CN116596329A - Multi-energy complementary enterprise electric power carbon emission factor conduction calculation method and system - Google Patents
Multi-energy complementary enterprise electric power carbon emission factor conduction calculation method and system Download PDFInfo
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Abstract
The invention discloses a method and a device for conducting and calculating electric power carbon emission factors of a multi-energy complementary enterprise, which are used for acquiring carbon emission accounting boundary model data of a collecting device; acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period; acquiring a regional power grid carbon emission factor of a target unit; calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factor; and deducing a dynamic carbon emission factor of a target unit in a preset time period based on the real-time carbon emission metering data. According to the carbon emission accounting boundary model and the energy consumption activity real-time data in the preset time period acquired by the acquisition device, the invention calculates the instant carbon emission of the enterprise, and deduces the dynamic carbon emission factor, so as to realize the carbon emission accounting of the energy consumption of the enterprise in a multi-energy complementary manner, and improve the real-time property and the reliability of the carbon emission data of the enterprise.
Description
Technical Field
The invention relates to the technical field of enterprise carbon emission accounting, in particular to a method and a system for conducting and calculating a carbon emission factor of a multi-energy complementary enterprise.
Background
The enterprise carbon emission nuclear calculation is a basic premise of effectively developing various carbon emission reduction works and promoting economic green transformation, and is an important support for actively participating in coping with international negotiations of climate change. The carbon accounting can directly quantify the carbon emission data, and can find out potential emission reduction links and modes by analyzing the carbon emission data of each link, which is important to the realization of a carbon neutralization target and the operation of a carbon trade market.
In the prior art, there are generally three ways of accounting for carbon emissions: an emission factor method, a mass balance method and an actual measurement method. For enterprises taking electricity as a main energy source, an emission factor method is generally adopted in the indirect carbon emission formed by calculating the electricity consumption of the enterprises, and accounting is performed based on regional power grid carbon emission factors.
The prior art has the following problems: because of regional energy quality difference, unit combustion efficiency difference and other reasons, large deviation is easy to occur in various energy consumption statistics and carbon emission factor measurement, meanwhile, distributed energy is developed in various regions and enterprises, and the power grid carbon emission factor cannot accurately reflect objective conditions of renewable energy power development of enterprises in various regions. The electric network carbon emission factor calculation data release period takes years as a unit, which is not beneficial to objectively evaluating the carbon emission reduction effect of enterprises and scientifically promoting the carbon emission reduction work, the electric network carbon emission factor calculation is not conducted to the enterprises, the electric carbon market fusion development cannot be effectively promoted, the electricity utilization behavior of the enterprises and the transaction behavior of the enterprises in the electric power market and the carbon market cannot be influenced, and the enterprises cannot be driven to flexibly select a production mode with the advantage of clean energy.
Thus, a need exists for a technique to implement multi-energy complementary enterprise electric carbon emission factor conduction calculations.
Disclosure of Invention
The technical scheme of the invention provides a method and a system for conducting and calculating power carbon emission factors of a multi-energy complementary enterprise, which are used for solving the problem of conducting and calculating the power carbon emission factors of the multi-energy complementary enterprise.
In order to solve the above problems, the present invention provides a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise, the method comprising:
acquiring carbon emission accounting boundary model data of the acquisition device;
acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
acquiring a regional power grid carbon emission factor of a target unit;
calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factor;
and deducing a dynamic carbon emission factor of a target unit in a preset time period based on the real-time carbon emission metering data.
Preferably, the carbon emission accounting boundary model data includes:
distributed photovoltaic generating capacity, energy storage device charging capacity, energy storage device electricity placing capacity, internet surfing capacity and internet surfing capacity.
Preferably, the energy consumption real-time data within the preset time period includes:
the method comprises the steps of distributing photovoltaic generating capacity in a preset time period, charging quantity of an energy storage device in the preset time period, placing electric quantity of the energy storage device in the preset time period, surfing electric quantity in the preset time period and downloading electric quantity in the preset time period.
Preferably, the calculating the real-time carbon emission measurement data of the target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional power grid carbon emission factor includes:
classifying and summarizing the energy consumption real-time data to obtain a classification and summarization result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
and calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
Preferably, the obtaining the regional power grid carbon emission factor of the target unit includes:
the identification information of the target unit is sent to a carbon metering monitoring platform through the acquisition device;
And matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
Preferably, the method further comprises:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And carrying out data encryption on the energy consumption real-time data and the real-time carbon emission metering data, and sending the encrypted energy consumption real-time data and the real-time carbon emission metering data to a carbon metering monitoring platform.
Preferably, the acquiring the real-time data of energy consumption of at least one energy consumption device of the target unit of the access acquisition device in the preset time period includes:
performing communication protocol type conversion on the energy consumption real-time data based on a preset protocol format of a communication protocol;
and storing the converted energy consumption real-time data.
