A method and device for quantifying carbon emissions of electrical equipment based on electric carbon information entropy

Abstract

The application discloses an electrical equipment carbon emission quantification method and device based on electrical carbon information entropy, comprising: extracting the power signal of electrical equipment; the power signal is decomposed into base frequency, harmonic and direct current component; based on the regional electrical carbon emission factor calculation method and the carbon emission flow calculation method, the relationship between the power signal and carbon emission is associated to obtain the electrical carbon conversion coefficient; based on the information entropy theory and the electrical carbon conversion coefficient, the electrical carbon information entropy is calculated, and the electrical carbon information entropy is taken as a quantitative index for measuring the carbon emission of electrical equipment. The problem that the prior art cannot quantitatively evaluate the carbon emission of new electrical equipment is solved.

Description

Technical Field

[0001] This invention relates to the field of carbon metering technology, specifically to a method and apparatus for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy. Background Technology

[0002] Actual carbon emissions in the power grid originate from the combustion of fossil fuels at power plants. However, from the perspective of carbon emission flows, carbon emissions can be viewed as flowing through the nodes of the power system along with the electricity flow for easier research and management. In recent years, with the rapid development of distributed resources such as distributed photovoltaics and electric vehicle charging stations in the distribution system, and the widespread use of new electrical equipment, the power grid has been injected with a large amount of harmonic and DC energy, most of which is converted into heat loss. These new characteristics bring about the impacts of energy consumption, entropy increase, and carbon emissions. However, current research on the energy efficiency of electrical equipment is not yet complete, making it difficult to quantitatively evaluate the carbon emissions of new electrical equipment. Summary of the Invention

[0003] To address the above problems, this invention provides a method for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy, comprising:

[0004] Extracting power signals from electrical equipment;

[0005] The power signal is deconstructed into fundamental frequency, harmonics, and DC components;

[0006] Based on the regional electricity carbon emission factor calculation method and the carbon emission flow calculation method, the electricity carbon conversion coefficient is obtained by correlating the relationship between the power signal and carbon emissions;

[0007] Based on the information entropy theory and the electro-carbon conversion coefficient, the electro-carbon information entropy is calculated and used as a quantitative indicator to measure the carbon emissions of electrical equipment.

[0008] Furthermore, extracting the power signals from the electrical equipment includes:

[0009] The power signals of electrical equipment are extracted by voltage and current transformers, and the power signals include voltage signals and current signals.

[0010] Furthermore, the power signal is deconstructed into fundamental frequency, harmonics, and DC components, including:

[0011] The voltage and current signals are decomposed into fundamental frequency, harmonics, and DC components using a spectrum analysis method based on fast Fourier transform.

[0012] The DC component is denoted as the 0th harmonic, and the fundamental frequency is denoted as the 1st harmonic;

[0013] The voltage signal U is decomposed into voltage components (u0, u1, … u) nThe superposition of harmonics, where the subscript indicates the harmonic order and n is the maximum harmonic order;

[0014] Decompose the current signal 1 into current components (i0, i1, ..., i...). n The superposition of harmonics, where the subscript indicates the harmonic order and n is the maximum harmonic order.

[0015] Further, the regional electricity carbon emission factor calculation method includes:

[0016] Identify information about specific power plants within a given area, categorized by primary fuel type;

[0017] Calculate the average emission rate and standard deviation for each fuel type and pollutant from all plants in the region;

[0018] Average emission rate μ ER The calculation is weighted based on the power generation of each factory:

[0019]

[0020] Among them ER i It is the emission rate of a specific pollutant from factory i, NG i It is the net power generation of factory i;

[0021] The relationship between unit power generation and the amount of fossil fuel consumed and carbon emissions is established. The ratio of unit carbon emissions to active power flow for different types of power generation is defined as the emission factor EF, where the emission factor for clean energy power generation is 0.

[0022] Further methods for calculating carbon emission flows include:

[0023] In a power system, the node carbon potential of node n is defined as:

[0024]

[0025] Where i is the branch number, N is the set of all branches connected to this node that have a flow into this node, R is the carbon emission flow per unit time of the above branch, and P is the active power flow of the above branch.

