Carbon emission online measurement and evaluation function module for active power distribution network park

Abstract

The invention discloses an active power distribution network park carbon emission online measurement and evaluation function module, which relates to the technical field of power systems, and comprises the steps of constructing a data acquisition module, establishing a data acquisition model in a power grid and park energy network, and acquiring power grid operation data, park load data and internal distributed energy power generation data. The method has the beneficial effects that a novel carbon emission measuring and calculating method is provided for the park energy network, and a real-time carbon emission measuring and calculating model is constructed by integrating energy data acquisition and load balance analysis; an electric network and a gas network are covered, and the contribution of various energy forms to carbon emission is comprehensively considered.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a function module for online carbon emission measurement and evaluation in an active distribution network park. Background Art

[0002] In addition to large-scale development of clean energy on the power generation side, the penetration rate of distributed power sources on the power distribution and consumption sides is also increasing rapidly. The traditional single-source radial distribution network will become a multi-source active distribution network, and the traditional single-energy supply on the user side begins to evolve into multi-energy collaborative supply. However, in the previous research on related applications of active distribution networks, with the integration of heterogeneous energy networks such as electricity, heat, gas, and storage and coupled terminals, the existing active distribution network source-network-load-storage analysis platform based on power flow and its key technologies can no longer achieve dynamic information interaction of multi-energy flow systems, especially cannot meet the requirements of low-carbon operation. At the same time, realizing online carbon emission measurement will become a core function in the power system and energy industry, which not only helps to meet policy compliance requirements, but also helps to improve energy utilization efficiency, optimize power dispatching, and promote the development of green and low-carbon economy. Currently, the inventory method of the Intergovernmental Panel on Climate Change (IPCC) mainly considers direct carbon emissions within a specific boundary, aiming to calculate direct carbon emissions for the energy consumed on the production side; the current carbon emission measurement method proposed by the Ministry of Ecology and Environment of the People's Republic of China aims to carry out carbon emission measurement on a regional and provincial basis. The method mainly uses the emission factor method, selecting the national published regional or provincial carbon emission factors and multiplying them by the power generation to obtain the carbon dioxide emissions. However, since the data is collected on an annual basis, its carbon emissions often have a lag; in addition, selecting the fixed carbon emission factors published by the country ignores the influence of time and space dimensions to a certain extent, and cannot be used as an incentive signal to guide enterprises to adjust self-disciplinedly, that is, reduce the electricity load when the carbon emission factor is high, and reasonably increase production capacity and electricity consumption when the carbon emission factor is low. Summary of the Invention

[0003] In view of the above or existing problems in the art, the present invention is proposed.

[0004] Therefore, the object of the present invention is to provide a function module for online carbon emission measurement and evaluation in an active distribution network park, which can solve the problems mentioned in the background art.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A function module for online carbon emission measurement and evaluation in an active distribution network park, which includes S1: constructing a data acquisition module, forming a data acquisition model C in the power grid and the park energy network xyz , collecting power grid operation data, park load data, and internal distributed energy generation data;

[0006] S2: Build a power balance classification diagram based on the power load data of the park, refine the power sources that meet the power load demand at each moment, and build a dynamic carbon emission factor for the park power network based on various types of power and their corresponding carbon emission factors;

[0007] S3: Construct a gas balance classification diagram based on the gas load data of the park, obtain the gas consumption power of gas boilers and gas loads at each time, and construct a carbon emission calculation model for the gas network at each time in the park based on the carbon emission factor corresponding to natural gas;

[0008] S4: According to the dynamic carbon emission factor model of the electricity network at each moment constructed in step S2, multiply it by the amount of electricity of each type at each moment and integrate it over time; add the carbon emission model of the gas network in step S3 to obtain the real-time carbon emissions of the park energy system;

[0009] S5: According to the dynamic carbon emission factor of electricity in step S2, compare it with the provincial electricity carbon emission factor released by the Ministry of Ecology and Environment of the People's Republic of China, set the emission factor classification range, and construct "high", "medium" and "low" carbon evaluation indicators. Enterprises can carry out self-discipline adjustments based on the evaluation indicators to effectively reduce overall carbon emissions.

[0010] As a preferred solution of the online carbon emission measurement and evaluation function module for active distribution network park described in the present invention, wherein: the internal distributed energy generation data includes gas, gas purchase, electricity consumption, renewable energy generation, and power purchase from the power grid;

[0011] The carbon emission factors include coal-fired power generation, gas-fired power generation, wind power, and solar power.

