural network model is used to predict the power consumption and energy consumption. Using the time response equation of electric energy substitution potential, the electric energy substitution potential level of this region is calculated and analyzed at each time node. The invention is applied to theanalysis and prediction of the regional electric energy substitution potential, and provides a feasibility study method with high accuracy and self-adaptability for the analysis of the electric energy substitution potential.

Description

technical field [0001] The invention relates to the field of power system load forecasting, in particular to a method for analyzing the electric energy substitution potential of a certain area based on GM gray forecasting. Background technique [0002] In the traditional regional electric energy substitution potential analysis scheme, the long-term regional load forecast is carried out through conventional load forecasting methods (elasticity coefficient method, large user method, load density method, etc.), combined with the proportion of electric energy substitution potential of various industries in the region at the current stage, Predictive analysis of long-term regional electric energy substitution potential. [0003] In the traditional analysis method, the electric energy substitution analysis scheme has the following defects: 1. It can only focus on predicting the load result from a certain factor, and cannot comprehensively analyze the load forecasting result from m...

AI Technical Summary

Problems solved by technology

[0003] In the traditional analysis method, the electric energy substitution analysis scheme has the following defects: 1. It can only focus on predicting the load result from a certain factor, and cannot comprehensively analyze the load forecasting result from multiple factors; 2. The load forecasting result is not self-adaptive and cannot be passed Multiple training improves prediction accuracy

The GM gray prediction model has the advantages of less modeling information, convenient calculation and high accuracy, but it has relatively high requirements for the applicability of the original data.

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