Preferably, the preset time period includes: 15 minutes, 24 hours, 30 days, 365 days.
Based on another aspect of the present invention, the present invention provides a multi-energy complementary enterprise electric carbon emission factor conduction calculation apparatus, the apparatus comprising:
The data storage module is used for acquiring the carbon emission accounting boundary model data of the acquisition device;
acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
the edge calculation module is used for acquiring the regional power grid carbon emission factor of the target unit; calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factor; and deducing a dynamic carbon emission factor of a target unit in a preset time period based on the real-time carbon emission metering data.
Preferably, the edge calculation module is configured to calculate real-time carbon emission measurement data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional power grid carbon emission factor, and is further configured to:
classifying and summarizing the energy consumption real-time data to obtain a classification and summarization result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
and calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
Preferably, the edge calculation module is configured to obtain a regional power grid carbon emission factor of a target unit, and includes:
the identification information of the target unit is sent to a carbon metering monitoring platform through the acquisition device;
and matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
Preferably, the communication module is further included for:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And sending the energy consumption real-time data and the real-time carbon emission metering data encrypted by the data encryption module to a carbon metering monitoring platform.
Based on another aspect of the present invention, the present invention provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program for executing a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise.
Based on another aspect of the present invention, the present invention provides an electronic device, which is characterized in that the electronic device includes: a processor and a memory; wherein,,
the memory is used for storing the processor executable instructions;
the processor is used for reading the executable instructions from the memory and executing the instructions to realize a multi-energy complementary enterprise electric power carbon emission factor conduction calculation method.
The technical scheme of the invention provides a method and a system for conducting and calculating electric power carbon emission factors of a multi-energy complementary enterprise, wherein the method comprises the following steps: acquiring carbon emission accounting boundary model data of the acquisition device; acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period; acquiring a regional power grid carbon emission factor of a target unit; calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factors; based on the real-time carbon emission measurement data, a dynamic carbon emission factor of the target unit in a preset time period is deduced. According to the technical scheme, the acquisition device is adopted to calculate the instant carbon emission of the enterprise according to the self carbon emission accounting boundary model and the energy consumption activity real-time data in the preset time period acquired by the acquisition device, and the dynamic carbon emission factor is deduced according to the carbon emission, so that the carbon emission accounting of the energy consumption of the enterprise in a multi-energy complementary manner is realized, and the real-time performance and the reliability of the carbon emission data of the enterprise are improved.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a flow chart of a method for calculating the conduction of carbon emission factors of a multi-energy complementary enterprise power according to a preferred embodiment of the present invention;
FIG. 2 is a flow chart of a method for calculating the conduction of carbon emission factors of a multi-energy complementary enterprise power according to a preferred embodiment of the present invention;
FIG. 3 is a flow chart of a method for calculating the conduction of carbon emission factors of a multi-energy complementary enterprise power according to a preferred embodiment of the present invention;
FIG. 4 is a flow chart of a method for calculating the conduction of carbon emission factors of a multi-energy complementary enterprise power according to a preferred embodiment of the present invention; and
fig. 5 is a schematic structural view of a carbon emission measuring edge collecting device according to a preferred embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the examples described herein, which are provided to fully and completely disclose the present invention and fully convey the scope of the invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, like elements/components are referred to by like reference numerals.
Unless otherwise indicated, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. In addition, it will be understood that terms defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
FIG. 1 is a flow chart of a method for calculating the conduction of carbon emission factors of a multi-energy complementary enterprise according to a preferred embodiment of the invention. The invention discloses a method for calculating electric power carbon emission factor conduction of a multifunctional complementary enterprise, which comprises the following steps: acquiring carbon emission accounting boundary model information of the acquisition device; acquiring energy consumption activity data of at least one energy utilization device accessed to the acquisition device; and determining instant carbon emission metering data according to the carbon emission accounting boundary model information and the energy consumption activity data and combining regional power grid carbon emission factors. According to the invention, the acquisition device is adopted to calculate the instant carbon emission of the enterprise according to the self carbon emission accounting boundary model and the real-time data integration of the energy consumption activity every 15 minutes acquired by the acquisition device, and the dynamic carbon emission factor is deduced according to the carbon emission, so that the carbon emission accounting of the energy consumption of the enterprise in a multi-energy complementary manner is realized, and the real-time property and the reliability of the enterprise carbon emission data are improved.
As shown in fig. 1, the invention provides a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise, which comprises the following steps:
step 101: acquiring carbon emission accounting boundary model data of the acquisition device;
the invention firstly obtains the self carbon emission accounting boundary model information of the acquisition device, wherein the carbon emission accounting boundary model information comprises: the distributed photovoltaic power generation amount, the energy storage charging and discharging amount, the internet surfing electric amount and the internet surfing electric amount type data and the carbon emission accounting boundary model information data are used for determining carbon accounting boundary information of the acquisition device.