[0012] As a preferred solution of the online carbon emission measurement and evaluation function module for the active distribution network park of the present invention, the step S1 specifically refers to: establishing a data collection model C in the power grid and the park energy network xyz :

[0013]

[0014] Where: σ represents the collection interval of electric energy data; u represents the interaction deviation; ψ represents the electric energy data collection ratio; the deployment spacing D of different nodes is:

[0015]

[0016] Where: ω represents the total coverage of the node; g represents the data collection unit distance; c represents the total number of data collection times of the node; π represents the data collection correction coefficient; θ represents the energy data collection frequency.

[0017] As a preferred solution for the carbon emission online measurement and evaluation function module of the active distribution network park described in the present invention, wherein: the step S2 specifically refers to: the real-time calculation method of the dynamic carbon emission factor C e (τ):

[0018] C e (τ) = [∑CEm g (τ) + ∑CEm j (τ) - ∑CEm l (τ)] / [∑P grid (τ) + ∑P j (τ) - ∑P l (τ)]

[0019] In the formula: CEm k (τ) is the carbon emission generated on the source side when the park j purchases electricity from the power grid at time τ, kgCO2; CEm j (τ) is the carbon emission generated by the non-zero-carbon distributed power sources in the park j at time τ, kgCO2; CEm l (τ) is the carbon emission corresponding to the tie-line electricity at time τ, kgCO2; P grid (τ) is the electricity transmitted from the power grid to the park j at time τ, kWh; P j (τ) is the power generation of the non-zero-carbon distributed power sources in the park j at time τ, kWh; P l (τ) is the electricity on the tie-line at time τ, kWh; where:

[0020]

[0021] In the formula: C r,c (τ), C r,g (τ), C r,k (τ), C r,s (τ), C r,l (τ) are the carbon emission factors per kWh of coal-fired units, gas-fired units, non-zero-carbon power source k in the park j, energy storage, and tie-line at time τ, respectively, kgCO2 / kWh; P c (τ), P g (τ), P j,k (τ), P j,s (τ), P l (τ) are the electricity of coal-fired units on the power grid side, gas-fired units on the power grid side, non-zero-carbon power source k in the park, the discharge amount of park energy storage, and the park tie-line electricity at time τ, respectively, kWh; by decomposing the impact of each energy type on carbon emissions, the calculation of the dynamic carbon emission factor is completed, and the range fluctuation of -0.214 to +0.501 kgCO2 / kWh will occur when compared with the provincial fixed carbon emission factor; according to the constructed dynamic carbon emission factor of the power grid, the carbon emission model T of the park power grid is further obtained c :

[0022] T c = ∫P T (τ)·C e (τ)·dτ

[0023] Where: Where: C e (τ) is the dynamic carbon emission factor of the power in this park, kgCO2 / kWh; P T is the electrical load of the park, kWh.

[0024] As a preferred solution of the carbon emission online measurement and evaluation function module for the active distribution network park described in the present invention, where: the step S3 specifically refers to: using the natural gas emission factor C r,g = 0.40 kgCO2 / kWh to construct the carbon emission model G of the gas network in the park c :

[0025] G c = ∫(P GB,g (τ) + P L,g (τ))·C r,g ·dτ

[0026] Where: P GB,g (τ) and P L,g (τ) are the gas consumption power and gas load power of the gas boiler at time τ, respectively, kWh.

[0027] As a preferred solution of the carbon emission online measurement and evaluation function module for the active distribution network park described in the present invention, where: the step S4 specifically refers to: a multi-energy flow model of the park that can integrate electricity and gas network data to achieve a dynamic carbon emission measurement model Y c :

[0028] Y c = G c + T c = ∫[(P GB,g (τ) + P L,g (τ))·C r,g + P T (τ)·C e (τ)]·dτ.

[0029] As a preferred solution of the carbon emission online measurement and evaluation function module for the active distribution network park described in the present invention, where: the step S5 specifically refers to: the design and application of hierarchical evaluation indicators, using the provincial fixed carbon emission factor EF p = 0.5182 kgCO2 / kWh as the benchmark, setting the carbon emission classification standard for the park, and using the dynamic emission factor C eWhen (τ) ≥ 0.7182 kgCO2 / kWh, it is set as the "high" carbon interval, C e When (τ) ∈ [0.3182, 0.7182) kgCO2 / kWh, it is set as the "medium" carbon interval, C e When (τ) < 0.3182 kgCO2 / kWh, it is set as the "low" carbon interval, and these three evaluation criteria are used as the reference basis for production optimization and energy efficiency improvement.

