## 2 Related Work  
In recent years, research has identified two main methods for estimating carbon emissions: the emission factor method and the online monitoring method [10]. The emission factor method estimates CO2 emissions indirectly by analyzing operational data and emission coefficients of companies or facilities [11]. The online monitoring method for calculating the actual CO2 emissions directly relies on continuous emission monitoring systems (CEMSs) to track the concentration of CO2 in gas emissions and the velocity of flue gas in real time [12]. Although both methods for estimating carbon emissions have been recognized internationally [13], the emission factor method is the main method used in China. To further study the practicality of the direct measurement method in the CO\({}_{2}\) emission accounting of thermal power plants in China, [PERSON] et al. [14] developed an online carbon emission monitoring and management system for coal-fired power plants. [PERSON] [15] compared the monitoring system and accounting strategy of carbon emissions from thermal power plants. [PERSON] [16] focused on the study of the system design of the direct monitoring method for a certain 300 MW unit. [PERSON] and co-workers [17] analyzed the coal-fired power generation company's GHG emissions quantification method. [PERSON] et al. [18] proposed a strategy to strengthen the monitoring of GHG emissions from stationary sources in China based on a review of GHG emissions monitoring at home and abroad. All of these studies recommended the use of a continuous carbon dioxide emission monitoring system (CO\({}_{2}\)-CEMS) as a basis for estimating carbon emissions, and noted that manual measurements are usually used as a reference method for calibrating the data of the online monitoring system under the current CEMS management framework. The emission factor method, which estimates CO\({}_{2}\) emissions by combining operational data and specific emission factors, has been widely used in China and EU countries. Meanwhile, the real-time monitoring technique, which allows immediate monitoring of CO\({}_{2}\) emissions through the deployment of continuous emission monitoring systems (CEMSs), is more common in the United States. Nonetheless, both methods have obvious shortcomings. As reliance on annual reports of carbon emissions has become the norm, the emission factor approach suffers from problems including inefficient data collection and significant delays in results. The problem of timeliness is further exacerbated by the additional time required to review the reports once they are submitted. At the same time, the data collected are limited in terms of coverage and level of detail. In the case of real-time monitoring technologies, although they provide instantaneous data, they risk compromising stability and accuracy due to the vulnerability of the monitoring equipment to environmental factors such as temperature and humidity [19]. In view of this, it is particularly important to explore new methods that can effectively track and estimate CO\({}_{2}\) emissions in real time. In the power industry, carbon dioxide is a major source of greenhouse gas emissions, including emissions from the combustion of fossil fuels, desulphurization processes, and purchased electricity [20]. Accounting tools usually rely on data such as the low-level calorific value of the coal combusted and the results of carbon per unit of heat assays. However, accurate carbon emission data are only available once a month, as the assay step usually lags behind the production activities. In addition, considering the blended coal widely used as fuel in domestic power plants, there may be significant differences between the assay samples and the actual coal burned, which makes it challenging for power plants to realize real-time monitoring of carbon emissions. Estimating carbon dioxide emissions from electricity consumption data is a well-established program.