3results about How to "Accurate emissions" patented technology

This invention discloses a carbon emission data quality early warning method and system based on big data. The early warning method includes the following steps: collecting and preprocessing carbon emission data from enterprises and actual emissions; calculating the theoretical total carbon emissions of a single enterprise based on the enterprise carbon emission data; calculating the theoretical specific content of carbon emission types at each stage based on the theoretical total carbon emissions of a single enterprise, and issuing an early warning if the specific content of a certain type exceeds the industry standard; detecting the actual carbon emission type content and total carbon emissions of a single enterprise at each stage, comparing them with the industry standard, and issuing an early warning if they exceed the standard; calculating the difference between the actual monitored carbon emissions in the control area and the area's carbon emission standard, and the difference between the carbon emission type content and the type standard, and issuing an early warning if they exceed the standard; providing an early warning record for the area based on the early warning information; calculating a carbon emission reduction potential index to assess the degree of carbon emission reduction after the early warning enterprise takes measures. This invention provides early warning information from multiple aspects of carbon emissions, making carbon emission early warning more accurate.

This utility model discloses an automatic separation and collection device for heavy debris in an airflow conveying system, relating to the technical field of airflow separation equipment. The separation body includes a cylindrical cavity with a conical guide hood at the top. A spiral feed plate is located between the outer side of the guide hood and the inner wall of the cavity. A feed pipe is located on one side of the upper part of the cavity, a discharge pipe is located at the top of the cavity, and a discharge port is located at the bottom of the cavity. Corn fibers, being lightweight and highly susceptible to airflow, move upwards more easily with the airflow, while heavy debris, due to gravity and centrifugal force, tends to sink closer to the inner wall of the cavity, significantly improving the initial separation efficiency and reducing the mutual entanglement of corn fibers and heavy debris.

This application provides a method and system for predicting carbon emissions throughout the entire lifecycle of a substation. The prediction method divides the carbon emissions throughout the substation's lifecycle into an installation phase and an operation phase. The first type of multi-source data corresponding to the installation phase includes periodic fluctuation data and causal correlation data, while the second type of multi-source data corresponding to the operation phase includes node status data and environmental correlation data. A carbon emission prediction model is constructed, comprising sub-models for the installation phase and the operation phase. The installation phase sub-model includes a VMD-LSTM module and a causal interaction module to obtain the predicted total carbon emissions for the installation phase. The operation phase sub-model uses a graph neural network structure to obtain the predicted total carbon emissions for the operation phase. Combining the predicted total carbon emissions for the installation phase and the operation phase, the total predicted carbon emissions for the entire substation's lifecycle are obtained and output. This application enables accurate prediction of carbon emissions throughout the entire lifecycle of a substation.