CN-122022172-A - Multifunctional complementary carbon accounting method and system for breweries

CN122022172ACN 122022172 ACN122022172 ACN 122022172ACN-122022172-A

Abstract

The invention discloses a multifunctional complementary carbon accounting method and system for a beer brewery, wherein the method comprises the steps of collecting real-time energy consumption data of each process unit in the whole beer production process, synchronously obtaining biogas flow and component data generated by an anaerobic fermentation system, establishing a dynamic carbon emission factor mapping table based on historical operation data and equipment characteristics of each process unit, generating a process-level carbon emission intensity sequence with a timestamp according to the real-time energy consumption data, the biogas flow and component data and the dynamic carbon emission factor mapping table, drawing a full-chain carbon footprint space-time distribution map according to the process-level carbon emission intensity sequence, and identifying carbon heat extraction point procedures and generating a multifunctional complementary optimization strategy based on the full-chain carbon footprint space-time distribution map. By utilizing the embodiment of the invention, the high carbon emission working procedure can be positioned, a targeted multi-energy complementary optimization strategy can be generated, the accuracy and the regulation and control efficiency of carbon management are improved, and the upgrading from static accounting to dynamic closed loop control is realized.

Inventors

ZHANG YONGHUA
ZHU TONGTONG
Huang Kengche
Luo Chendong
HUANG JIEPING
Liang Junbiao