[0030] Advantages of the present invention: The present invention proposes a new carbon emission measurement method for the park energy network. By integrating energy data collection and load balance analysis, a real-time carbon emission measurement model is constructed; it covers the power network and the gas network, comprehensively considering the contributions of various energy forms to carbon emissions; and according to the emission factors obtained from the measurement model, interval classification is carried out to construct "high", "medium", and "low" evaluation indicators to guide enterprises to adjust independently, providing an operable path for realizing a low-carbon park. Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0032] Figure 1 It is the power network balance diagram of the present invention.

[0033] Figure 2 It is the gas network balance diagram of the present invention.

[0034] Figure 3 It is the power dynamic carbon emission factor diagram of the present invention.

[0035] Figure 4 It is the carbon emission diagram of each moment of the park energy system of the present invention.

[0036] Figure 5 It is the carbon emission classification evaluation index diagram of the present invention. Detailed Embodiments

[0037] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will give a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification.

[0038] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from the description herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0039] Secondly, the so-called "one embodiment" or "embodiment" herein refers to specific features, structures or characteristics that may be included in at least one implementation manner of the present invention. The phrase "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is separate or selectively mutually exclusive with other embodiments.

[0040] Embodiment 1

[0041] Refer to Figures 1 to 4 , which is the first embodiment of the present invention. This embodiment provides an online carbon emission measurement and evaluation function module for an active distribution network park, which includes S1: constructing a data acquisition module and forming a data acquisition model C in the power grid and the park energy network xyz to collect power grid operation data, park load data, internal distributed energy generation data, etc. (including gas, gas purchase, power consumption, renewable energy generation, power grid power purchase).

[0042] S2: According to the park's electricity load data, construct an electricity balance classification diagram (as Figure 1 shown), refine the electricity sources that meet the electricity load demand at each moment, and based on various types of electricity and their corresponding carbon emission factors (such as coal-fired power generation, gas-fired power generation, wind energy, solar energy, etc.), construct a dynamic carbon emission factor for the park's electricity network (as Figure 2 shown).

[0043] S3: According to the park's gas load data, construct a gas balance classification diagram (as Figure 2 shown), obtain the gas consumption power of gas boilers and gas loads at each moment, and combine with the carbon emission factor corresponding to natural gas to construct a carbon emission measurement model for the park's gas network at each moment.

[0044] S4: According to the dynamic carbon emission factor model of the electricity network constructed in step S2, multiply it by various types of electricity at each moment and integrate over time; add the carbon emission model of the gas network in step S3 to obtain the real-time carbon emissions of the park's energy system (as Figure 4 shown).

[0045] S5: According to the power dynamic carbon emission factor in step S2, compare with the provincial power carbon emission factor issued by the Ministry of Ecology and Environment of the People's Republic of China, set the emission factor classification interval, and construct "high", "medium", and "low" carbon evaluation indicators (as Figure 5 shown). Enterprises can carry out self-regulatory adjustment according to the evaluation indicators to effectively reduce the overall carbon emissions.

[0046] Step S1 specifically refers to: forming a data acquisition model C in the power grid and the park energy network xyz :

[0047]

[0048] In the formula: σ represents the acquisition interval of electrical energy data; u represents the sympathetic deviation; ψ represents the acquisition ratio of electrical energy data; the deployment spacing D of different nodes is calculated by the formula:

[0049]

[0050] In the formula: ω represents the total coverage range of nodes; g represents the distance of the data acquisition unit; c represents the total number of data acquisitions of nodes; π represents the data acquisition correction factor; θ represents the acquisition frequency of energy data;

[0051] Step S2 specifically refers to: the real-time calculation method of the dynamic carbon emission factor C e (τ):

[0052] C e (τ) = [∑CEm g (τ) + ∑CEm j (τ) - ∑CEm l (τ)] / [∑P grid (τ) + ∑P j (τ) - ∑P l (τ)]