[0026] Based on the power system topology and power flow calculation model, the node carbon potential of the entire network can be derived according to the carbon emission flow calculation method.

[0027] If the node number of the electrical equipment is k, its node carbon potential e can be determined. k .

[0028] Furthermore, by correlating the relationship between the power signal and carbon emissions, the electrocarbon conversion coefficient is obtained, including:

[0029] The fundamental frequency of the power signal is defined as positive, and the remaining components that cause losses are defined as negative. The electro-carbon conversion coefficient of the electrical equipment is then defined as follows:

[0030] C=(c(0) c(1) … c(n))=(-e k e k … -e k ).

[0031] Furthermore, based on information entropy theory and the electro-carbon conversion coefficient, the electro-carbon information entropy is calculated, and this electro-carbon information entropy is used as a quantitative indicator to measure the carbon emissions of electrical equipment, including:

[0032] Information entropy is defined as:

[0033]

[0034] Where X is a discrete random variable, and the probability of each possible value x is p(x). When the base b = 2, the unit of information entropy is bits.

[0035] For an electrical signal P, x represents components of different harmonic orders. Combining the electrocarbon conversion coefficient C, the electrocarbon information entropy E(P) of the electrical signal P is defined as:

[0036]

[0037] The carbon information entropy of electricity is used as a quantitative indicator to measure the carbon emissions of electrical equipment.

[0038] Furthermore, it also includes:

[0039] The higher the entropy of electrical carbon information, the higher the quality of electrical energy and the lower the loss and carbon emissions of electrical equipment.

[0040] This invention also provides a device for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy, comprising:

[0041] A power signal extraction unit is used to extract power signals from electrical equipment.

[0042] A power signal deconstruction unit is used to deconstruct the power signal into fundamental frequency, harmonics, and DC components;

[0043] The conversion coefficient acquisition unit, based on the regional electricity carbon emission factor calculation method and the carbon emission flow calculation method, obtains the electricity carbon conversion coefficient by associating the relationship between the power signal and carbon emissions;

[0044] The electrical carbon information entropy calculation unit calculates the electrical carbon information entropy based on information entropy theory and electrical carbon conversion coefficient, and uses the electrical carbon information entropy as a quantitative indicator to measure the carbon emissions of electrical equipment.

[0045] The present invention provides a method and apparatus for quantifying carbon emissions of electrical equipment based on electrocarbon information entropy, which solves the problem that existing technologies cannot quantify and evaluate the carbon emissions of new electrical equipment. Attached Figure Description

[0046] Figure 1 This is a flowchart of the method for quantifying carbon emissions of electrical equipment based on electrocarbon information entropy provided in an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of an electrical equipment carbon emission quantification device based on electrical carbon information entropy, which is involved in an embodiment of the present invention. Detailed Implementation

[0048] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0049] Figure 1 This invention provides a flowchart of a method for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy. Taking a grid-connected inverter of a distributed photovoltaic system as an example, the method for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy includes the following steps:

[0050] Step S101: Extract the power signal from the electrical equipment.

[0051] The power signals of electrical equipment are extracted by voltage and current transformers, and the power signals include voltage signals and current signals.

[0052] Step S102: Deconstruct the power signal into fundamental frequency, harmonics and DC components.

[0053] Using a spectrum analysis method based on Fast Fourier Transform (FFT), the aforementioned voltage and current signals are decomposed into fundamental frequency, harmonics, and DC components, respectively. The DC component is denoted as the 0th harmonic, and the fundamental frequency as the 1st harmonic. The voltage signal U can be decomposed into voltage components (u0 u1 … u…). n The summation of harmonics is represented by the superposition of (i0, i1, ..., ii) components, where the subscript indicates the harmonic order, and n is the maximum harmonic order. Similarly, the current signal I can be decomposed into current components (i0, i1, ..., ii) n The output power P of the device can be calculated from the voltage and current.