Preferably, the carbon emission accounting boundary model data includes:
distributed photovoltaic generating capacity, energy storage device charging capacity, energy storage device electricity placing capacity, internet surfing capacity and internet surfing capacity.
Step 102: acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
preferably, the energy consumption real-time data within the preset time period includes:
the method comprises the steps of distributing photovoltaic generating capacity in a preset time period, charging quantity of an energy storage device in the preset time period, placing electric quantity of the energy storage device in the preset time period, surfing electric quantity in the preset time period and downloading electric quantity in the preset time period.
Preferably, acquiring the real-time data of energy consumption of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period includes:
performing communication protocol type conversion on the energy consumption real-time data based on a preset protocol format of the communication protocol;
and storing the converted energy consumption real-time data.
Preferably, the preset time period includes: 15 minutes, 24 hours, 30 days, 365 days.
The method comprises the steps of obtaining energy consumption activity data metered by various energy metering devices connected with a collecting device;
wherein the energy consumption activity data metered by the plurality of energy metering devices comprises: 15 minutes of distributed photovoltaic power generation, 15 minutes of energy storage device charge, 15 minutes of energy storage device placement power, 15 minutes of network surfing power and 15 minutes of network discharging power; a variety of energy metering devices are used to determine the energy class consumption per 15 minutes for a multi-energy complementary enterprise.
The communication protocol conversion module is arranged between the local communication module and the data storage module;
the communication protocol conversion module is used for receiving the energy consumption activity data uploaded by the local communication module, carrying out communication protocol type conversion on the energy consumption activity data based on a preset protocol format, and sending the energy consumption activity data in the preset protocol format to the data storage module.
The dynamic carbon emission factors include: carbon emission factor 15 minutes, day, year.
Step 103: acquiring a regional power grid carbon emission factor of a target unit;
preferably, obtaining the regional grid carbon emission factor of the target unit includes:
the identification information of the target unit is sent to a carbon metering monitoring platform through a collecting device;
and matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
The method comprises the steps of obtaining the regional power grid carbon emission factor of an enterprise connected with a collection device;
the regional power grid carbon emission factor of the enterprise is a regional power grid carbon emission factor issued by the administrative province of the enterprise; and the acquisition device receives the regional power grid carbon emission factor data packet fed back by the carbon metering monitoring platform.
Transmitting regional grid carbon emission factors issued by a multi-energy complementary enterprise administrative province to an affiliated acquisition device, comprising:
the acquisition device uploads the multi-energy complementary enterprise administrative provincial domain codes to the carbon metering monitoring platform;
comparing the administrative provincial codes of the multi-energy complementary enterprises with a preset regional power grid carbon emission factor database by adopting a carbon metering monitoring platform, and determining regional power grid carbon emission factors according to the comparison result;
And the carbon metering monitoring platform transmits the comparison result to the acquisition device and receives the regional power grid carbon emission factor data packet issued by the carbon metering monitoring platform.
Step 104: calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factors;
preferably, calculating the real-time carbon emission measurement data of the target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional power grid carbon emission factor includes:
classifying and summarizing the energy consumption real-time data to obtain a classifying and summarizing result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
and calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
According to the 15-minute energy consumption data acquired by the acquisition device, the carbon accounting boundary model of the acquisition device and the regional power grid carbon emission factor are combined, and the 15-minute enterprise carbon emission is calculated; the present invention is illustrated with 15 minutes of energy consumption data only, but embodiments of the present invention are not limited to 15 minutes.
According to 15 minutes energy consumption data that collection system gathered, combine collection system carbon to calculate boundary model and regional electric wire netting carbon emission factor, calculate 15 minutes carbon emission, include:
classifying and summarizing the energy consumption activity data, and determining carbon accounting boundary model information corresponding to the same type of energy activity data according to a classified summarizing result;
and carrying out edge calculation of the acquisition device based on the carbon accounting boundary model information and the same type of energy activity data to obtain the carbon emission of the enterprise.
Step 105: based on the real-time carbon emission measurement data, a dynamic carbon emission factor of the target unit in a preset time period is deduced.
Preferably, the method further comprises:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And carrying out data encryption on the energy consumption real-time data and the real-time carbon emission metering data, and sending the encrypted energy consumption real-time data and the real-time carbon emission metering data to a carbon metering monitoring platform.
According to the enterprise carbon emission calculated by the acquisition device, the dynamic carbon emission factor is deduced by combining the acquired energy consumption data.
The carbon emission factor package of the regional power grid is used for sending the carbon emission factor package of the regional power grid to the data storage module, and receiving the carbon emission factor of the regional power grid issued by the carbon metering monitoring platform, so that the edge calculation module determines carbon emission data according to the energy consumption activity data and the carbon emission factor of the regional power grid and uploads the carbon emission data to the carbon metering monitoring platform;
and the uplink communication module is also used for uploading dynamic carbon emission factors deduced by combining the acquired energy consumption data to the carbon metering monitoring platform according to the enterprise carbon emission calculated by the acquisition device.
