Calculation method, system and equipment for carbon flow rate of zero-carbon power supply station and medium

Abstract

The invention discloses a zero-carbon power supply station carbon flow rate calculation method, system and device and a medium, and the method comprises the steps: obtaining power supply related data, and obtaining branch power according to the power supply related data; calculating the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the bus carbon potential to which the branch belongs; calculating the loss carbon flow rate of the zero-carbon power supply station based on the branch power and the bus carbon potential to which the branch belongs in combination with the new energy power generation scene; and based on the branch carbon flow rate and the loss carbon flow rate, identifying a high-carbon emission area, and optimizing an energy distribution strategy of the zero-carbon power supply station. According to the method, different conditions of new energy generating capacity are fully considered, the branch carbon flow rate and the loss carbon flow rate are calculated, the carbon emission condition of each part of the zero-carbon power supply station can be known, the high-carbon emission area can be accurately found, the energy distribution strategy can be reasonably optimized according to the results, and the overall carbon emission is reduced. Energy conservation and emission reduction of the zero-carbon power supply station are achieved, and the energy utilization efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, system, device and medium for calculating the carbon flow rate of a zero-carbon power supply. Background Art

[0002] Zero-carbon emissions have become a key development direction for power systems. Zero-carbon power stations, key infrastructure for achieving this goal, feature complex microgrid structures encompassing a variety of renewable energy generation methods and load types. The volatility of renewable energy generation and the diversity of load demand present challenges for the operation and management of zero-carbon power stations, particularly in terms of carbon footprint tracking and emissions management. Traditional methods for calculating carbon emissions in power systems are primarily based on fossil fuel consumption. However, the introduction of renewable energy in zero-carbon power stations complicates carbon emission calculations. While renewable energy generation itself produces no carbon emissions, its generation and efficiency are affected by factors such as weather and time of day, leading to variations in power flow and carbon emission characteristics within the microgrid. Furthermore, the diverse loads and power losses within zero-carbon power stations also require more sophisticated carbon emission calculations.

[0003] In existing carbon emission calculation methods, the impact of different renewable energy power generation in the zero-carbon power station microgrid on carbon emissions is usually not taken into account, nor is a reasonable allocation of virtual carbon emissions caused by power losses. This results in the inability to accurately reflect the actual carbon emissions of each branch when calculating the branch carbon flow rate of the zero-carbon power station, and it is also impossible to provide effective support for the carbon emission management and optimization of the power station. Therefore, a method for calculating the carbon flow rate of a zero-carbon power station is needed. This method can take into account the differences in renewable energy power generation in the zero-carbon power station microgrid and the impact of power losses on carbon emissions, thereby achieving accurate calculation of carbon emissions of each branch and providing a scientific basis for the carbon emission management and optimization of the zero-carbon power station. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for calculating the carbon flow rate of a zero-carbon power supply to solve the problem that traditional calculation methods cannot take into account the differences in new energy power generation and the inaccurate carbon emission calculation caused by the reasonable allocation of power losses, as well as the difficulty in effectively managing and optimizing the carbon emissions of zero-carbon power supplies.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for calculating the carbon flow rate of a zero-carbon power supply, comprising:

[0008] Acquire power supply related data, and acquire branch power according to the power supply related data;

[0009] Calculating the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the busbar to which the branch belongs;

[0010] Based on the branch power and the carbon potential of the busbar to which the branch belongs, and in combination with the renewable energy power generation scenario, the loss carbon flow rate of the zero-carbon power station is calculated;

[0011] Based on the branch carbon flow rate and loss carbon flow rate, high carbon emission areas are identified and the energy distribution strategy of the zero-carbon power supply station is optimized.

[0012] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power station described in the present invention, the branch carbon flow rate of the zero-carbon power station is calculated based on the branch power and the carbon potential of the bus to which the branch belongs, including:

[0013] According to the branch type, obtain the carbon potential of the busbar to which the branch belongs;

[0014] Calculate the product of the branch power and the carbon potential of the bus to which the branch belongs to obtain the branch carbon flow rate.

