Method and device for determining carbon emission of transformer and computer equipment

Abstract

The application relates to a transformer carbon emission determination method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining the winding temperature rise of the transformer according to the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment where the transformer is located; determining the real-time load loss corresponding to the winding temperature rise based on the corresponding relationship between the winding temperature rise and the steady-state load loss and the winding temperature rise change rate represented by the winding temperature rise; determining the total power loss of the transformer according to the real-time load loss and the no-load loss of the transformer; and determining the carbon emission amount of the transformer by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs. The method can reduce the accounting scene limitation and accounting cost of the transformer carbon emission and improve the energy saving of the transformer operation.

Description

Technical Field

[0001] This application relates to the field of transformer carbon emission technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for determining the carbon emissions of a transformer. Background Technology

[0002] Carbon emissions during transformer operation refer to the total amount of greenhouse gas emissions, such as carbon dioxide, generated by the power generation environment corresponding to the continuous consumption of electrical energy due to no-load and load losses within the transformer after it is put into operation on the power grid. Calculating carbon emissions during transformer operation is an important basis for assessing equipment energy efficiency, developing energy-saving renovation plans, and conducting power carbon accounting.

[0003] Currently, carbon emission accounting typically requires collecting various electrical parameters from the high-voltage or low-voltage side of the transformer, such as operating current, voltage, and power factor, and then adjusting for losses based on oil temperature. This method is often ineffective for older or critical transformers because they lack the necessary conditions for installing current transformers. Furthermore, it requires deploying numerous electrical sensors, resulting in high accounting costs and safety risks associated with high-voltage side data acquisition. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the carbon emissions of transformers, which can reduce the limitations and costs of calculating carbon emissions in transformer carbon emission accounting scenarios and improve the energy efficiency of transformer operation, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for determining the carbon emissions of a transformer. The method includes:

[0006] The winding temperature rise of the transformer is determined based on the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment in which the transformer is located.

[0007] Based on the correspondence between the winding temperature rise and the steady-state load loss, and the winding temperature rise rate characterized by the winding temperature rise, the real-time load loss corresponding to the winding temperature rise is determined.

[0008] The total power loss of the transformer is determined based on the real-time load loss and the no-load loss of the transformer.

[0009] The carbon emissions of the transformer are determined by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs.

[0010] In one embodiment, determining the real-time load loss corresponding to the winding temperature rise based on the preset correspondence between the winding temperature rise and the steady-state load loss, and the winding load change trend characterized by the winding temperature rise, includes:

[0011] Invoke the pre-configured steady-state loss model and additional loss model for the transformer;

[0012] Based on the correspondence between winding temperature rise and steady-state load loss described by the steady-state loss model, a target steady-state load loss that matches the winding temperature rise is determined.

[0013] Using the aforementioned additional loss model, the additional losses that generate the winding temperature rise are determined based on the winding temperature rise rate, which is characterized by the winding temperature rise.

[0014] The sum of the target steady-state load loss and the additional loss is determined as the real-time load loss corresponding to the winding temperature rise.

[0015] In one embodiment, determining the target steady-state load loss matching the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss described by the steady-state loss model includes:

[0016] Obtain the power exponent parameter determined by the steady-state temperature rise test of the transformer, the power exponent parameter being used to reflect the heat dissipation nonlinearity of the transformer;

[0017] The rated load loss, rated winding steady-state temperature rise, power exponent parameters, and winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0018] In one embodiment, determining the additional losses that generate the winding temperature rise based on the winding temperature rise rate of change, as characterized by the winding temperature rise using the additional loss model, includes:

[0019] Obtain the temperature rise rate data obtained from the transient temperature rise test of the transformer;

[0020] The temperature rise rate data is fitted to obtain the correction parameters of the transformer; the correction parameters are used to reflect the equivalent heat capacity of the transformer.

[0021] The additional loss model is used to determine the winding temperature rise rate of the transformer based on the winding temperature rise. The product of the winding temperature rise rate and the correction parameter is determined as the additional loss that causes the winding temperature rise.

[0022] In one embodiment, the step of inputting the transformer's rated load loss, rated winding steady-state temperature rise, power exponent parameters, and the winding temperature rise into the steady-state loss model to obtain a target steady-state load loss matching the winding temperature rise includes:

[0023] Obtain the operating status information of the transformer;

[0024] If, based on the operating status information, it is determined that the transformer does not meet the forced zero-setting judgment condition, the rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0025] In one embodiment, the method further includes:

[0026] If the transformer meets the forced zero-setting judgment condition based on the operating status information, the forced zero-setting time threshold of the transformer is determined based on the thermal time constant of the transformer.

[0027] If the temperature rise of the transformer winding is less than the no-load judgment temperature and the duration exceeds the forced zero-time threshold, then the rated load loss of the transformer is set to zero, and the updated rated load loss is obtained.

[0028] The rated winding steady-state temperature rise, the updated rated load loss, the power exponent parameter, and the winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0029] Secondly, this application also provides a device for determining the carbon emissions of a transformer. The device includes:

[0030] The winding temperature rise module is used to determine the winding temperature rise of the transformer based on the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment in which the transformer is located.

[0031] The real-time load loss determination module is used to determine the real-time load loss corresponding to the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss, as well as the winding temperature rise change rate characterized by the winding temperature rise.

[0032] The total power loss determination module is used to determine the total power loss of the transformer based on the real-time load loss and the no-load loss of the transformer.

[0033] The carbon emission determination module is used to determine the carbon emission of the transformer by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs.

[0034] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described method.

[0035] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0036] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the above-described method.

[0037] The aforementioned method, apparatus, computer equipment, storage medium, and computer program products for determining the carbon emissions of transformers determine the winding temperature rise based on real-time winding temperature and ambient temperature collected during transformer operation. Subsequently, based on the correspondence between the winding temperature rise and steady-state load losses, and the winding temperature rise rate, the real-time load loss corresponding to the winding temperature rise is determined. This compensates for thermal inertia delays during sudden load changes, reducing the possibility of overestimation or underestimation of losses, ensuring that the determined real-time load loss accurately reflects the actual operating conditions of the transformer and improving the accuracy of carbon emission determination. Then, based on the real-time load loss and the transformer's no-load loss, the total power loss of the transformer is determined. The product of the total power loss and the carbon emission factor of the power grid to which the transformer belongs is determined as the transformer's carbon emission. The entire calculation process directly derives the load loss from winding temperature rise data, without relying on the measurement of transformer operating current. This effectively reduces the limitations and costs of transformer carbon emission calculation scenarios. Accurate carbon emission determination provides direct carbon data support for subsequent energy-saving operation of the transformer, effectively reducing the actual carbon emissions of transformer operation and improving the energy efficiency of transformer operation. Attached Figure Description

[0038] Figure 1 This is a diagram illustrating the application environment of a method for determining the carbon emissions of a transformer in one embodiment.