The data encryption module is arranged between the uplink communication module and the edge calculation module;
the data encryption module is used for respectively carrying out data encryption processing on the energy consumption activity data and the carbon emission metering data, and transmitting the obtained encrypted activity data and the obtained encrypted metering data to the uplink communication module.
The parameter setting module is connected with the edge calculation module and is used for acquiring and displaying the energy consumption activity classification data and the carbon emission data calculated and output by the edge metering module.
The invention provides a method for conducting and calculating electric power carbon emission factors of a multifunctional complementary enterprise, which is characterized in that a dynamic carbon emission factor is formed by calculating an edge calculation module of a collecting device in real time, carbon accounting is executed in the collecting device in real time, and the instantaneity and the accuracy of carbon accounting data are improved.
The invention provides a multi-energy complementary enterprise electric power carbon emission factor conduction calculation device, which comprises:
the data storage module is used for acquiring the carbon emission accounting boundary model data of the acquisition device;
acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
the edge calculation module is used for acquiring the regional power grid carbon emission factor of the target unit; calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factors; based on the real-time carbon emission measurement data, a dynamic carbon emission factor of the target unit in a preset time period is deduced.
Preferably, the edge calculation module is configured to calculate the real-time carbon emission measurement data of the target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional power grid carbon emission factor, and is further configured to:
classifying and summarizing the energy consumption real-time data to obtain a classifying and summarizing result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
And calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
Preferably, the edge calculation module is configured to obtain a regional power grid carbon emission factor of a target unit, and includes:
the identification information of the target unit is sent to a carbon metering monitoring platform through a collecting device;
and matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
Preferably, the apparatus further comprises a communication module for:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And sending the energy consumption real-time data and the real-time carbon emission metering data encrypted by the data encryption module to a carbon metering monitoring platform.
The invention provides a multi-energy complementary enterprise electric power carbon emission collection device, which is used for executing the electric power carbon emission factor conduction calculation method, and comprises the following steps: the edge calculation module is used for acquiring the regional power grid carbon emission factor of the acquisition device, performing coupling calculation according to the energy activity data acquired by the acquisition device to form a dynamic carbon emission factor, wherein the dynamic carbon emission factor comprises: carbon emission factors of 15 minutes, days and years; the local communication module is used for acquiring the energy consumption activity data of at least one energy utilization device; the data storage module is used for classifying and summarizing the energy consumption activity data and storing the calculation boundary model information according to the carbon emission and the calculation result of the energy consumption activity data and the regional power grid carbon emission factors; the uplink communication module is used for sending the regional power grid carbon emission factor package to the data storage module, receiving the regional power grid carbon emission factor issued by the carbon metering monitoring platform, enabling the edge calculation module to determine carbon emission data according to the energy consumption activity data and the regional power grid carbon emission factor, uploading the carbon emission data to the carbon metering monitoring platform, and uploading the dynamic carbon emission factor deduced according to the carbon emission calculated by the acquisition device and combined with the acquired energy consumption data to the carbon metering monitoring platform; the communication protocol conversion module is used for receiving the energy consumption activity data uploaded by the local communication module, carrying out communication protocol type conversion on the energy consumption activity data based on a preset protocol format, and sending the energy consumption activity data in the preset protocol format to the data storage module; the data encryption module is used for respectively carrying out data encryption processing on the energy consumption activity data and the carbon emission metering data and transmitting the obtained encrypted activity data and the obtained encrypted metering data to the uplink communication module; and the parameter setting module is used for acquiring and displaying the energy consumption activity classification data and the carbon emission data calculated and output by the edge metering module.
The invention is executed by an edge acquisition device, and the carbon emission accounting boundary model information of the acquisition device and the 15-minute-level energy consumption activity data of at least one energy utilization device connected to the acquisition device are obtained; according to the carbon emission amount converted by the distributed photovoltaic power generation amount in the carbon emission calculation boundary model, the carbon emission amount converted by the energy storage charge-discharge amount conversion consumption, the carbon emission amount deducted by the on-grid power quantity, the carbon emission amount type data calculated by the off-grid power quantity, the energy consumption activity classification data and the carbon emission calculation boundary model information data type are in one-to-one correspondence, the instant carbon emission metering data are determined by combining regional power grid carbon emission factors, and the dynamic carbon emission factors are deduced according to the carbon emission amount, so that the carbon emission calculation of energy used in a multi-energy complementary enterprise is realized, and the instantaneity and reliability of the enterprise carbon emission data are improved.