[0054] Step S103: Based on the regional electricity carbon emission factor calculation method and the carbon emission flow calculation method, the electricity carbon conversion coefficient is obtained by associating the relationship between the electricity signal and carbon emissions.

[0055] First, a regional power generation carbon emission factor calculation method is employed. This method involves first identifying information on specific power plants within a region, categorized by primary fuel type. Then, the average emission rate and standard deviation for each fuel type and pollutant from all plants in the region are calculated. The average emission rate μ is... ER The calculation is weighted based on the power generation of each factory:

[0056]

[0057] Among them ER i It is the emission rate of a specific pollutant from factory i, NG i This represents the net power generation of plant i. From this, we can establish the relationship between unit power generation and its consumption of fossil fuels and carbon emissions. We define the ratio of unit carbon emissions to active power flow for different types of power generation as the emission factor EF, where the emission factor for clean energy power generation is 0.

[0058] The carbon conversion factor for electricity is calculated using carbon emission flow calculation methods. For a given node n in a power system, the nodal carbon potential is defined as:

[0059]

[0060] Where i is the branch number, N is the set of all branches connected to this node that have power flows into this node, R is the carbon emission flow per unit time of the above branch, and P is the active power flow of the above branch; based on the power system topology and power flow calculation model, the node carbon potential of the entire network can be derived according to the carbon emission flow calculation method; if the node number of the electrical equipment is k, its node carbon potential e can be determined. k .

[0061] The electro-carbon conversion factor is defined as follows: to describe the power quality and carbon emissions of electrical equipment, the fundamental frequency of the power signal is positive, and the other components that cause losses are negative.

[0062] C=(c(0) c(1) … c(n))=(-e k e k … -e k ).

[0063] Step S104: Based on the information entropy theory and the electro-carbon conversion coefficient, calculate the electro-carbon information entropy, and use the electro-carbon information entropy as a quantitative indicator to measure the carbon emissions of electrical equipment.

[0064] Information entropy is defined as:

[0065]

[0066] Where X is a discrete random variable, and the probability of each possible value x is p(x). When the base b = 2, the unit of information entropy is bit.

[0067] For an electrical signal P, x represents components of different harmonic orders. Combining the electrocarbon conversion coefficient C, the electrocarbon information entropy E(P) of the electrical signal P is defined as:

[0068]

[0069] The electrical carbon information entropy is used as a quantitative indicator to measure the carbon emissions of electrical equipment. The higher the electrical carbon information entropy, the higher the power quality and the lower the losses and carbon emissions of electrical equipment.

[0070] The carbon emission quantification method for electrical equipment based on information entropy theory can be applied to the carbon emission quantification of power conversion equipment such as inverters, rectifiers, solid-state transformers, and energy routers. It can be used to achieve scientific measurement and calculation of carbon emissions from electrical equipment and power systems.

