Promoting the transition to electric energy plays a positive role in driving industrial modernization forward, which holds considerable importance in enhancing the efficiency of energy utilization, and is also capable of effectively mitigating environmental pollution problems and safeguarding energy security. Drawing on the three dimensions encompassing economic development, technological progress and policy support, the article constructs an evaluation index system targeting electric energy substitution projects, and utilizes electricity consumption data from 2016 to 2024 as a study sample, and measures the capacity for electric energy substitution projects through integrating principal component analysis. On this basis, the GM gray model along with the BP neural network are introduced, and GM-BP model is developed by employing the empowerment combination method, which is used to accomplish the assessment alongside the forecasting of electric energy substitution potential. It was found that the index of electric energy substitution project potential grew from 0.399 in 2016 to 0.751 in 2024, with an overall increase of 88.22%. When carrying out the forecasting work regarding the potential of electric energy substitution projects, the prediction accuracy of the GM-BP model can reach 99.15%, and within the framework of ensuring economic development, technological advancement and policy support, the capacity improvement of electric energy substitution projects compared to a single scenario can be up to 29.02 trillion kWh. Therefore, the full utilization of AI and multivariate data analysis technology can enable the accurate assessment pertaining to electric energy substitution projects and facilitate energy conservation, emission reduction and green low-carbon.