[0039] Figure 2 This is a flowchart illustrating a method for determining the carbon emissions of a transformer in one embodiment;

[0040] Figure 3 This is a schematic diagram of a process for determining the real-time load loss corresponding to the winding temperature rise based on a preset correspondence between the winding temperature rise and the steady-state load loss, and the trend of winding load change characterized by the winding temperature rise, in one embodiment.

[0041] Figure 4This is a schematic diagram illustrating the process of determining the additional losses that cause the winding temperature rise based on the winding temperature rise rate, which is characterized by the winding temperature rise, in one embodiment using an additional loss model.

[0042] Figure 5 This is a flowchart illustrating a method for determining the carbon emissions of a transformer in another embodiment;

[0043] Figure 6 This is a flowchart illustrating a method for determining the carbon emissions of a transformer in another embodiment;

[0044] Figure 7 This is a schematic diagram of the transformer structure in one embodiment;

[0045] Figure 8 This is a schematic diagram of the mapping relationship between winding temperature rise and load loss under different power exponents α in one embodiment;

[0046] Figure 9 This is a schematic diagram of carbon emission time-series curves in one embodiment;

[0047] Figure 10 This is a structural block diagram of a transformer carbon emission determination device in one embodiment;

[0048] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] The method for determining the carbon emissions of transformers provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the carbon emission accounting system 102 communicates with the server 104 via a network. A data storage system can store the data that the carbon emission accounting system 102 needs to process. The data storage system can be integrated onto the server 104, or it can be placed in the cloud or on another network server. The carbon emission accounting system 102 can determine the winding temperature rise of the transformer based on the real-time winding temperature during operation and the real-time ambient temperature of the environment where the transformer is located. Based on the correspondence between the winding temperature rise and steady-state load loss, and the winding temperature rise rate, it determines the real-time load loss corresponding to the winding temperature rise. Subsequently, based on the real-time load loss and the transformer's no-load loss, it determines the total power loss of the transformer. The product of the total power loss and the carbon emission factor of the power grid to which the transformer belongs is determined as the carbon emission amount of the transformer.

[0051] The carbon emission accounting system 102 can be integrated into a terminal or a server 104. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can be maintenance equipment used by power grid maintenance personnel. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0052] In one embodiment, such as Figure 2 As shown, a method for determining the carbon emissions of a transformer is provided, which can be applied to... Figure 1 Taking the carbon emission accounting system 102 in the example, the following steps are included:

[0053] S202, the winding temperature rise of the transformer is determined based on the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment in which the transformer is located.

[0054] Among them, transformers are static electromagnetic devices in power grid equipment that use the principle of electromagnetic induction to realize changes in voltage, current and impedance. A transformer can be composed of an iron core and two or more windings, and can convert electrical energy of one voltage level into electrical energy of another voltage level at the same frequency through alternating magnetic flux coupling.

[0055] The windings of a transformer are conductive coils made of copper or aluminum wires that carry current and generate a magnetic field. Real-time winding temperature is temperature data used to reflect the current thermal state of the transformer windings. It can be the instantaneous temperature value of the winding conductors measured during transformer operation via optical fiber or thermal simulation device.

[0056] Real-time ambient temperature is the temperature data of the environment in which the transformer is located. It can be the instantaneous temperature value of the air or cooling medium around the transformer installation location.

[0057] Winding temperature rise is the gradient of winding temperature relative to ambient temperature, and it can characterize the degree of heating in the winding. In essence, winding temperature rise can be expressed as the difference between the real-time winding temperature and the real-time ambient temperature.

[0058] For example, the carbon emission accounting system can obtain the real-time winding temperature Tw and ambient temperature Ta collected during transformer operation, and calculate the winding temperature rise ΔT = Tw - Ta based on the real-time winding temperature Tw and ambient temperature Ta.

[0059] In one embodiment, a temperature sensor can be installed inside or on the surface of the transformer winding to collect real-time temperature data of the transformer winding and the ambient temperature. The carbon emission accounting system can communicate with the temperature sensor to obtain the real-time winding temperature and the real-time ambient temperature.

[0060] In one embodiment, the winding temperature sensor can be a fiber Bragg grating sensor or a platinum resistance temperature sensor, with a frequency of not less than 1 time / minute.

[0061] S204. Based on the correspondence between winding temperature rise and steady-state load loss, and the winding temperature rise rate characterized by the winding temperature rise, the real-time load loss corresponding to the winding temperature rise is determined.

[0062] Steady-state load loss refers to the active power consumption of a transformer under thermal equilibrium conditions caused by the load current. It can be understood as the active power loss caused by the winding resistance when the winding temperature, ambient temperature, and load current remain constant for a sufficiently long time, and the winding temperature rise no longer changes. Under stable temperature conditions, steady-state load loss is directly equal to actual load loss.

[0063] The correspondence between winding temperature rise and steady-state load loss refers to a deterministic functional mapping between the two. During transformer operation, almost all of the load loss (copper loss) Pk in the winding is converted into heat, causing the winding temperature to be higher than the surrounding cooling medium, such as oil or air. Under steady-state conditions, the heat generated equals the heat dissipated, thus establishing a one-to-one mapping between winding temperature rise and load loss.

[0064] In one embodiment, the correspondence between winding temperature rise and steady-state load loss can be represented as a mapping table or mapping curve. The carbon emission accounting system can determine the steady-state load loss that matches the current winding temperature rise by looking up the table or mapping the curve.

[0065] The winding temperature rise rate refers to the rate at which the temperature rise changes over time. It is the derivative of the dynamic thermal process and can be understood as the amount of change in winding temperature rise per unit time. A positive winding temperature rise rate indicates an increase in temperature, meaning the transformer load is increasing and the actual losses are greater than the steady-state load losses. A negative winding temperature rise rate indicates a decrease in temperature, meaning the transformer load is decreasing and the actual losses are less than the steady-state load losses.

[0066] For example, in actual transformer operation, the load changes constantly, and the winding temperature does not instantly reach a new steady state. Thermal inertia causes the temperature rise to lag behind the loss change. Therefore, when determining the real-time load loss of a transformer, the carbon emission accounting system needs to consider not only the steady-state load loss corresponding to the winding temperature rise under steady-state conditions, but also the lag in temperature rise caused by thermal inertia. The carbon emission accounting system can determine the real-time load loss corresponding to the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss, as well as the winding temperature rise rate characterized by the winding temperature rise.

[0067] In one embodiment, the carbon emission accounting system can first determine the steady-state load loss that matches the winding temperature rise, then determine the additional loss corresponding to the rate of change of winding temperature rise, and finally determine the sum of the steady-state load loss and the additional loss as the real-time load loss corresponding to the winding temperature rise.