[0053] In the formula: CEm k (τ) is the carbon emission generated on the source side when the park j purchases electricity from the power grid at time τ, kgCO2; CEm j (τ) is the carbon emission generated by the non-zero-carbon distributed power source in the park j at time τ, kgCO2; CEm l (τ) is the carbon emission corresponding to the tie-line electricity at time τ, kgCO2; P grid (τ) is the electricity transmitted from the power grid to the park j at time τ, kWh; P j (τ) is the power generation of the non-zero-carbon distributed power source in the park j at time τ, kWh; P l (τ) is the electricity on the tie-line at time τ, kWh; where:

[0054]

[0055] In the formula: C r,c (τ), C r,g (τ), C r,k (τ), C r,s (τ), C r,l (τ) are the carbon emission factors per kWh of the coal-fired unit, gas-fired unit, non-zero-carbon power source k in park j, energy storage, and tie-line at time τ, respectively, kgCO2 / kWh; P c (τ), P g (τ), P j,k (τ), P j,s(τ), P l (τ) are the coal-fired power units on the grid side, gas-fired power units on the grid side, non-zero-carbon power sources k in the park, the discharge of energy storage in the park, and the power of the park connection line at time τ, in kWh; by decomposing the impact of each energy type on carbon emissions, the dynamic carbon emission factor is calculated, and there is a range fluctuation of -0.214 to +0.501 kgCO2 / kWh compared with the provincial fixed carbon emission factor; according to the constructed dynamic carbon emission factor of the power grid, the carbon emission model T of the park power grid is further obtained c :

[0056] T c = ∫P T (τ)·C e (τ)·dτ

[0057] In the formula: C e (τ) is the dynamic carbon emission factor of the park's electricity, in kgCO2 / kWh; P T is the park's electricity load, in kWh;

[0058] Step S3 specifically refers to: using the national standard natural gas emission factor C r,g = 0.40 kgCO2 / kWh to construct the carbon emission model G of the park's gas network c :

[0059] G c = ∫(P GB,g (τ) + P L,g (τ))·C r,g ·dτ

[0060] In the formula: P GB,g (τ) and P L,g (τ) are the gas consumption power of the gas boiler and the gas load power at time τ, in kWh;

[0061] Step S4 specifically refers to: a multi-energy flow model of the park that can integrate electricity and gas network data to implement a dynamic carbon emission measurement model Y c :

[0062] Y c = G c + T c = ∫[(P GB,g (τ) + P L,g (τ))·C r,g + P T (τ)·C e (τ)]·dτ

[0063] Step S5 specifically refers to: the design and application of hierarchical evaluation indicators, using the provincial fixed carbon emission factor EF pTaking 0.5182 kgCO2 / kWh as the benchmark, the carbon emission classification standard for the park is set, and the dynamic emission factor C e (τ)≥0.7182 kgCO2 / kWh is set as the "high" carbon interval, and C e (τ)∈[0.3182, 0.7182) kgCO2 / kWh is set as the "medium" carbon interval, and C e (τ)<0.3182 kgCO2 / kWh is set as the three evaluation criteria for the "low" carbon interval, and is used as the reference basis for production optimization and energy efficiency improvement.

[0064] Importantly, the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. An online carbon emission measurement and evaluation function module for an active distribution network park, characterized by: include, S1: Construct data collection module and build data collection model C in power grid and park energy network xyz , collect power grid operation data, park load data and internal distributed energy generation data; S2: Build a power balance classification diagram based on the power load data of the park, refine the power sources that meet the power load demand at each moment, and build a dynamic carbon emission factor for the park power network based on various types of power and their corresponding carbon emission factors; S3: Construct a gas balance classification diagram based on the gas load data of the park, obtain the gas consumption power of gas boilers and gas loads at each time, and construct a carbon emission calculation model for the gas network at each time in the park based on the carbon emission factor corresponding to natural gas; S4: According to the dynamic carbon emission factor model of the electricity network at each moment constructed in step S2, multiply it by the amount of electricity of each type at each moment and integrate it over time; add the carbon emission model of the gas network in step S3 to obtain the real-time carbon emissions of the park energy system; S5: According to the dynamic carbon emission factor of electricity in step S2, compare it with the provincial electricity carbon emission factor released by the Ministry of Ecology and Environment of the People's Republic of China, set the emission factor classification range, and construct "high", "medium" and "low" carbon evaluation indicators. Enterprises can carry out self-discipline adjustments based on the evaluation indicators to effectively reduce overall carbon emissions.