[0015] The beneficial effects of this preferred technical solution are: determining the carbon potential based on the branch type, and then simply multiplying to calculate the branch carbon flow rate, thereby achieving rapid and accurate quantification of carbon emissions from different branches, laying the foundation for a comprehensive understanding of the carbon emission status of the power supply station.

[0016] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power supply station described in the present invention, the loss carbon flow rate of the zero-carbon power supply station is calculated in combination with the new energy power generation scenario, including:

[0017] Renewable energy generation scenarios include insufficient and excessive renewable energy generation;

[0018] The carbon flow rate of AC bus loss, the carbon flow rate of DC bus loss and the carbon flow rate of branch loss are calculated respectively when the renewable energy power generation is insufficient and when the renewable energy power generation is excessive.

[0019] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power supply described in the present invention, the calculation of the AC bus loss carbon flow rate, the DC bus loss carbon flow rate, and the branch loss carbon flow rate when the renewable energy power generation is insufficient and when the renewable energy power generation is excessive includes:

[0020] Based on the power supply related data, the total AC bus power loss is calculated, and the allocation coefficient is introduced to calculate the AC bus power loss, which is then multiplied by the AC bus carbon potential to obtain the AC bus loss carbon flow rate;

[0021] Calculate the total power loss of the DC bus based on the power supply related data, determine the power loss borne by the DC bus in combination with the power loss borne by the AC bus, and then multiply it by the carbon potential of the AC bus to obtain the DC loss carbon flow rate;

[0022] Each branch shares the total bus power loss according to its power ratio, and then multiplies it by the bus carbon potential to obtain the carbon loss flow rate of each branch.

[0023] The beneficial effects of this preferred technical solution are: the carbon flow rate of each bus and branch loss is calculated separately for different new energy power generation scenarios, the system loss is fully considered, and it can more accurately reflect the actual carbon emissions of the power supply station under different working conditions, providing accurate data support for energy conservation and carbon reduction.

[0024] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power supply station described in the present invention, wherein: based on the branch carbon flow rate and the loss carbon flow rate, high carbon emission areas are identified and the energy allocation strategy of the zero-carbon power supply station is optimized, including:

[0025] If the branch carbon flow rate and loss carbon flow rate exceed the set threshold, the area where the branch is located is marked as a high carbon emission area;

[0026] Analyze the high carbon emission areas and formulate differentiated energy allocation strategies based on the analysis results.

[0027] The beneficial effects of this preferred technical solution are: by setting thresholds to mark high-carbon emission areas and formulating differentiated strategies, high-emission areas can be accurately located, targeted and optimized energy allocation can be achieved, the overall carbon emissions of power supply stations can be effectively reduced, and energy utilization efficiency can be improved.

[0028] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power supply station described in the present invention, wherein: according to the branch type, obtaining the carbon potential of the busbar to which the branch belongs includes:

[0029] If the branch is an AC load, the carbon potential of the branch power is the carbon potential of the AC bus;

[0030] If the branch is a DC load, the carbon potential of the branch power is the carbon potential of the DC bus.

[0031] If the voltage difference exceeds the voltage regulation dead zone, a bus voltage regulation incomplete signal is output.

[0032] As a preferred solution of the method for calculating the carbon flow rate of the zero-carbon power supply of the present invention, it also includes:

[0033] If the AC bus injects power into the DC bus, the carbon potential of the injected power is the carbon potential of the AC bus;

[0034] If the DC bus injects power into the AC bus, the carbon potential of the injected power is the carbon potential of the DC bus.

[0035] In a second aspect, the present invention provides a system for calculating the carbon flow rate of a zero-carbon power supply, comprising: a data acquisition module for acquiring power supply-related data;

[0036] A primary calculation module, used to obtain branch power according to the power supply related data;

[0037] A secondary calculation module is used to calculate the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the bus to which the branch belongs; based on the branch power and the carbon potential of the bus to which the branch belongs, and in combination with the new energy power generation scenario, calculate the loss carbon flow rate of the zero-carbon power supply station;

[0038] The identification and optimization module is used to identify high-carbon emission areas based on the branch carbon flow rate and loss carbon flow rate, and optimize the energy distribution strategy of the zero-carbon power supply station.