[0068] S206. Determine the total power loss of the transformer based on the real-time load loss and the no-load loss of the transformer.

[0069] No-load loss refers to the fixed active power loss generated by the transformer core in an alternating magnetic field. It can be understood as the total active power loss consisting of hysteresis loss and eddy current loss in the core when the transformer windings are open and the rated voltage is applied to one side. No-load loss is basically unaffected by the load current and can be considered a constant.

[0070] Total power loss refers to the sum of all active power consumed during transformer operation. It represents the total active power consumed by the transformer at the current moment and can reflect the energy absorbed by the transformer from the power grid but not transferred to the load.

[0071] For example, a carbon emission accounting system can determine the total power loss of a transformer based on real-time load loss and the transformer's no-load loss.

[0072] In one embodiment, the total power loss E = ∫[P0 + P k ] dt, where P0 is the no-load loss, P k This represents real-time load loss.

[0073] In one embodiment, the transformer's no-load loss can be periodically calibrated. For example, once a year during a planned power outage for transformer maintenance, the actual no-load loss P0 is measured, and if the deviation from the nameplate value exceeds ±5%, P0 is updated with the measured value.

[0074] S208 defines the carbon emissions of a transformer as the product of its total power loss and the carbon emission factor of the power grid to which it belongs.

[0075] The carbon emission factor is the intensity of carbon dioxide emissions per unit of electricity consumption. The carbon emission factor can be different for each power grid, and it can be determined by the power supply structure of the power grid.

[0076] In one embodiment, the grid carbon emission factor EF can be a provincial grid annual average factor or a real-time dynamic factor.

[0077] For example, a carbon emission accounting system can calculate the product of total power loss and the carbon emission factor of the power grid to which the transformer belongs, and determine it as the carbon emission of the transformer.

[0078] In one embodiment, carbon emissions Ctotal = E×EF, where EF is the power grid carbon emission factor.

[0079] In one embodiment, after obtaining real-time carbon emission data of the transformer, the carbon emission accounting system can upload the real-time carbon emission data to the cloud, generate a carbon emission time series curve, and issue an early warning when the carbon emission rate exceeds a threshold.

[0080] In the aforementioned method for determining the carbon emissions of transformers, the winding temperature rise is determined based on real-time winding temperatures and ambient temperatures collected during transformer operation. Then, based on the correspondence between the winding temperature rise and steady-state load losses, and the rate of change of winding temperature rise as a representation of the temperature rise, the real-time load loss corresponding to the winding temperature rise is determined. This compensates for the thermal inertia delay during sudden load changes, reducing the possibility of overestimation or underestimation of losses, ensuring that the determined real-time load loss accurately reflects the actual operating conditions of the transformer and improving the accuracy of carbon emission determination. Subsequently, based on the real-time load loss and the transformer's no-load loss, the total power loss of the transformer is determined. The product of the total power loss and the carbon emission factor of the power grid to which the transformer belongs is determined as the transformer's carbon emissions. The entire calculation process directly derives load losses from winding temperature rise data, without relying on the measurement of transformer operating current. This effectively reduces the limitations and costs of transformer carbon emission calculation scenarios. Accurate carbon emission determination provides direct carbon data support for subsequent energy-saving operation of the transformer, effectively reducing the actual carbon emissions of transformer operation and improving the energy efficiency of transformer operation.

[0081] In one embodiment, such as Figure 3 As shown, S204, based on the preset correspondence between winding temperature rise and steady-state load loss, and the trend of winding load change characterized by winding temperature rise, determines the real-time load loss corresponding to the winding temperature rise, including:

[0082] S302 invokes the pre-configured steady-state loss model and additional loss model for the transformer.

[0083] The steady-state loss model is a mathematical expression used to describe the deterministic relationship between winding temperature rise and load loss under thermal equilibrium conditions. Specifically, it describes the equivalent loss corresponding to the current temperature rise. The steady-state loss model can be a mapping function; by inputting the winding temperature rise value, the load loss at which thermal equilibrium is reached under that temperature rise can be obtained.

[0084] The additional loss model is a mathematical relationship used to describe the additional losses caused by the rate of change of temperature rise during dynamic processes. Specifically, it describes the additional losses caused by changing the winding temperature. The additional loss model can also be a mapping function; the additional losses are obtained by taking the winding temperature rise value as input. The additional loss model can consider dynamic factors such as winding heat capacity and heat dissipation time constant to compensate for the hysteresis error of the steady-state loss model when the load changes rapidly.

[0085] For example, the carbon emission accounting system is pre-configured with a steady-state loss model and an additional loss model for transformers. When carbon emission accounting is required, the carbon emission accounting system can directly call the pre-configured steady-state loss model and additional loss model for transformers.

[0086] S304, based on the correspondence between winding temperature rise and steady-state load loss described by the steady-state loss model, determines the target steady-state load loss that matches the winding temperature rise.

[0087] The target steady-state load loss is the loss value corresponding to the current winding temperature rise under the steady-state loss model. It can be expressed as the load loss should be if the current winding temperature rise is formed in a steady state.

[0088] For example, the carbon emission accounting system can input the winding temperature rise into the steady-state loss model, and determine the target steady-state load loss that matches the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss described by the steady-state loss model.

[0089] S306 uses an additional loss model to determine the additional losses that cause winding temperature rise based on the rate of change of winding temperature rise as characterized by winding temperature rise.

[0090] The additional loss is a dynamic correction parameter caused by thermal inertia, exceeding the steady-state value. It can be determined using an additional loss model based on the winding temperature rise rate. When the winding temperature rise rate is positive, the additional loss is usually positive. When the winding temperature rise rate is negative, the additional loss is usually negative.

[0091] For example, a carbon emission accounting system can use an additional loss model to determine the additional losses that cause the winding temperature rise based on the rate of change of winding temperature rise, which is characterized by the winding temperature rise.

[0092] S308 determines the sum of the target steady-state load loss and the additional loss as the real-time load loss corresponding to the winding temperature rise.

[0093] For example, a carbon emission accounting system can determine the sum of the target steady-state load loss and additional losses as the real-time load loss corresponding to the winding temperature rise.

[0094] In the above embodiments, a static correspondence between temperature rise and loss is established through a steady-state loss model. At the same time, an additional loss model is introduced, and the deviation caused by thermal inertia is corrected in real time using the rate of change of temperature rise. This makes the sum of the target steady-state loss and the additional loss approximate the actual resistance loss, effectively eliminating the influence of thermal inertia, improving the calculation accuracy of real-time load loss, and providing an accurate data foundation for subsequent carbon emission calculations.