2. The online carbon emission measurement and evaluation function module of the active distribution network park according to claim 1 is characterized by: The internal distributed energy generation data includes gas, gas purchases, electricity consumption, renewable energy generation, and grid electricity purchases; The carbon emission factors include coal-fired power generation, gas-fired power generation, wind power, and solar power.

3. The online carbon emission measurement and evaluation function module of the active distribution network park according to claim 2 is characterized by: The step S1 specifically refers to: establishing a data collection model C in the power grid and the park energy network xyz : Where: σ represents the collection interval of electric energy data; u represents the interaction deviation; ψ represents the electric energy data collection ratio; the deployment spacing D of different nodes is: Where: ω represents the total coverage of the node; g represents the data collection unit distance; c represents the total number of data collection times of the node; π represents the data collection correction coefficient; θ represents the energy data collection frequency.

4. The online carbon emission measurement and evaluation function module of the active distribution network park according to claim 3 is characterized by: The step S2 specifically refers to: dynamic carbon emission factor C e Real-time calculation method of (τ): C e (τ)=[ΣCEm g (t)+ΣCEm j (t)-ΣCEm l (t)] / [ΣP grid (τ)+∑P j (τ)-∑P l (t)] Where: CEm k (τ) is the carbon emission generated by the source side when the park j purchases electricity from the grid at time τ, kgCO2; CEm j (τ) is the carbon emission generated by non-zero carbon distributed power sources in park j at time τ, kgCO2; CEm l (τ) is the carbon emission corresponding to the interconnection line power at time τ, kgCO2; P grid (τ) is the power delivered by the power grid to park j at time τ, kWh; P j (τ) is the power generation of non-zero carbon distributed generation in park j at time τ, kWh; P l (τ) is the power on the interconnection line at time τ, kWh; where: Where: C r,c (τ), C r,g (τ), C r,k (τ), C r,s (τ), C r,l (τ) are the carbon emission factors of coal-fired units, gas-fired units, non-zero carbon power source k in park j, energy storage and interconnection lines at time τ, kgCO2 / kWh; P c (τ), P g (τ), P j,k (τ), P j,s (τ), P l (τ) are the coal-fired units on the grid side, the gas-fired units on the grid side, the non-zero carbon power source k in the park, the energy storage discharge in the park, and the power of the park interconnection line at time τ, kWh; by decomposing the impact of each energy type on carbon emissions, the dynamic carbon emission factor is calculated, which will fluctuate in the range of -0.214 to +0.501 kgCO2 / kWh compared with the provincial fixed carbon emission factor; according to the constructed power network dynamic carbon emission factor, the carbon emission model T of the park power network is further obtained c : T c =∫P T (t)·C e (t)·dt In the formula: In the formula: C e (τ) is the dynamic carbon emission factor of the park’s electricity, kgCO2 / kWh; P T is the park electricity load, kWh.

5. The online carbon emission measurement and evaluation function module of the active distribution network park according to claim 4 is characterized by: The step S3 specifically refers to: using the natural gas emission factor C specified by the state r,g = 0.40kgCO2 / kWh to build the carbon emission model of the park gas network G c : G c =∫(P GB,g (t)+P L,g (t))·C r,g ·dτ Where: P GB,g (τ) and P L,g (τ) are respectively the gas consumption power and gas load power of the gas boiler at time τ, in kWh.

6. The online carbon emission measurement and evaluation function module of the active power distribution network park according to claim 5, characterized in that: The step S4 specifically refers to: a park multi-energy flow model capable of integrating electricity and gas network data to realize a dynamic carbon emission calculation model Y c : Y c =G c +T c =∫[(P GB,g (t)+P L,g (t))·C r,g +P T (t)·C e (τ)]·dτ.

7. The online carbon emission measurement and evaluation functional module of the active power distribution network park according to claim 6, characterized in that: The step S5 specifically refers to: designing and applying the hierarchical evaluation index, converting the provincial fixed carbon emission factor EF p = 0.5182kgCO2 / kWh as the benchmark, set the park carbon emission classification standard, and set the dynamic emission factor C e (τ)≥0.7182kgCO2 / kWh is set as the "high" carbon range, C e (τ)∈[0.3182,0.7182)kgCO2 / kWh is set as the "medium" carbon range, C e (τ)<0.3182kgCO2 / kWh is set as the three-category evaluation standard for the "low" carbon range and serves as a reference for production optimization and energy efficiency improvement.

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