The invention provides a method and a device for conducting and calculating electric power carbon emission factors of a multi-energy complementary enterprise, which are used for acquiring energy consumption activity data of energy consumption equipment of the enterprise; and calculating the instant carbon emission of the enterprise in real time according to the carbon emission calculation boundary model information and the energy consumption activity classification data, and deducing a dynamic carbon emission factor according to the carbon emission so as to realize the carbon emission calculation of energy consumption of the multi-energy complementary enterprise and improve the instantaneity and reliability of the enterprise carbon emission data.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Fig. 2 is a flowchart of a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise, which is provided by the embodiment of the invention, and the method can be suitable for an application scenario of executing multi-energy data collection and carbon accounting according to energy activity data of an enterprise at an edge collection device, wherein the edge collection device can be realized in a form of hardware and/or software.
Referring to fig. 2, the method for calculating the electric power carbon emission factor of the multi-energy complementary enterprise specifically includes the following steps:
step S1: and acquiring the self carbon emission accounting boundary model information of the acquisition device.
The carbon emission accounting boundary model information comprises information such as carbon emission amount converted by one degree of electricity (1 kilowatt hour) of distributed photovoltaic, carbon emission amount converted by energy storage charge-discharge amount conversion efficiency consumption, carbon emission amount reduced by net surfing electric quantity deduction, carbon emission amount calculated by net surfing electric quantity and the like.
Step S2: and acquiring energy consumption activity data metered by various energy metering devices connected to the acquisition device.
The energy consumption activity data AD are the electric quantity generated by the enterprise installation distributed photovoltaic power station after each 15 minutes, the electric quantity consumed (generated) by the enterprise installation energy storage device after each 15 minutes of charging (discharging), the conversion efficiency, the electric quantity reversely conveyed to the power grid by the enterprise after each 15 minutes, the electric quantity consumed from the power grid by the enterprise in each 15 minutes of period due to the production activity process and the like.
According to the invention, energy metering equipment with single-phase and three-phase forward and reverse metering can be adopted to be in communication connection with the acquisition device, the energy metering equipment is used for detecting the load of the inlet wire end of the enterprise side power grid, the distributed photovoltaic and energy storage device and the energy consumption activity data AD of the link end of the low-voltage power grid, and the detected data is transmitted to the edge acquisition device.
Step S3: and acquiring the regional power grid carbon emission factor of the enterprise connected with the acquisition device.
Wherein the emission factor EF is a greenhouse gas emission coefficient corresponding to the energy consumption activity data AD for characterizing the amount of activity per unit production or consumption, e.g. the emission factor EF may comprise the carbon or elemental carbon content per unit heating value, the oxidation rate, etc.
According to the invention, the regional power grid carbon emission factor of the enterprise is firstly set by a parameter setting module of an acquisition device connected to the enterprise, and then the provincial administrative district code of the enterprise is interacted with the carbon emission monitoring platform data by the acquisition device, so as to obtain the regional power grid carbon emission factor EF corresponding to the provincial administrative district code.
Specifically, the edge collecting device sends out an emission factor query data packet through a communication technology, and receives a regional power grid carbon emission factor feedback data packet returned after query, wherein the regional power grid carbon emission factor feedback data packet comprises the latest emission factor EF of the region where the edge collecting device is located, and the emission factor EF is a parameter issued by a national government administration or calculated by regional representative measurement data, and is not limited.
Step S4: and according to the 15-minute energy consumption data acquired by the acquisition device, combining the carbon accounting boundary model of the acquisition device and the regional power grid carbon emission factor, and accounting out the 15-minute carbon emission.
In the invention, the edge collecting device substitutes the determined regional power grid carbon emission factor into a greenhouse gas emission basic equation shown in a formula I to calculate the greenhouse gas carbon emission (GHG):
carbon emission (GHG) =energy consumption Activity Data (ADi) ×emission factor (EFi) (formula one).
ADi represents energy consumption activity data of distributed photovoltaic power generation capacity, charge and discharge loss of an energy storage device, on-line power and off-line power every 15 minutes; EFi the greenhouse gas emission coefficient per unit production or consumption activity corresponding to ADi, i being a positive integer of 1 or more.
Specifically, when the carbon emission is calculated, the edge collecting device in the multi-energy complementary enterprise can correspond to the energy metering devices, receive the energy consumption activity data AD of different types uploaded by each energy metering device, and classify, mark and summarize the energy consumption activity data AD according to the energy types, for example, mark the energy consumption activity data of the ith supply energy source in the jth energy metering device as adi.j, and mark the energy consumption activity data of the ith supply energy source in the kth energy metering device as adi.k. The edge collecting device collects ADi according to the energy consumption activity data of the j-th energy metering equipment and the k-th energy metering equipment which belong to the i-th energy supply, and calculates the carbon emission of all the energy metering equipment connected to the collecting device with the corresponding emission factor EFi.
Step S5: and deducing a dynamic carbon emission factor according to the carbon emission calculated by the acquisition device core and the acquired energy consumption data.
In the invention, the edge collecting device gathers the carbon emission calculated according to the determined energy consumption activity data AD of different types and calculates the total carbon emission (A0) of greenhouse gases of every 15 minutes of an enterprise:
a0 = Σbi (formula two).