[0095] In one embodiment, S304, based on the correspondence between winding temperature rise and steady-state load loss described by the steady-state loss model, determining the target steady-state load loss that matches the winding temperature rise may include:

[0096] Obtain the power-law parameter determined by the steady-state temperature rise test of the transformer. The power-law parameter reflects the nonlinearity of the transformer's heat dissipation. Input the transformer's rated load loss, rated winding steady-state temperature rise, power-law parameter, and winding temperature rise into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0097] The steady-state temperature rise test is a standardized experiment for determining the temperature rise characteristics of a transformer under thermal equilibrium conditions. It involves applying a rated load to the transformer and maintaining a stable ambient temperature until the winding temperature rise no longer changes, then measuring the final stable temperature rise value.

[0098] The power-law parameter is an exponential value characterizing the nonlinear change in heat dissipation capacity with temperature rise. It is also an exponential constant used in transformer thermal models to describe the nonlinear relationship between winding temperature rise and losses. The relationship between the heat dissipated by the transformer and the winding temperature rise is not a linear function, but a power-law function, which means that the heat dissipation efficiency changes non-proportionally as the temperature rises.

[0099] In one embodiment, a steady-state temperature rise test can be performed on the transformer, recording the steady-state temperature rise under different loads. Data fitting is then performed based on the steady-state temperature rise under different loads to obtain the power exponent parameter. For example, online identification can be performed using a least-squares fitting algorithm.

[0100] Rated load loss is the nominal active power loss of a transformer under rated operating conditions caused by the load current. It is the active power consumed by the winding resistance of the transformer at rated current and reference temperature. Rated load loss is determined by factory testing and is one of the transformer's performance parameters.

[0101] Rated winding steady-state temperature rise refers to the nominal temperature rise value of a transformer when it reaches thermal equilibrium under rated load. That is, when the transformer is subjected to rated load and the ambient temperature is the standard reference value, the winding temperature is higher than the ambient temperature after stabilization. This value is determined by the temperature rise test.

[0102] For example, the carbon emission accounting system can obtain the power exponent parameter, which is determined by a steady-state temperature rise test of a transformer and reflects the nonlinearity of the transformer's heat dissipation, and then input the transformer's rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0103] In one embodiment, the winding temperature rise ΔT s There is a power function relationship between load loss and load loss:

[0104] P k =C·(ΔT s ) m

[0105] Where C is the heat dissipation coefficient, which is related to the cooling method and structure. The exponent m is usually between 1.0 and 1.25. For example, it is close to 1.25 when it is pure convection heat dissipation, but the actual heat dissipation of transformer windings is close to 1.0 to 1.2.

[0106] For rated operating conditions:

[0107] P n =C·(ΔTn) m

[0108] Among them, P n For rated load loss, ΔT n This is the steady-state temperature rise of the rated winding.

[0109] Eliminating C yields the steady-state mapping:

[0110] P k = P n ·(ΔT s / ΔT n ) m

[0111] Based on this, the steady-state loss model can be obtained as follows:

[0112] Steady-state load loss = P n ×(ΔT / ΔT n ) α

[0113] Where α=m, is the power exponent parameter.

[0114] When calculating the target steady-state load loss, the carbon emission accounting system needs to obtain the transformer's power exponent parameters, rated load loss, and rated winding steady-state temperature rise. By inputting these parameters and the winding temperature rise as known quantities into the steady-state loss model, the target steady-state load loss can be output.

[0115] In one embodiment, the power exponent parameter α can range from 0.8 to 1.2. For pure natural convection cooling, the relationship between heat dissipation power and temperature rise follows a modified form of Newton's law of cooling—the Nusselt number Nu∝(Gr·Pr)¹ / ⁴, causing the heat dissipation coefficient to change with temperature rise. Ultimately, the heat loss in steady state is proportional to the temperature rise as P∝ΔT. 5 / 4 The relationship is ΔT∝P 0.8 .

[0116] Conversely, when heat rise is used to represent losses:

[0117] P∝ΔT 1.25

[0118] Therefore, theoretically α = 1.25.

[0119] However, the range is set to 0.8~1.2 instead of 1.25 because of the influence of the hybrid cooling method and the positive feedback of winding resistance increasing with temperature. Specifically, in the forced oil circulation air cooling method, heat dissipation efficiency is improved, the sensitivity of temperature rise to losses decreases, and the exponent α may decrease to around 1.0. In the forced oil circulation water cooling method, the exponent α can be as low as 0.9~1.0. In the case of natural air cooling, due to near-pure convection, the exponent is higher, but due to the influence of winding surface radiation and heat conduction, α is usually ≤1.2. Meanwhile, the load loss P... k =I 2 R, where R increases with increasing temperature. As the winding temperature rises, the resistance increases, further increasing losses, making the relationship between temperature rise and losses steeper than predicted by pure thermodynamics. If the resistance change is ignored, pure thermodynamics gives P∝ΔT. 1.25 After accounting for the resistance effect, the effective exponent may rise to 1.3~1.4. The α set in this embodiment is the equivalent exponent, used to map the measured temperature rise to the total load loss, and theoretically, it can be greater than 1.25. However, an excessively high α will make the model extremely sensitive to temperature rise noise, and the extrapolation error will be large for different load ranges. To maintain the robustness of the model, in actual engineering, α is limited to within 1.2 through online fitting. After overall averaging, the equivalent α of most transformers falls within the range of 1.0±0.2.

[0120] The engineering purpose of setting α in the range of 0.8 to 1.2 is primarily to prevent overfitting. Without constraints, α might converge to physically unreasonable extreme values, such as 0.3 or 3.0, resulting in small fitting errors but poor extrapolation performance. Limiting α to [0.8, 1.2] is equivalent to imposing physical priors on the model, ensuring that the model exhibits monotonically increasing and reasonably convex characteristics across any load range. Secondly, it accommodates different cooling methods and winding structures. Finally, it can work in conjunction with the correction parameter β, limiting α to a reasonable narrow range, ensuring that β primarily reflects the true heat capacity rather than compensating for model structural deviations.

[0121] In the above embodiments, the introduction of power exponent parameters can accurately describe the nonlinearity of heat dissipation, thereby replacing the traditional linear assumption. At the same time, the rated point and the current temperature rise are substituted into the steady-state loss model, so that the steady-state loss calculation is consistent with the actual heat dissipation characteristics. This effectively eliminates the systematic error caused by the linear assumption, significantly improves the calculation accuracy of the target steady-state load loss over a wide load range, and provides a more reliable physical basis for subsequent carbon emission accounting.

[0122] In one embodiment, such as Figure 4 As shown in S306, using an additional loss model, the additional losses that cause the winding temperature rise are determined based on the winding temperature rise rate, which is characterized by the winding temperature rise. These losses may include:

[0123] S402, acquire the temperature rise rate data obtained from the transient temperature rise test of the transformer.

[0124] The transient temperature rise test is an experiment to measure the dynamic change of transformer temperature rise over time during load changes. A step load can be applied to the transformer (e.g., suddenly increasing from no-load to rated load), and the winding temperature rise can be continuously recorded from the initial value to the steady-state value to obtain the temperature rise curve over time.