[0039] In a third aspect, the present invention provides an electronic device, comprising:

[0040] memory and processor;

[0041] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for calculating the carbon flow rate of a zero-carbon power supply are implemented.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for calculating the carbon flow rate of a zero-carbon power supply.

[0043] Compared with existing technologies, this invention offers significant advantages: By fully accounting for the varying levels of renewable energy generation, it calculates branch carbon flow rates and loss carbon flow rates. This not only allows for understanding the carbon emissions of each component of a zero-carbon power station and accurately identifying high-carbon emission areas, but also allows for rationally optimizing energy allocation strategies based on these results, reducing overall carbon emissions. This helps achieve the energy conservation and emission reduction goals of zero-carbon power stations and improves energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is a schematic diagram of the overall flow of a method for calculating the carbon flow rate of a zero-carbon power supply according to an embodiment of the present invention.

[0046] Figure 2 A schematic diagram of network metering of insufficient renewable energy power generation according to a method for calculating the carbon flow rate of a zero-carbon power supply according to an embodiment of the present invention.

[0047] Figure 3 A schematic diagram of network metering of excess renewable energy power generation according to a method for calculating the carbon flow rate of a zero-carbon power supply according to an embodiment of the present invention.

[0048] Figure 4 Schematic diagram of measurement points of an XP power station according to a method for calculating the carbon flow rate of a zero-carbon power station described in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0050] Example 1, with reference to Figure 1 , as one embodiment of the present invention, provides a method for calculating the carbon flow rate of a zero-carbon power supply, comprising:

[0051] S100: Obtain power supply related data, and obtain branch power according to the power supply related data;

[0052] S102: Calculate the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the busbar to which the branch belongs;

[0053] S104: Calculate the carbon loss rate of the zero-carbon power station based on the branch power and the carbon potential of the busbar to which the branch belongs, combined with the renewable energy power generation scenario;

[0054] S106: Based on branch carbon flow rate and loss carbon flow rate, identify high carbon emission areas and optimize the energy distribution strategy of zero-carbon power supply stations.

[0055] It should be noted that the microgrid structure inside the zero-carbon power supply station is complex, the power generation of new energy is unstable and the load is diverse, and it is difficult for traditional calculation methods to accurately calculate carbon emissions. Step S100 obtains the branch power by obtaining power supply related data to provide basic data for subsequent calculations. Step S102 calculates the branch carbon flow rate based on the branch power and the carbon potential of the bus to which it belongs, which can accurately quantify the carbon emissions of each branch. Step S104 calculates the loss carbon flow rate in combination with the new energy power generation scenario, fully considering the loss differences under different power generation conditions. Finally, based on the two carbon flow rates, high-carbon emission areas are identified and the energy allocation strategy is optimized. It can achieve refined management of carbon emissions of zero-carbon power supply stations, accurately reflect the carbon emissions of microgrids, reasonably allocate losses, effectively handle carbon emission calculations of complex microgrid structures, help identify high-carbon emission areas to formulate energy-saving and emission reduction measures, and promote the green and low-carbon development of zero-carbon power supply stations and even the entire power system.

[0056] Example 2, reference Figure 1-Figure 3 , which is an embodiment of the present invention, provides a method for calculating the carbon flow rate of a zero-carbon power supply based on the above embodiment.

[0057] In an embodiment of the present invention, the power supply related data in step S100 includes the three-phase voltage, three-phase current, total active power, node carbon potential at each metering point, as well as the generated power of each power generation equipment, the power of the upper power grid, the power data of each load, etc.

[0058] In an optional embodiment, data preprocessing is performed after the power supply related data is obtained. Based on the preprocessed power supply related data, the power of the corresponding branch is directly obtained through the total active power data of each metering point; for branches whose power is not directly measured, Kirchhoff's current law and voltage law can be used to combine the known voltage and current data to calculate the branch power.

[0059] In an optional embodiment, preprocessing can be to remove outliers in the data; interpolate missing data, for example, using linear interpolation, mean filling, etc.; and normalize the data to unify data of different dimensions to the same order of magnitude for subsequent calculations.