Wherein A0 is the total carbon emission, bi is the carbon emission calculated by the consumption of the energy i; i is one of energy types in the distributed photovoltaic power generation amount, the charge and discharge loss amount of the energy storage device, the on-line power quantity and the off-line power quantity.
Fig. 3 is a flowchart of another method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise, and on the basis of fig. 2, a specific embodiment of acquiring energy consumption activity data metered by a plurality of energy metering devices connected to a collecting device is exemplarily shown.
As shown in fig. 3, the method for calculating the electric power carbon emission factor of the multi-energy complementary enterprise specifically includes the following steps:
step S1: and acquiring the self carbon emission accounting boundary model information of the acquisition device.
Step S201: and obtaining 15-minute distributed photovoltaic power generation.
Step S202: and acquiring the charge quantity of the energy storage device for 15 minutes.
Step S203: and acquiring the storage capacity of the energy storage device for 15 minutes.
Step S204: and obtaining the online electric quantity for 15 minutes.
Step S205: and acquiring the power-off quantity of the network after 15 minutes.
Step S3: and acquiring the regional power grid carbon emission factor of the enterprise connected with the acquisition device.
Specifically, the edge collecting device sends an emission factor query data packet through a communication technology, and receives a regional power grid carbon emission factor feedback data packet returned after query, wherein the regional power grid carbon emission factor feedback data packet comprises the latest emission factors EFi (i=1, 2,3,4, 5) of the region where the edge collecting device is located, and the latest emission factors EF1, EF2, EF3 and EF4 are manually set by a parameter setting module of the edge collecting device. The emission factor EF1 is a distributed photovoltaic power generation carbon emission factor obtained by estimating regional representative measurement data, the emission factor EF2 is an energy storage and charge conversion consumption carbon emission factor obtained by estimating regional representative measurement data, the emission factor EF3 is an energy storage and discharge conversion consumption carbon emission factor obtained by estimating regional representative measurement data, the emission factor EF4 is an internet-surfing counteraction carbon emission factor obtained by estimating regional representative measurement data, and the emission factor EF5 is a parameter issued by the national government administration, which is not limited.
Fig. 4 is a flowchart of another method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise, and on the basis of fig. 1, an embodiment of calculating 15 minutes of carbon emission according to 15 minutes of energy consumption data acquired by an acquisition device by combining an acquisition device carbon accounting boundary model and regional power grid carbon emission factors is exemplarily shown.
As shown in fig. 4, the method for calculating the electric power carbon emission factor of the multi-energy complementary enterprise specifically includes the following steps:
step S1: and acquiring the self carbon emission accounting boundary model information of the acquisition device.
Step S2: and acquiring energy consumption activity data metered by various energy metering devices connected to the acquisition device.
Step S3: and acquiring the regional power grid carbon emission factor of the enterprise connected with the acquisition device.
Step S401: accounting the carbon emission (+)' of the photovoltaic power generation for 15 minutes.
Step S402: accounting for 15 minutes, energy storage and charging conversion consumes carbon (+).
Step S403: accounting for 15 minutes to convert the energy storage discharge into consumed carbon (+).
Step S404: accounting 15 minutes of surfing electricity counteracts carbon emission (-).
Step S405: accounting the carbon emission of the power of the net under 15 minutes (+).
Step S5: and deducing a dynamic carbon emission factor according to the carbon emission calculated by the acquisition device core and the acquired energy consumption data.
Specifically, the edge collection device obtains a regional power grid carbon emission factor feedback data packet EFi (i=1, 2,3,4, 5) through step S3, performs carbon emission accounting in a one-to-one correspondence manner in step S401, step S402, step S403, step S404, step S405 and EFi (i=1, 2,3,4, 5), and step S5 sums up the carbon emission A0 calculated by the above step and sums up the energy consumption activity data E0 measured by the energy metering device in step S2, and derives a 15-minute dynamic carbon emission factor by using the formula three:
EF0 = A0/E0 (formula three).
Fig. 5 is a schematic structural diagram of a carbon emission measuring edge collecting device provided by the invention, wherein the collecting device is used for executing the carbon emission factor conduction calculating method and has corresponding functional modules and beneficial effects of the executing method.
As shown in fig. 5, the carbon emission measuring edge collecting device 1 includes: the parameter setting module 100 is used for inquiring and setting the enterprise carbon emission accounting boundary model information; a carbon emission accounting boundary model 101 for delivering the latest regional grid carbon emission factor to an edge calculation module 103; the uplink communication module 102 is configured to send the latest regional power grid carbon emission factor query data packet to the carbon emission monitoring platform 0, receive a regional power grid carbon emission factor feedback data packet sent by the carbon emission monitoring platform 0, and transmit the regional power grid carbon emission factor feedback data packet to the carbon emission accounting boundary model 101 through the edge calculation module 103 for updating; the edge calculation module 103 is used for acquiring the regional power grid carbon emission factor of the carbon emission accounting boundary model 101, acquiring the energy consumption activity data of the data storage module 104, and determining carbon emission metering data according to the energy consumption activity data and the regional power grid carbon emission factor; a data storage module 104, configured to obtain energy consumption activity data of at least one energy metering device 2; the local communication module 105 is configured to receive the energy consumption activity data fed back by any energy metering device 2.
