Big Data-based Carbon Efficiency Grading Evaluation Method of Green Energy Power Generation Projects

Based on Carbon Peaking and Carbon Neutrality Goals by the Chinese government, green energy power generation technology is developing rapidly. In order to study the carbon efficiency level of green energy power generation projects, this paper puts forward a carbon efficiency grading evaluation method considering multiple indicators. Firstly, based on big data processing methods, the massive power generation data of green energy power stations are preprocessed. Secondly, considering multiple indicators such as energy consumption and output, carbon reduction effect and new energy consumption level, it is proposed to construct a carbon efficiency evaluation indicator system from the perspective of carbon. Then, the key evaluation indicators and their characteristic weights are screened out by applying Analytic Hierarchy Process (AHP) and Fuzzy Mathematical methods, so as to obtain the final comprehensive evaluation results and assign a graded carbon efficiency code to green energy power generation. Finally, combined with the examples, it is verified that the research method proposed in this paper can quantify the carbon efficiency level of green power generation projects, and can reflect the carbon reduction efficiency of green energy power generation projects in a more comprehensive way.