[0125] Temperature rise rate data refers to the set of original measurements of how fast the temperature rise changes with time during a transient process. It can be understood as the first derivative of the temperature rise with respect to time at different time points in a transient temperature rise test. It is obtained by differentiating or differentiating the temperature rise-time curve and reflects the strength of the transformer's thermal inertia.

[0126] For example, a carbon emission accounting system can acquire data on the rate of temperature rise obtained from transient temperature rise tests on transformers.

[0127] S404, by fitting the temperature rise rate data, obtains the correction parameters of the transformer; the correction parameters are used to reflect the equivalent heat capacity of the transformer.

[0128] Among them, data fitting refers to the method of approximating discrete data points with data functions. By fitting the data on the rate of temperature rise, a correction parameter that reflects the equivalent heat capacity of the transformer can be obtained.

[0129] Among them, the correction parameter is a coefficient used to correct the difference between the model and the actual situation. Its physical meaning is to characterize the equivalent heat capacity of the transformer.

[0130] For example, the carbon emission accounting system can perform data fitting on the temperature rise rate data to obtain the correction parameters of the transformer; the correction parameters are used to reflect the equivalent heat capacity of the transformer.

[0131] In one embodiment, the correction parameter can be obtained by fitting data from transient temperature rise tests, such as the rate of temperature rise under step load or a period of known load rate, which is essentially the equivalent heat capacity of the winding.

[0132] S406 uses an additional loss model to determine the rate of change of winding temperature rise of the transformer based on the winding temperature rise, and the product of the rate of change of winding temperature rise and the correction parameter is determined as the additional loss that causes the winding temperature rise.

[0133] For example, the carbon emission accounting system can input the winding temperature rise and correction parameters into the additional loss model. The additional loss model can first determine the winding temperature rise rate of the transformer based on the winding temperature rise, and then calculate the product of the winding temperature rise rate and the correction parameters to obtain the additional losses that cause the winding temperature rise.

[0134] In one embodiment, according to Ohm's thermal law:

[0135] P k (t)=ΔT(t)R th +C th ·d[ΔT(t)] / dt

[0136] That is: the loss P at the current moment k (t) A portion is used to maintain the current temperature rise (heat dissipation power = ΔT / R) th Part of it is used to raise the winding temperature (heat storage power = C) th ·dΔT / dt).

[0137] Write the heat dissipation term as a steady-state relationship between power and temperature rise:

[0138] ΔT(t) / R th =P n ·(ΔT(t) / ΔT n ) α

[0139] therefore:

[0140] P k (t)=Pn ·(ΔT(t) / ΔTn) α +C th ·d[ΔT(t)] / dt

[0141] Let β=C th (Heat capacity) gives us the additional loss model:

[0142] Additional loss = β × d[ΔT] / dt

[0143] The carbon emission accounting system can input the correction parameters and winding temperature rise as known parameters into the above-mentioned additional loss model to calculate the additional losses.

[0144] In the above embodiments, the temperature rise rate data is obtained through transient temperature rise test and the correction parameter is obtained by fitting. The product of the temperature rise rate and the correction parameter is determined as the additional loss, realizing the physical quantification of the thermal inertia power component. This enables the real-time load loss under dynamic operating conditions to accurately reflect the actual heating of the winding, reduces the estimation deviation in the transient process, and provides high-precision data that is synchronized with the real thermal process for carbon emission accounting.

[0145] In one embodiment, the rated load loss, rated winding steady-state temperature rise, power exponent parameters, and winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise. This may include:

[0146] Obtain the transformer's operating status information. If, based on the operating status information, it is determined that the transformer does not meet the forced zero-set judgment condition, input the transformer's rated load loss, rated winding steady-state temperature rise, power exponent parameters, and winding temperature rise into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0147] Among them, the operating status information is data used to describe the current electrical connections and load status of the transformer. It can be used to determine whether the transformer is always in grid-connected status and whether it will not be unloaded for a long time. Examples include high-voltage side circuit breaker position signals, low-voltage side circuit breaker position signals, and continuous no-load timers.

[0148] The forced zero-set judgment condition is a preset condition used to determine whether a transformer needs to be forced to zero. If the transformer meets the forced zero-set judgment condition, then a forced zero-set judgment needs to be performed, i.e., further determination of whether the transformer needs to be forced to zero. If the transformer does not meet the forced zero-set judgment condition, then a forced zero-set judgment is not necessary. Understandably, the purpose of setting the forced zero-set judgment condition is to prevent the calculation of non-zero load losses when the transformer is actually in an unloaded or stopped state, thus avoiding errors in carbon emission accounting.

[0149] For example, when the transformer is unloaded, that is, the primary side is energized and the secondary side is open, the load loss P k Theoretically, the temperature should be 0, but there is still a slight temperature rise in the winding. This is due to the heat transfer from the core caused by no-load losses. If the ambient temperature is low and ventilation is good, this temperature rise may be close to 0 or even negative. If directly input into the model, even if ΔT≈0, the steady-state loss model calculation result will either be 0 or a small positive or negative value due to measurement noise. Taking the α-th power of a negative number is meaningless, and the program may process it as 0. More seriously, when the transformer is shut down, i.e., the primary side is de-energized, the winding temperature gradually drops to the ambient temperature, and the temperature rise ΔT may be negative. This is because sensor noise or heat dissipation causes the winding temperature to be temporarily lower than the ambient temperature. At this time, the model will output unstable or even abnormal values. Therefore, it is necessary to set a forced zero-setting judgment condition to reduce the possibility of calculating non-zero load losses when the transformer is actually in a no-load or shutdown state.

[0150] Understandably, if the transformer does not meet the forced zero-setting judgment condition based on the operating status information, it can be assumed that it is not necessary to force the rated load loss to zero, and the target steady-state load loss can be accurately calculated.

[0151] In one embodiment, the forced zero-setting condition may include the transformer not always being connected to the grid, or the possibility of prolonged no-load operation.

[0152] For example, the carbon emission accounting system can obtain the transformer's operating status information and determine whether the transformer meets the mandatory zero-setting judgment condition based on the transformer's operating status information. If the transformer does not meet the mandatory zero-setting judgment condition, the rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise of the transformer can be directly input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0153] In the above embodiments, the determination of whether the transformer meets the forced zero-setting judgment condition based on the transformer operating status information can reduce the erroneous loss calculation under no-load or shutdown conditions through pre-processing logic screening, ensuring that carbon emission accounting is only carried out under effective operating conditions, reducing the risk of overstating emissions due to miscalculation, and improving the reliability of carbon emission accounting.