The local communication module 105 provides various types of electrical I/O interfaces, including but not limited to: carrier interface, WISUN interface, loRa interface, 485 interface.
The uplink communication module 102 is in communication connection with the carbon emission monitoring platform through an Ethernet data interface/4G communication interface, on one hand, the uplink communication module 102 packages and forwards the 15-minute carbon emission and dynamic carbon emission factor data calculated by the edge calculation module 103 according to the data format required by the platform; on the other hand, the uplink communication module 102 also transmits the 15-minute energy consumption activity data obtained by the data storage module 104 to the local energy management system, and provides real-time status data of the energy metering device to realize load monitoring.
Specifically, in accounting for carbon emissions, the local communication module 105 receives 15 minute energy consumption activity data AD uploaded by different energy metering devices and transmits the received 15 minute energy consumption activity data AD to the data storage module 104. The edge calculation module 103 reads the data of the data storage module, and sorts, marks and summarizes the energy consumption activity data AD according to the energy type, for example, marks the energy consumption activity data of the ith supply energy in the jth energy metering device as adi.j, and marks the energy consumption activity data of the ith supply energy in the kth energy metering device as adi.k. Meanwhile, the edge calculation module 103 collects ADi according to the energy consumption activity data in the j-th and k-th energy metering devices of the ith energy supply, and calculates the carbon emission of all the energy metering devices connected to the edge collection device 1 with the corresponding emission factor EFi. The edge calculation module 103 transmits the calculated carbon emissions to the data storage module, which sums up the total 15 minute carbon emissions A0 and calculates a 15 minute dynamic carbon emission factor in combination with the 15 minute total energy consumption activity data E0.
After the carbon emission and dynamic carbon emission factor data are obtained for 15 minutes, the uplink communication module 102 also packs and forwards the carbon emission data every 15 minutes, and realizes the carbon emission curve display of the carbon emission monitoring platform on a multifunctional complementary enterprise by forwarding the periodic data every 15 minutes, so as to monitor the dynamic carbon emission of the enterprise in real time.
Therefore, the invention completes the real-time calculation of the carbon emission data of the multifunctional complementary enterprises through the edge acquisition device, solves the problem that the carbon emission factor of the power grid cannot accurately reflect the objective condition of the renewable energy power development of the enterprises in each region in real time in the development of distributed energy sources in each region, promotes the fusion development of the electric carbon market, influences the electricity utilization behavior of the enterprises and the transaction behavior of the enterprises in the electric power market and the carbon market, and cannot drive the enterprises to flexibly select the production mode with the advantage of clean energy.
In summary, the electric power carbon emission factor conduction calculation method and the collection device are executed by the edge collection device, and the collection device obtains 15-minute distributed photovoltaic power generation capacity, energy storage device charging and discharging capacity, internet surfing capacity and internet surfing capacity energy consumption activity data of the energy metering equipment; and calculating 15-minute classified carbon emission according to the regional power grid carbon emission factor cores in one-to-one correspondence, summarizing total 15-minute carbon emission and 15-minute total energy consumption activity data, and calculating 15-minute dynamic carbon emission factors. The problem that the carbon emission of the enterprise cannot be accurately reflected in real time based on the annual issued power grid carbon emission factors in the development of distributed energy sources by the multifunctional complementary enterprise is solved, and the instantaneity and the reliability of the enterprise carbon emission data are improved. Promote the fusion development of the electric carbon market, and promote enterprises to flexibly select production modes with cleaner energy advantages.
The invention provides a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise and an acquisition device, wherein the method comprises the following steps: acquiring carbon emission accounting boundary model information of the acquisition device; acquiring energy consumption activity data of at least one energy utilization device accessed to the acquisition device; and determining instant carbon emission metering data according to the carbon emission accounting boundary model information and the energy consumption activity data and combining regional power grid carbon emission factors. According to the invention, the acquisition device is adopted to calculate the instant carbon emission of the enterprise according to the self carbon emission accounting boundary model and the real-time data integration of the energy consumption activity every 15 minutes acquired by the acquisition device, and the dynamic carbon emission factor is deduced according to the carbon emission, so that the carbon emission accounting of the energy consumption of the enterprise in a multi-energy complementary manner is realized, and the real-time property and the reliability of the enterprise carbon emission data are improved.
The invention provides a computer readable storage medium, which stores a computer program for executing a method for calculating electric power carbon emission factor conduction of a multi-energy complementary enterprise.