Assignees

广州广氏食品有限公司
广州华糖食品有限公司

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. A method of multi-energy complementary carbon accounting for a brewery, said method comprising: Collecting real-time energy consumption data of each process unit in the whole process of saccharification, boiling, fermentation and filling of beer production, and synchronously obtaining biogas flow and component data generated by an anaerobic fermentation system; determining energy consumption characteristics of the process units based on historical operation data and equipment characteristics of each process unit, and simultaneously establishing a dynamic carbon emission factor mapping table by combining biomass source carbon properties of the biogas components; performing real-time carbon accounting step by step according to the real-time energy consumption data, the biogas flow and component data and the dynamic carbon emission factor mapping table, and generating a step-level carbon emission intensity sequence with a time stamp; Driving a carbon flow tracking model through a digital twin platform according to the process-level carbon emission intensity sequence, and drawing a full-chain carbon footprint space-time distribution diagram from raw material input to product output; And identifying carbon heat extraction point procedures and generating a multi-energy complementary optimization strategy based on the full-chain carbon footprint space-time distribution map, so as to realize carbon accounting and carbon regulation closed-loop management.
2. The method of claim 1, wherein the step of collecting real-time energy consumption data of each process unit of saccharification, boiling, fermentation and filling in the whole beer production process and synchronously obtaining biogas flow and component data generated by the anaerobic fermentation system comprises the steps of: Arranging intelligent electric meters, steam flow meters and gas meters at key nodes of each process unit of the saccharification pot, the boiling pot, the fermentation tank and the filling line, establishing an Internet of things data acquisition network, and generating an original energy consumption data stream; An ultrasonic flowmeter and an online gas analyzer are arranged on a biogas collecting pipeline of the anaerobic fermentation system, the flow rate of biogas is monitored in real time, the concentration proportion of methane, carbon dioxide and hydrogen sulfide is analyzed, and a biogas monitoring data stream is generated; transmitting the original energy consumption data stream and the biogas monitoring data stream to a central data acquisition server through an industrial Internet of things protocol, aligning time sequences of different data sources by adopting a time stamp synchronization technology, and generating a time-synchronized energy consumption and biogas data set; And (3) carrying out data cleaning and abnormal value correction on the time-synchronous energy consumption and biogas data set, removing abnormal data points generated by equipment failure or communication interruption, and generating a standardized real-time energy consumption data set and biogas flow and component data set.
3. The method of claim 2, wherein determining process unit energy consumption characteristics based on historical operating data and equipment characteristics of each process unit while establishing a dynamic carbon emission factor map in combination with biomass source carbon properties of the biogas component comprises: extracting historical operation data of each process unit from a production management system, wherein the historical operation data comprises energy consumption curves, equipment operation parameters and raw material consumption records under different production batches, and generating a historical operation data set; analyzing an energy consumption mode in the historical operation data set, and establishing an energy consumption reference model of each process unit by combining rated power, a thermal efficiency curve and load characteristic parameters of equipment to generate an energy consumption characteristic parameter set of the process unit; According to methane content and gas composition in the methane flow and component data set, calculating the heat value equivalent and carbon oxidation factor of the methane by combining with a biomass energy carbon accounting standard to generate a methane carbon attribute parameter set; and integrating the process unit energy consumption characteristic parameter set and the biogas carbon attribute parameter set, constructing a dynamic carbon emission factor calculation function taking the production load, the raw material proportion and the energy structure as independent variables, and generating a dynamic carbon emission factor mapping table.
4. A method according to claim 3, wherein said generating a time stamped sequence of process-level carbon emission intensities from said real-time energy consumption data, said biogas flow and composition data, and said dynamic carbon emission factor map by process real-time carbon calculations comprises: Extracting energy consumption data of a current production period including instantaneous values of electric energy consumption, steam consumption and gas consumption from a standardized real-time energy consumption data set according to a process, and generating a process real-time energy consumption slice; Extracting biogas generation amount and component data corresponding to a time window from the biogas flow and component data set, calculating carbon offset potential of biogas utilization, and generating biogas carbon compensation amount; Inquiring a dynamic carbon emission factor mapping table according to the current production load, acquiring real-time carbon emission factors of each energy variety, multiplying energy consumption data in the real-time energy consumption slices of the working procedure by the corresponding carbon emission factors, and generating direct carbon emission of the working procedure; and deducting methane carbon compensation quantity from the direct carbon emission quantity of the working procedure to obtain the net carbon emission quantity of the working procedure, adding an accurate time stamp for the net carbon emission quantity of each working procedure, and arranging according to production time sequence to generate a working procedure-level carbon emission intensity sequence with the time stamp.
5. The method of claim 4, wherein the drawing a full chain carbon footprint spatiotemporal profile from feedstock input to product output from the process-level carbon emission intensity sequence by driving a carbon flow tracking model with a digital twin platform comprises: Establishing a three-dimensional virtual model of the whole beer production process in a digital twin platform, mapping each process unit into a virtual node, configuring the connection relation of material flow, energy flow and data flow, and generating a virtual production process model; inputting the process-level carbon emission intensity sequence with the time stamp into a virtual production flow model, driving a carbon flow tracking model to calculate the transfer and accumulation process of carbon emission among all nodes, and generating carbon flow intensity distribution data; Based on carbon flow intensity distribution data, visualizing carbon emission intensity of each node on a virtual production flow model by adopting a thermodynamic diagram rendering algorithm, and using a color gradient to represent carbon emission magnitude so as to generate a carbon footprint thermodynamic diagram; and superposing a time axis animation on the carbon footprint thermodynamic diagram, displaying the time-space evolution process of carbon emission along with the production process, marking a key carbon transfer path and an accumulation node, and finally generating a full-chain carbon footprint time-space distribution diagram.
6. The method of claim 5, wherein the identifying carbon heat rejection points process and generating a multi-energy complementary optimization strategy based on the full chain carbon footprint spatiotemporal profile, implementing carbon accounting and carbon regulation closed-loop management, comprises: Analyzing a carbon emission peak area in a full-chain carbon footprint space-time distribution diagram, and combining process parameters in a virtual production flow model, identifying a hot spot process with carbon emission intensity higher than a preset intensity threshold value, and generating a carbon emission point analysis report; analyzing the energy consumption structure, the equipment operation efficiency and the process control parameters aiming at the carbon exhaust heat point analysis report to generate a carbon exhaust root cause diagnosis report; Based on a carbon root cause diagnosis report, an optimization scheme is designed by combining a multi-energy complementation principle, and the optimization scheme comprises the steps of adjusting the steam recovery proportion of a saccharification process, optimizing the temperature control strategy of a fermentation process and increasing the methane power generation self-use proportion to generate a multi-energy complementation optimization strategy set; Inputting the multi-energy complementary optimization strategy set into a digital twin platform for simulation verification, optimizing strategy parameters according to simulation results, issuing verified strategies to a production control system for execution, and simultaneously establishing a carbon emission monitoring feedback mechanism to realize carbon accounting and carbon regulation closed-loop management.
7. A brewery multi-energy complementary carbon accounting system, said system comprising: The acquisition module is used for acquiring real-time energy consumption data of each process unit of saccharification, boiling, fermentation and filling in the whole beer production process and synchronously acquiring biogas flow and component data generated by the anaerobic fermentation system; The building module is used for determining the energy consumption characteristics of the process units based on the historical operation data and the equipment characteristics of each process unit, and meanwhile, building a dynamic carbon emission factor mapping table by combining the biomass source carbon attribute of the biogas component; The accounting module is used for carrying out real-time carbon accounting step by step according to the real-time energy consumption data, the biogas flow and component data and the dynamic carbon emission factor mapping table to generate a process-level carbon emission intensity sequence with a time stamp; the tracking module is used for driving a carbon flow tracking model through a digital twin platform according to the process-level carbon emission intensity sequence and drawing a full-chain carbon footprint space-time distribution diagram from raw material input to product output; And the identification module is used for identifying carbon heat extraction point procedures and generating a multi-energy complementary optimization strategy based on the full-chain carbon footprint space-time distribution diagram so as to realize carbon accounting and carbon regulation closed-loop management.
8. The system according to claim 7, wherein the acquisition module is specifically configured to: Arranging intelligent electric meters, steam flow meters and gas meters at key nodes of each process unit of the saccharification pot, the boiling pot, the fermentation tank and the filling line, establishing an Internet of things data acquisition network, and generating an original energy consumption data stream; An ultrasonic flowmeter and an online gas analyzer are arranged on a biogas collecting pipeline of the anaerobic fermentation system, the flow rate of biogas is monitored in real time, the concentration proportion of methane, carbon dioxide and hydrogen sulfide is analyzed, and a biogas monitoring data stream is generated; transmitting the original energy consumption data stream and the biogas monitoring data stream to a central data acquisition server through an industrial Internet of things protocol, aligning time sequences of different data sources by adopting a time stamp synchronization technology, and generating a time-synchronized energy consumption and biogas data set; And (3) carrying out data cleaning and abnormal value correction on the time-synchronous energy consumption and biogas data set, removing abnormal data points generated by equipment failure or communication interruption, and generating a standardized real-time energy consumption data set and biogas flow and component data set.
9. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1-6 when run.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of claims 1-6.

