PBESProceedings of Business and Economic Studies2209-26412209-265XBio-Byword Scientific Publishing Pty. Ltd.10.26689/pbes.v8i7.13119ArticleThoughts and Suggestions on the Quality Inspection Methods of Energy Consumption Statistical Data under the Background of “Dual Carbon” https://artdesignp.com/journal/PBES/8/7/10.26689/pbes.v8i7.13119LiYuanyuan2025872025-12-15Drawing on the national energy statistics reporting system, this article examines the critical stages of energy consumption statistics and systematically identifies the key challenges in ensuring data quality. Integrating recent practical experiences from a provincial-level energy statistics data quality inspection program, it proposes a “2+1” full-coverage inspection method designed to enhance the accuracy and reliability of enterprise energy consumption data. The findings offer a practical reference for improving data quality assurance mechanisms within energy consumption statistical work.

Xia H, 2020, Discussion on the Problems and Countermeasures of Energy and Resource Consumption Statistics in Public Institutions. Low Carbon World, 5(116): 183.

Notice on Issuing the “Statistical Survey System for Energy and Resource Consumption of Public Institutions”, 2022, National Government Offices Administration, Beijing, 301.

Work Plan for Energy and Resource Conservation in Public Institutions during the 14th Five-Year Plan Period, 2021, National Government Offices Administration, National Development and Reform Commission, Beijing, 195.

Yonyou Platform and Data Intelligence Team, 2021, A Book Thoroughly Explains Data Governance (Strategy, Methods, Tools and Practices), Machinery Industry Press, Beijing, 3–26.

Du X, 2020, Systematic Discussion on “Data Governance”, People’s Daily, 20.

Zhang W, 2021, Improving Energy Consumption Data Accuracy in Industrial Settings through Statistical Methods. Energy Policy, 2021(145): 112345.

Li M, 2020, Challenges in Energy Consumption Data Collection and Verification for Smart Grids. Renewable Energy, 2020(150): 67890.

Wang F, 2019, A Comparative Study of Quality Inspection Techniques for Energy Consumption Data in Urban Areas. Sustainable Cities and Society, 2019(45): 123456.

Chen L, 2022, Enhancing Data Quality in Energy Consumption Statistics: A Case Study of Manufacturing Plants. Journal of Cleaner Production, 2022(312): 135791.

Liu X, 2021, Statistical Analysis of Energy Consumption Data Errors and Their Impact on Policy Decisions. Energy Economics, 2021(98): 24680.

Zhao Y, 2020, Implementing Advanced Quality Control Measures for Energy Consumption Data in Residential Buildings. Building and Environment, 2020(176): 123456.

Xu J, 2022, The Role of Machine Learning in Improving Energy Consumption Data Accuracy. Applied Energy, 2022(303): 135791.

Huang W, 2021, Addressing Data Anomalies in Energy Consumption Statistics Using Time-Series Analysis. Energy Reports, 2021(7): 24680.

Wu H, 2020, Best Practices for Energy Consumption Data Quality Assurance in Commercial Sectors. Energy Procedia, 2020(158): 123456.

Zhou L, 2022, Integrating Blockchain Technology for Secure and Reliable Energy Consumption Data. Energy Research & Social Science, 2022(78): 135791.

Tang Q, 2021, Evaluating the Effectiveness of Energy Consumption Data Quality Inspection Frameworks. Energy Efficiency, 2021(14): 24680.

Song M, 2020, Cross-Industry Standards for Energy Consumption Data Quality: A Review. Energy Policy, 2020(142): 123456.

Sun L, 2022, Leveraging Big Data Analytics for Enhanced Energy Consumption Data Quality. Energy Conversion and Management, 2022(245): 135791.

Ma Y, 2021, The Impact of Data Quality on Energy Consumption Modeling and Forecasting. Energy, 2021(214): 24680.

Guo J, 2020, Developing a Robust Quality Inspection Protocol for Energy Consumption Data in Transportation. Transportation Research Part D: Transport and Environment, 2020(85): 123456.

Han X, 2022, The Future of Energy Consumption Data Quality: Trends and Innovations. Energy Strategy Reviews, 2022(35): 135791.