[0071] Among these methods, compared to the national fuel assessment emission rate approach, the regional power generation carbon emission factor calculation method can more accurately assess the carbon emissions generated at the power generation end in a specific region as load changes. The carbon emission flow calculation method based on power flow models can equate the carbon emissions generated by power plants in the power system to load-side electrical equipment through carbon emission flows, establishing a relationship between power quality and carbon emissions from electrical equipment. The electrical carbon conversion coefficient can establish a conversion relationship between power signals and carbon emissions, distinguishing between usable components and lossy components that need filtering. Electrical carbon information entropy, as a quantitative indicator of carbon emissions from electrical equipment, reflects power quality and carbon emissions; a higher electrical carbon information entropy indicates higher power quality and lower losses and carbon emissions from electrical equipment. This addresses the problem that existing technologies cannot quantitatively evaluate the carbon emissions of new electrical equipment.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A method for quantifying carbon emissions from electrical equipment based on electrical carbon information entropy, characterized in that, include: Extracting power signals from electrical equipment; The power signal is deconstructed into fundamental frequency, harmonics, and DC components; Based on the regional electricity carbon emission factor calculation method and the carbon emission flow calculation method, the electricity carbon conversion coefficient is obtained by correlating the relationship between the power signal and carbon emissions; Based on the information entropy theory and the electro-carbon conversion coefficient, the electro-carbon information entropy is calculated and used as a quantitative indicator to measure the carbon emissions of electrical equipment. Extracting power signals from electrical equipment, including: The power signals of electrical equipment are extracted by voltage and current transformers, and the power signals include voltage signals and current signals. The power signal is deconstructed into fundamental frequency, harmonics, and DC components, including: The voltage and current signals are decomposed into fundamental frequency, harmonics, and DC components using a spectrum analysis method based on fast Fourier transform. The DC component is denoted as the 0th harmonic, and the fundamental frequency is denoted as the 1st harmonic; The voltage signal U is decomposed into voltage components. The superposition of harmonics, where the subscripts indicate the harmonic order, and n is the maximum harmonic order; Decompose the current signal I into current components. The superposition of harmonics, where the subscripts indicate the harmonic order, and n is the maximum harmonic order; By correlating the relationship between the power signal and carbon emissions, the electricity-to-carbon conversion coefficient is obtained, including: The fundamental frequency of the power signal is defined as positive, and the remaining components that cause losses are defined as negative. The electro-carbon conversion coefficient of the electrical equipment is then defined as follows: ； Based on information entropy theory and the electro-carbon conversion coefficient, the electro-carbon information entropy is calculated and used as a quantitative indicator to measure the carbon emissions of electrical equipment, including: Information entropy is defined as: Where X is a discrete random variable, and each of its possible values... x The probability is p ( x (Take the base) b When the value is 2, the unit of information entropy is bits. For power signals P , x For components of different harmonic orders, combined with the carbon-to-electric conversion coefficient Define power signals P Entropy of electric carbon information for: The carbon information entropy of electricity is used as a quantitative indicator to measure the carbon emissions of electrical equipment.

2. The method according to claim 1, characterized in that, Methods for calculating regional electricity carbon emission factors include: Identify information about specific power plants within a given area, categorized by primary fuel type; Calculate the average emission rate and standard deviation for each fuel type and pollutant from all plants in the region; Average emission rate The calculation is weighted based on the power generation of each factory: in It is a factory i Emission rate of specific pollutants, It is a factory i Net electricity generation; Establish the relationship between unit power generation and its consumption of fossil fuels and carbon emissions, and define the ratio of unit carbon emissions to active power flow for different types of power generation as emission factors. EF The emission factor for clean energy power generation is 0.

3. The method according to claim 1, characterized in that, Methods for calculating carbon emission flows include: Nodes in the power system n The node carbon potential is defined as: in, i It is the branch road number. N It is the set of all branches connected to this node that have a current flowing into this node. R The carbon emission flow rate per unit time for the aforementioned branch roads. P The aforementioned branch lines are the source of the tidal current; Based on the power system topology and power flow calculation model, the node carbon potential of the entire network can be derived according to the carbon emission flow calculation method. If the node number where the electrical equipment is located is k Its node carbon potential can be determined. .

4. The method according to claim 1, characterized in that, Also includes: The higher the entropy of electrical carbon information, the higher the quality of electrical energy and the lower the loss and carbon emissions of electrical equipment.

5. A device for quantifying carbon emissions of electrical equipment based on the method of any one of claims 1-4, characterized in that, include: A power signal extraction unit is used to extract power signals from electrical equipment. A power signal deconstruction unit is used to deconstruct the power signal into fundamental frequency, harmonics, and DC components; The conversion coefficient acquisition unit, based on the regional electricity carbon emission factor calculation method and the carbon emission flow calculation method, obtains the electricity carbon conversion coefficient by associating the relationship between the power signal and carbon emissions; The electrical carbon information entropy calculation unit calculates the electrical carbon information entropy based on information entropy theory and electrical carbon conversion coefficient, and uses the electrical carbon information entropy as a quantitative indicator to measure the carbon emissions of electrical equipment.

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