[0060] In an embodiment of the present invention, in step S102, the branch carbon flow rate of the zero-carbon power station is calculated based on the branch power and the carbon potential of the bus to which the branch belongs, including the following steps A1-A2:

[0061] A1: According to the branch type, obtain the carbon potential of the busbar to which the branch belongs;

[0062] A2: Calculate the product of the branch power and the carbon potential of the busbar to which the branch belongs to obtain the branch carbon flow rate.

[0063] In the embodiment of the present invention, if the branch is an AC load, the carbon potential of the branch power is the carbon potential of the AC bus; if the branch is a DC load, the carbon potential of the branch power is the carbon potential of the DC bus.

[0064] Specifically, AC loads include charging piles, power supply station AC loads, etc.; DC loads include energy storage, microgrid DC loads, etc.

[0065] In the embodiment of the present invention, if the AC bus injects power into the DC bus, the carbon potential of the injected power is the carbon potential of the AC bus; if the DC bus injects power into the AC bus, the carbon potential of the injected power is the carbon potential of the DC bus.

[0066] In the embodiment of the present invention, the branch carbon flow rate calculation formula is:

[0067] R=PE

[0068] Where R is the branch carbon flow rate, in kW; P is the power flowing through the branch, in kgCO2 / h; E is the carbon potential of the bus corresponding to the branch, in kgCO2 / kWh.

[0069] In one alternative implementation, branch carbon flow rates are obtained through blockchain technology. Specifically, blockchain nodes are deployed at each device node in a zero-carbon power station. Each node records its own power data and the carbon potential data of the connected bus in real time, and uploads this data in encrypted form to the blockchain network. Leveraging blockchain's smart contract functionality, and based on the branch carbon flow rate calculation formula, relevant data from the entire network is integrated and calculated to derive the carbon flow rate for each branch.

[0070] In another optional embodiment, the branch carbon flow rate can also be obtained through a machine learning algorithm. Specifically, a large amount of historical branch power, bus carbon potential, and corresponding branch carbon flow rate data is collected as a training set. The training set is then studied using a machine learning algorithm to establish a mapping relationship model between the branch carbon flow rate, branch power, and bus carbon potential. In actual application, the current branch power and bus carbon potential data are obtained in real time and input into the trained model, and the branch carbon flow rate is obtained through model prediction.

[0071] It should be noted that the branch carbon flow rate refers to the amount of carbon dioxide emissions carried by the electricity flowing through a branch per unit time. By calculating the branch carbon flow rate, we can monitor carbon emissions and calculate the carbon flow rate in real time for key nodes within the power station, including AC and DC loads, grid nodes in the microgrid, and energy storage within the microgrid. This provides data support for the subsequent development of corresponding carbon emission optimization strategies.

[0072] In the embodiment of the present invention, step S104 calculates the carbon loss flow rate of the zero-carbon power station based on the branch power and the carbon potential of the bus to which the branch belongs, in combination with the renewable energy power generation scenario, including the following steps B1-B2:

[0073] B1: New energy power generation scenarios include insufficient new energy power generation and excess new energy power generation;

[0074] B2: Calculate the AC bus loss carbon flow rate, DC bus loss carbon flow rate, and branch loss carbon flow rate when renewable energy power generation is insufficient and when renewable energy power generation is excessive.

[0075] In the embodiment of the present invention, the total power loss of the AC bus is calculated based on the power supply related data, and the allocation coefficient is introduced to calculate the power loss borne by the AC bus, and then multiplied by the AC bus carbon potential to obtain the AC bus loss carbon flow rate;

[0076] like Figure 2 As shown, Figure 2 This is the network metering diagram for insufficient renewable energy generation. Figure 2In the equation, F represents the metering point. The metering data items include the three-phase voltage, three-phase current, total active power, node carbon potential and output carbon flow rate at each metering point. F1, F2, F3...Fm are the metering points at the main power supply switch of the substation. Fm+1, Fm+2, Fm+3, Fm+4, Fm+5 and Fm+6 are the metering points at the branch power supply switch of the power supply station busbar. The carbon potential E of the power supply station busbar Li and Lj is defined as GDS ,Right now The unit is kgCO2 / kWh, corresponding to the carbon potential at each metering point. Bus Li is the AC bus, and bus Lj is the DC bus. Since each substation is located at the power supply station, the carbon potential at the low-voltage node in each substation is the same, e1, in kgCO2 / kWh.