Description

Multifunctional complementary carbon accounting method and system for breweries Technical Field The invention belongs to the technical field of beer manufacturing, and in particular relates to a multifunctional complementary carbon accounting method and system for a beer brewery. Background The beer production belongs to the traditional high-energy consumption industry, and the production process involves a plurality of process units such as saccharification, boiling, fermentation, filling and the like, and has a complex energy structure and dispersed carbon emission sources. The current general carbon accounting method in industry carries out overall estimation based on macroscopic statistical data and fixed emission factors, has coarse accounting granularity and poor timeliness, is difficult to accurately reflect the dynamic emission characteristics of each process, and is more incapable of effectively tracing the specific distribution of carbon footprint in space-time dimension. Meanwhile, the existing method generally regards biogas generated in the recycling process of anaerobic fermentation and the like as single energy input, and the dynamic influence of biomass energy attribute on the carbon emission factor cannot be fully considered, so that the accuracy of the accounting result is insufficient. The extensive accounting mode makes it difficult for enterprises to accurately position carbon heat extraction point procedures, carbon emission reduction regulation measures often lack pertinence, closed-loop management of accounting, analysis and optimization cannot be formed, and the aim of realizing refined and intelligent carbon reduction in the beer industry is restricted. Disclosure of Invention The invention aims to provide a multi-energy complementary carbon accounting method and system for a brewery, which are used for solving the defects in the prior art, locating a high carbon emission process and generating a targeted multi-energy complementary optimization strategy, improving the accuracy and regulation and control efficiency of carbon management and realizing the upgrading from static accounting to dynamic closed loop control. One embodiment of the present application provides a method of multi-energy complementary carbon accounting for a brewery, said method comprising: Collecting real-time energy consumption data of each process unit in the whole process of saccharification, boiling, fermentation and filling of beer production, and synchronously obtaining biogas flow and component data generated by an anaerobic fermentation system; determining energy consumption characteristics of the process units based on historical operation data and equipment characteristics of each process unit, and simultaneously establishing a dynamic carbon emission factor mapping table by combining biomass source carbon properties of the biogas components; performing real-time carbon accounting step by step according to the real-time energy consumption data, the biogas flow and component data and the dynamic carbon emission factor mapping table, and generating a step-level carbon emission intensity sequence with a time stamp; Driving a carbon flow tracking model through a digital twin platform according to the process-level carbon emission intensity sequence, and drawing a full-chain carbon footprint space-time distribution diagram from raw material input to product output; And identifying carbon heat extraction point procedures and generating a multi-energy complementary optimization strategy based on the full-chain carbon footprint space-time distribution map, so as to realize carbon accounting and carbon regulation closed-loop management. Yet another embodiment of the present application provides a brewery multi-energy complementary carbon accounting system, comprising: The acquisition module is used for acquiring real-time energy consumption data of each process unit of saccharification, boiling, fermentation and filling in the whole beer production process and synchronously acquiring biogas flow and component data generated by the anaerobic fermentation system; The building module is used for determining the energy consumption characteristics of the process units based on the historical operation data and the equipment characteristics of each process unit, and meanwhile, building a dynamic carbon emission factor mapping table by combining the biomass source carbon attribute of the biogas component; The accounting module is used for carrying out real-time carbon accounting step by step according to the real-time energy consumption data, the biogas flow and component data and the dynamic carbon emission factor mapping table to generate a process-level carbon emission intensity sequence with a time stamp; the tracking module is used for driving a carbon flow tracking model through a digital twin platform according to the process-level carbon emission intensity sequence and drawing a full-chain carbon footprint sp