[0154] In one embodiment, such as Figure 5 As shown, the method for determining the carbon emissions of a transformer may also include the following steps:

[0155] S502, based on the operating status information, if it is determined that the transformer meets the forced zero-setting judgment condition, the forced zero-setting time threshold of the transformer is determined based on the thermal time constant of the transformer.

[0156] The thermal time constant of a transformer is an inherent thermal inertia parameter that describes the rate of temperature change in a transformer. It is determined by the ratio of the transformer's equivalent heat capacity to its equivalent heat dissipation coefficient, and reflects the transformer's response speed to temperature changes.

[0157] The forced zero-set time threshold is the minimum duration required to determine the no-load state. Only when the winding temperature rise is below the no-load judgment temperature for a continuous period exceeding this threshold can the transformer be considered to be in a no-load state, and a forced zero-set will be performed. Understandably, different transformers may correspond to different forced zero-set time thresholds.

[0158] For example, the forced zero-reset time threshold for small and medium-sized oil-immersed transformers can be set to 30 minutes. For such transformers (e.g., 10kV, 1000kVA), the time required for the winding temperature to drop from the rated temperature rise (approximately 55K) to near ambient temperature (ΔT<1K) after shutdown is approximately 2 to 4 times the thermal time constant. Dry-type transformers, with their lower thermal inertia, can reduce this time to 10 to 15 minutes. Large oil-immersed transformers, however, may require 40 to 60 minutes.

[0159] For example, when the carbon emission accounting system determines that the transformer meets the mandatory zero-setting judgment conditions based on the operating status information, it can determine the mandatory zero-setting time threshold that matches the transformer based on the transformer's thermal time constant.

[0160] In one embodiment, the forced zeroing time threshold t off The thermal time constant τ of the transformer is set, with a value ranging from 0.5τ to 2τ, and preferably t. off =τ. For oil-immersed distribution transformers, the typical value is 20~40 minutes. For dry-type transformers, the typical value is 10~20 minutes. In cases where the thermal time constant cannot be obtained, the default value is 30 minutes. This threshold can also be manually set by the user based on field experience or updated online through an automatic identification algorithm.

[0161] S504 If the temperature rise of the transformer winding is less than the no-load judgment temperature and the duration exceeds the forced zero-set time threshold, then the rated load loss of the transformer is set to zero, and the updated rated load loss is obtained.

[0162] The no-load judgment temperature is a temperature rise threshold used to distinguish whether a transformer is in a no-load thermal state. When the winding temperature rise is lower than the no-load judgment temperature, the transformer can be considered to be in a no-load or no-current state, because the losses generated by operating under load will at least cause the temperature rise to reach the temperature value corresponding to the no-load judgment temperature.

[0163] In one embodiment, the no-load determination temperature can be the ambient temperature or a preset threshold temperature.

[0164] For example, the carbon emission accounting system can compare the winding temperature rise of the transformer with the no-load judgment temperature. If the winding temperature rise of the transformer is less than the no-load judgment temperature, the duration of this state is counted. If the duration exceeds the forced zeroing time threshold, the rated load loss of the transformer is set to zero to obtain the updated rated load loss.

[0165] S506 inputs the transformer's rated winding steady-state temperature rise, updated rated load loss, power exponent parameters, and winding temperature rise into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0166] For example, the carbon emission accounting system can input the rated winding steady-state temperature rise, the updated rated load loss, the power exponent parameter, and the winding temperature rise of the transformer into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise. At this time, the updated rated load loss is 0.

[0167] In one embodiment, if the winding temperature rise of the transformer is greater than or equal to the no-load judgment temperature, or if the duration of the winding temperature rise being less than the no-load judgment temperature does not exceed the forced zero-time threshold, then the rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise of the transformer are directly input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0168] In one embodiment, when the winding temperature rise ΔT ≤ 0, the temperature rise measurement can be considered absolutely reliable and with extremely low noise, and the carbon emission accounting system can directly determine the rated load loss P. k =0, no time delay required.

[0169] In the above embodiments, when the winding temperature rise is lower than the no-load judgment temperature and continues to exceed the threshold determined based on the thermal time constant, the rated load loss is set to zero, which can make the model output return to zero correctly. Combined with the reasonable delay of the thermal time constant setting, the possibility of misjudgment of transient fluctuations is reduced, and the accuracy and reliability of carbon emission accounting under no-load conditions are significantly improved.

[0170] In one embodiment, such as Figure 6 As shown, a method for determining the carbon emissions of a transformer is provided, which can be applied to applications such as... Figure 7 The transformer shown is used as an example. The method may specifically include the following steps:

[0171] S601 obtains the real-time winding temperature and real-time ambient temperature of the transformer.

[0172] Winding temperature sensors, including but not limited to fiber Bragg grating sensors, platinum resistance temperature sensors, and negative temperature coefficient thermistors, are installed inside or on the surface of transformer windings.

[0173] In one embodiment, the fiber optic temperature sensor, connected to a flange mounted on the oil tank via a temperature detection probe embedded in the transformer coil, can transmit the winding temperature information during transformer operation to the fiber optic temperature sensor in real time. This allows for dynamic calculation of carbon emissions during operation based on real-time load oil temperature and local power grid conditions, providing an effective channel for tracking the carbon footprint of the product throughout its entire lifecycle.

[0174] S602 calculates the winding temperature rise based on the real-time winding temperature and the real-time ambient temperature.

[0175] The winding temperature sensor collects the winding temperature T in real time at a sampling frequency of no less than once per minute. w Simultaneously, the ambient temperature or cooling medium inlet temperature T at the transformer installation location is collected. a ; Calculate real-time winding temperature rise:

[0176] ΔT = T w -T a .

[0177] S603, based on direct mapping of load losses from a dynamic thermal model.

[0178] A nonlinear dynamic mapping model is established between winding temperature rise and load loss, converting the real-time temperature rise ΔT into real-time load loss P. k :

[0179] P k = P n × [ΔT / ΔT n ] ^α+ β × d[ΔT] / dt

[0180] Among them, P n The load loss (kW) of the transformer under rated load is taken from the nameplate or the factory test report.

[0181] ΔT n Steady-state temperature rise of windings under rated load (K), taken from type test report.

[0182] α: Loss-temperature rise power exponent, with a value range of 0.8 to 1.2, determined by fitting transformer no-load / load temperature rise test data.

[0183] In one embodiment, the mapping relationship between winding temperature rise and load loss under different power exponents α is shown in the figure below. Figure 8 As shown.

[0184] β: Dynamic correction coefficient, reflecting the instantaneous impact of the rate of temperature change on losses, in units of kW·s / K.

[0185] d[ΔT] / dt: The derivative of winding temperature rise with respect to time.