The present invention provides an electronic device characterized by comprising: a processor and a memory; wherein,,
A memory for storing processor-executable instructions;
and the processor is used for reading the executable instructions from the memory and executing the instructions to realize a multi-energy complementary enterprise electric power carbon emission factor conduction calculation method.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the invention can be realized by adopting various computer languages, such as object-oriented programming language Java, an transliteration script language JavaScript and the like.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
The invention has been described with reference to a few embodiments. However, as is well known to those skilled in the art, other embodiments than the above disclosed invention are equally possible within the scope of the invention, as defined by the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise therein. All references to "a/an/the [ means, component, etc. ]" are to be interpreted openly as referring to at least one instance of said means, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
Claims (14)
1. A method of multi-energy complementary enterprise electrical carbon emission factor conduction calculation, the method comprising:
Acquiring carbon emission accounting boundary model data of the acquisition device;
acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
acquiring a regional power grid carbon emission factor of a target unit;
calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factor;
and deducing a dynamic carbon emission factor of a target unit in a preset time period based on the real-time carbon emission metering data.
2. The method of claim 1, the carbon emission accounting boundary model data comprising:
distributed photovoltaic generating capacity, energy storage device charging capacity, energy storage device electricity placing capacity, internet surfing capacity and internet surfing capacity.
3. The method of claim 1, the energy consumption real-time data for a preset period of time comprising:
the method comprises the steps of distributing photovoltaic generating capacity in a preset time period, charging quantity of an energy storage device in the preset time period, placing electric quantity of the energy storage device in the preset time period, surfing electric quantity in the preset time period and downloading electric quantity in the preset time period.
4. The method of claim 1, the calculating real-time carbon emission metrology data for a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional grid carbon emission factor, comprising:
Classifying and summarizing the energy consumption real-time data to obtain a classification and summarization result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
and calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
5. The method of claim 1, the obtaining regional grid carbon emission factors for a target unit comprising:
the identification information of the target unit is sent to a carbon metering monitoring platform through the acquisition device;
and matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
6. The method of claim 1, further comprising:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And carrying out data encryption on the energy consumption real-time data and the real-time carbon emission metering data, and sending the encrypted energy consumption real-time data and the real-time carbon emission metering data to a carbon metering monitoring platform.
7. The method of claim 1, wherein the acquiring the real-time data of energy consumption of the at least one energy consumption device of the target unit of the access acquisition device for the preset period of time comprises:
performing communication protocol type conversion on the energy consumption real-time data based on a preset protocol format of a communication protocol;
and storing the converted energy consumption real-time data.
8. The method of claim 1, the preset time period comprising: 15 minutes, 24 hours, 30 days, 365 days.
9. A multi-energy complementary enterprise electrical carbon emission factor conduction computing device, the device comprising:
the data storage module is used for acquiring the carbon emission accounting boundary model data of the acquisition device;
acquiring energy consumption real-time data of at least one energy consumption device of a target unit accessed to the acquisition device in a preset time period;
the edge calculation module is used for acquiring the regional power grid carbon emission factor of the target unit; calculating real-time carbon emission metering data of a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data and the regional power grid carbon emission factor; and deducing a dynamic carbon emission factor of a target unit in a preset time period based on the real-time carbon emission metering data.
10. The apparatus of claim 9, the edge calculation module for the calculating real-time carbon emission metering data for a target unit based on the carbon emission accounting boundary model data, the energy consumption real-time data, and the regional grid carbon emission factor, further for:
classifying and summarizing the energy consumption real-time data to obtain a classification and summarization result of the energy consumption real-time data;
determining carbon emission accounting boundary model data corresponding to the same type of energy based on the energy consumption real-time data classification summary result;
and calculating real-time carbon emission metering data of a target unit based on the determined carbon emission accounting boundary model data, the real-time energy consumption data of the same type of energy sources and the regional power grid carbon emission factors.
11. The apparatus of claim 9, the edge calculation module to obtain a regional grid carbon emission factor for a target unit, comprising:
the identification information of the target unit is sent to a carbon metering monitoring platform through the acquisition device;
and matching the regional power grid carbon emission factor based on the identification information of the target unit through the carbon metering monitoring platform, and sending the regional power grid carbon emission factor to the acquisition device.
12. The apparatus of claim 9, further comprising a communication module to:
transmitting the calculated real-time carbon emission measurement data of the target unit to a carbon measurement monitoring platform; or alternatively
Transmitting the deduced dynamic carbon emission factor of the target unit in a preset time period to a carbon metering monitoring platform; or alternatively
And sending the energy consumption real-time data and the real-time carbon emission metering data encrypted by the data encryption module to a carbon metering monitoring platform.
13. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program for executing the method of any one of claims 1-8.
14. An electronic device, the electronic device comprising: a processor and a memory; wherein,,
the memory is used for storing the processor executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any one of claims 1-8.
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