[0186] Traditional methods directly calculate P using current I. k =I 2 R requires a current transformer. However, this formula can deduce P simply from the temperature rise ΔT and its rate of change. k This is because the temperature rise ΔT itself contains comprehensive information about the heating and cooling of the windings, and is a "response signal" after the loss acts on the heat capacity and thermal resistance. By inversely solving the thermal circuit model, the excitation signal (loss) can be recovered from the response signal.

[0187] In one embodiment, when the winding temperature rise ΔT is less than the ambient temperature or a preset limit and lasts for more than 30 minutes, the transformer is determined to be in a shutdown or no-load state, and P is forcibly set. n =0, to avoid miscalculation.

[0188] In one embodiment, during a period of operation with a known load rate of the transformer, such as 72 hours of continuous operation data, the values ​​of α and β are determined by least squares fitting, with the measured temperature rise as input and the load loss in the nameplate or factory test report as reference. Understandably, the values ​​of α and β are automatically updated every quarter or every six months.

[0189] S604, calculate the total power loss of the transformer.

[0190] The total power loss E of the transformer during its operation [t1, t2] is:

[0191] E = ∫_{t1}^{t2} [P0 + P k dt

[0192] Wherein, P0 is the no-load loss (kW), which is taken from the transformer nameplate or factory test report and is considered a constant value during the operation period.

[0193] In one embodiment, the P0 calibration step may include: measuring the actual no-load loss P0 once a year during a planned power outage maintenance of the transformer, and updating P0 with the measured value if the deviation from the nameplate value exceeds ±5%.

[0194] S605 calculates the carbon emissions of transformers.

[0195] This embodiment calculates the carbon emissions of the transformer itself, and does not replace the user-side electricity meter. Therefore, it is not necessary to calculate the carbon emissions corresponding to the total input electrical energy on the primary side of the transformer.

[0196] C total = E × EF

[0197] Among them, EF is the grid carbon emission factor (kgCO2 / kWh), the power generation carbon footprint factor is about 0.581 kgCO2 / kWh depending on the regional grid structure, and the transmission and distribution carbon footprint factor is 0.0036 kgCO2 / kWh excluding line losses. It adopts the annual average emission factor of the provincial grid where the transformer is located, or the dynamic emission factor released in real time by the power dispatch center and integrated over time.

[0198] S606 monitors and provides early warnings for carbon emissions from transformers based on their carbon emission levels.

[0199] Real-time temperature rise, real-time load loss, instantaneous carbon emission rate, and cumulative carbon emissions are uploaded to the cloud management system to generate a carbon emission time-series curve, such as... Figure 9 As shown, when carbon emissions per unit time exceed a preset threshold, an early warning signal is automatically issued.

[0200] In one embodiment, a unit with a rated capacity of 10000kVA and a rated load loss P is used. n =50kW, no-load loss P0=8kW, rated temperature rise ΔT n Taking a 55K oil-immersed transformer as an example, at t=10:00 on a certain operating day, the winding temperature T was measured by fiber optic thermography. w =85℃, ambient temperature T a =25℃.

[0201] 1) ΔT = 85℃ - 25℃ = 60K.

[0202] 2) Simplified calculation: Taking α = 1.0, β = 0.05 kW·s / K, and the rate of temperature change dΔT / dt = 0.02 K / s, then:

[0203] P k = P n ×[ΔT / ΔT n ] ^α+ β×d[ΔT] / dt)

[0204] = 50×(60 / 55)^1.0 + 0.05×0.02≈54.55 + 0.001=54.551kW.

[0205] 3) Total loss P 总 = P0+P k = 8 + 54.551 = 62.551 kW.

[0206] If this condition continues for 1 hour, the energy loss will be 62.551 kWh. Given a local EF of 0.581 kg CO2 / kWh, the carbon emission for that hour will be 36.34 kg CO2.

[0207] Based on the real-time winding temperature rise of the transformer, a nonlinear dynamic mapping model is used to convert the real-time temperature rise ΔT into the real-time load loss P. k Furthermore, by combining the dynamic power emission factors released by the local power grid, the carbon emissions during any operational phase at any given time or period can be calculated.

[0208] By combining pre-set emission data from the transformer manufacturing stage with the system's real-time cumulative calculation of the transformer's total carbon emissions since commissioning, and overlaying it with pre-stored lifecycle inventory data (carbon emissions from the raw material acquisition stage + manufacturing stage), the data is uploaded to the cloud monitoring platform, enabling real-time visualization of the entire lifecycle carbon footprint.

[0209] The method for determining the carbon emissions of transformers in the above embodiments has several advantages. First, unlike existing carbon emission calculations that rely on electrical parameters such as operating current and voltage, this method only requires temperature sensors, making it suitable for scenarios such as older transformers where current transformers cannot be installed and high-voltage side enclosed switchgear. Second, it eliminates the need for expensive equipment such as voltage transformers, current transformers, and power quality analyzers; continuous carbon emission monitoring can be achieved simply by deploying fiber optic temperature sensors or platinum resistance temperature sensors, significantly reducing the cost of carbon emission calculation. Third, it employs a mapping model using a power exponent plus a dynamic differential term, which, unlike the current linear temperature correction coefficient method, offers better dynamic response characteristics. Fourth, all sensors are located on the low-voltage side or within the winding itself, eliminating the need to operate high-voltage equipment and minimizing safety risks for maintenance personnel. Fifth, by identifying α and β parameters through historical operating data, model accuracy can be optimized without power outages. Sixth, the proposed real-time carbon footprint calculation method for transformers based on winding temperature rise provides power grid companies with accurate nodal carbon flow data, supporting low-carbon operation and scheduling of a new power system primarily based on new energy sources.

[0210] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0211] Based on the same inventive concept, this application also provides a transformer carbon emission determination device for implementing the above-described transformer carbon emission determination method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more transformer carbon emission determination device embodiments provided below can be found in the limitations of the transformer carbon emission determination method described above, and will not be repeated here.

[0212] In one embodiment, such as Figure 10 As shown, a transformer carbon emission determination device 1000 is provided, comprising: a winding temperature rise module 1001, a real-time load loss determination module 1002, a total power loss determination module 1003, and a carbon emission determination module 1004, wherein:

[0213] The winding temperature rise module 1001 is used to determine the winding temperature rise of the transformer based on the real-time winding temperature during transformer operation and the real-time ambient temperature of the environment in which the transformer is located.

[0214] The real-time load loss determination module 1002 is used to determine the real-time load loss corresponding to the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss, as well as the winding temperature rise rate characterized by the winding temperature rise.

[0215] The total power loss determination module 1003 is used to determine the total power loss of the transformer based on the real-time load loss and the no-load loss of the transformer.

[0216] The carbon emission determination module 1004 is used to determine the carbon emission of the transformer by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs.

[0217] In one embodiment, the real-time load loss determination module 1002 is configured to: invoke a pre-configured steady-state loss model and an additional loss model for the transformer; determine a target steady-state load loss matching the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss described by the steady-state loss model; use the additional loss model to determine the additional loss that causes the winding temperature rise based on the winding temperature rise rate of change characterized by the winding temperature rise; and sum the target steady-state load loss and the additional loss to determine the real-time load loss corresponding to the winding temperature rise.

[0218] In one embodiment, the real-time load loss determination module 1002 is used to: obtain the power exponent parameter determined by the steady-state temperature rise test of the transformer, the power exponent parameter being used to reflect the heat dissipation nonlinearity of the transformer; input the rated load loss, rated winding steady-state temperature rise, power exponent parameter and winding temperature rise of the transformer into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0219] In one embodiment, the real-time load loss determination module 1002 is used to: acquire temperature rise rate data obtained from a transient temperature rise test of the transformer; perform data fitting on the temperature rise rate data to obtain the correction parameters of the transformer; the correction parameters are used to reflect the equivalent heat capacity of the transformer; use an additional loss model to determine the winding temperature rise rate of the transformer based on the winding temperature rise, and determine the additional loss that causes the winding temperature rise by multiplying the winding temperature rise rate by the correction parameters.

[0220] In one embodiment, the real-time load loss determination module 1002 is used to: acquire the operating status information of the transformer; and, if it is determined from the operating status information that the transformer does not meet the forced zero-setting judgment condition, input the rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise of the transformer into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0221] In one embodiment, the transformer carbon emission determination device 1000 further includes:

[0222] The time threshold determination module is used to determine the forced zeroing time threshold of the transformer based on the thermal time constant of the transformer, when the transformer meets the forced zeroing judgment condition based on the operating status information.

[0223] The rated load loss zeroing module is used to set the rated load loss of the transformer to zero if the winding temperature rise of the transformer is less than the no-load judgment temperature and the duration exceeds the forced zeroing time threshold, thus obtaining the updated rated load loss.

[0224] The steady-state load loss calculation module is used to input the transformer's rated winding steady-state temperature rise, updated rated load loss, power exponent parameters, and winding temperature rise into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

[0225] Each module in the aforementioned transformer carbon emission determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0226] In one embodiment, a computer device is provided, which may be a server integrating a carbon emission accounting system, and its internal structure diagram may be as follows: Figure 11As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data related to a method for determining the carbon emissions of transformers. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for determining the carbon emissions of transformers.

[0227] Those skilled in the art will understand that Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0228] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the specific steps of the above-described embodiment of the method for determining the carbon emissions of a transformer.

[0229] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the specific steps of the above-described method embodiment for determining the carbon emissions of a transformer.

[0230] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the specific steps of the above-described embodiment of the method for determining the carbon emissions of a transformer.

[0231] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the acquisition, storage, processing, and transmission of the data all comply with relevant laws and regulations.

[0232] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0233] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0234] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the carbon emissions of a transformer, characterized in that, The method includes: The winding temperature rise of the transformer is determined based on the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment in which the transformer is located. Based on the correspondence between the winding temperature rise and the steady-state load loss, and the winding temperature rise rate characterized by the winding temperature rise, the real-time load loss corresponding to the winding temperature rise is determined. The total power loss of the transformer is determined based on the real-time load loss and the no-load loss of the transformer. The carbon emissions of the transformer are determined by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs.

2. The method according to claim 1, characterized in that, The determination of the real-time load loss corresponding to the winding temperature rise based on the preset correspondence between the winding temperature rise and the steady-state load loss, and the winding load change trend characterized by the winding temperature rise, includes: Invoke the pre-configured steady-state loss model and additional loss model for the transformer; Based on the correspondence between winding temperature rise and steady-state load loss described by the steady-state loss model, a target steady-state load loss that matches the winding temperature rise is determined. Using the aforementioned additional loss model, the additional losses that generate the winding temperature rise are determined based on the winding temperature rise rate, which is characterized by the winding temperature rise. The sum of the target steady-state load loss and the additional loss is determined as the real-time load loss corresponding to the winding temperature rise.

3. The method according to claim 2, characterized in that, The determination of the target steady-state load loss matching the winding temperature rise, based on the correspondence between the winding temperature rise and steady-state load loss described by the steady-state loss model, includes: Obtain the power exponent parameter determined by the steady-state temperature rise test of the transformer, the power exponent parameter being used to reflect the heat dissipation nonlinearity of the transformer; The rated load loss, rated winding steady-state temperature rise, power exponent parameters, and winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

4. The method according to claim 2, characterized in that, The step of using the additional loss model to determine the additional losses that cause the winding temperature rise based on the winding temperature rise rate of change, as characterized by the winding temperature rise, includes: Obtain the temperature rise rate data obtained from the transient temperature rise test of the transformer; The temperature rise rate data is fitted to obtain the correction parameters of the transformer; the correction parameters are used to reflect the equivalent heat capacity of the transformer. The additional loss model is used to determine the winding temperature rise rate of the transformer based on the winding temperature rise. The product of the winding temperature rise rate and the correction parameter is determined as the additional loss that causes the winding temperature rise.

5. The method according to claim 3 or 4, characterized in that, The process of inputting the rated load loss, rated winding steady-state temperature rise, power exponent parameters, and winding temperature rise of the transformer into the steady-state loss model to obtain the target steady-state load loss matching the winding temperature rise includes: Obtain the operating status information of the transformer; If, based on the operating status information, it is determined that the transformer does not meet the forced zero-setting judgment condition, the rated load loss, rated winding steady-state temperature rise, power exponent parameter, and winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

6. The method according to claim 5, characterized in that, The method further includes: If the transformer meets the forced zero-setting judgment condition based on the operating status information, the forced zero-setting time threshold of the transformer is determined based on the thermal time constant of the transformer. If the temperature rise of the transformer winding is less than the no-load judgment temperature and the duration exceeds the forced zero-time threshold, then the rated load loss of the transformer is set to zero, and the updated rated load loss is obtained. The rated winding steady-state temperature rise, the updated rated load loss, the power exponent parameter, and the winding temperature rise of the transformer are input into the steady-state loss model to obtain the target steady-state load loss that matches the winding temperature rise.

7. A device for determining the carbon emissions of a transformer, characterized in that, The device includes: The winding temperature rise module is used to determine the winding temperature rise of the transformer based on the real-time winding temperature of the transformer during operation and the real-time ambient temperature of the environment in which the transformer is located. The real-time load loss determination module is used to determine the real-time load loss corresponding to the winding temperature rise based on the correspondence between the winding temperature rise and the steady-state load loss, as well as the winding temperature rise change rate characterized by the winding temperature rise. The total power loss determination module is used to determine the total power loss of the transformer based on the real-time load loss and the no-load loss of the transformer. The carbon emission determination module is used to determine the carbon emission of the transformer by multiplying the total power loss by the carbon emission factor of the power grid to which the transformer belongs.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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