[0077] For example, when the renewable energy generation capacity is insufficient, the AC bus loss carbon flow rate calculation formula is:

[0078]

[0079] Where ΔP Total-AC is the total power loss at the AC bus, P SJDW is the total power output of the upper power grid,

[0080] P GDS is the AC load power (branch 2), P CDZ is the charging pile power (branch 1), P HL is the AC / DC bus interconnection branch power (branch 3), ΔP L-AC is the power loss borne by the AC bus, in kW. α is the sharing coefficient. R L-AC E is the carbon loss rate at the AC bus, in kgCO2 / h. L-AC is the carbon potential of the AC bus, in kgCO2 / kWh.

[0081] like Figure 3 As shown, Figure 3 This is the network metering diagram for excess renewable energy generation. Figure 3 In the equation, F represents the metering point. The metering data items include the three-phase voltage, three-phase current, total active power, node carbon potential and output carbon flow rate at each metering point. F1, F2, F3...Fm are the metering points at the main power supply switch of the substation. Fm+1, Fm+2, Fm+3, Fm+4, Fm+5 and Fm+6 are the metering points at the branch power supply switch of the power supply station busbar. The carbon potential E of the power supply station busbar Li and Lj is defined as GDS ,Right now The unit is kgCO2 / kWh, corresponding to the carbon potential at each metering point. Bus Li is the AC bus, and bus Lj is the DC bus. Since each substation is located at the power supply station, the carbon potential at the low-voltage node in each substation is the same, e1, in kgCO2 / kWh.

[0082] For example, when there is excess renewable energy generation, the AC busbar loss carbon flow rate is calculated as follows:

[0083]

[0084] Where ΔP Total-AC is the total power loss at the AC bus, P SJDW is the total power output of the upper power grid,

[0085] P GDS is the AC load power (branch 2), P CDZ is the charging pile power (branch 1), P HL is the AC / DC bus interconnection branch power (branch 3), ΔP L-AC is the power loss borne by the AC bus, in kW. α is the sharing coefficient. R L-AC E is the carbon loss rate at the AC bus, in kgCO2 / h. L-AC is the carbon potential of the AC bus, in kgCO2 / kWh.

[0086] In an optional embodiment, the AC bus loss carbon flow rate can also be obtained by constructing an equivalent circuit model. The AC bus system of the zero-carbon power supply station is equivalent to a circuit model containing components such as resistance and inductance; according to circuit theory, combined with the parameters of each component in the power supply related data and real-time measurement data such as current and voltage, the power loss in the AC bus system is calculated. By analyzing the power loss of different parts in the equivalent circuit, the power loss borne by the AC bus is determined. According to the carbon potential of the AC bus, the AC bus loss carbon flow rate is calculated using the formula.

[0087] In the embodiment of the present invention, the total power loss of the DC bus is calculated based on the power supply related data, the power loss borne by the DC bus is determined in combination with the power loss borne by the AC bus, and then multiplied by the carbon potential of the AC bus to obtain the DC loss carbon flow rate;

[0088] For example, when the power generation of renewable energy is insufficient, the DC bus loss carbon flow rate is calculated as follows:

[0089]

[0090] Where ΔP Total-DC is the total power loss at the DC bus, P DG is the distributed generation power (branch 5), P WWis the DC load power (branch 6), P CN is the energy storage power (branch 4), ΔP L-DC The power loss at the AC busbar is in kW. L-DC E is the carbon loss rate at the DC bus, in kgCO2 / h. L-DC is the carbon potential of the AC bus, in kgCO2 / kWh.

[0091] For example, when there is excess renewable energy generation, the DC bus loss carbon flow rate is calculated as follows:

[0092]

[0093] Where ΔP Total-DC is the total power loss at the DC bus, P DG is the distributed generation power (branch 5), P WW is the DC load power (branch 6), P CN is the energy storage power (branch 4), ΔP L-DC The power loss at the AC busbar is in kW. L-DC E is the carbon loss rate at the DC bus, in kgCO2 / h. L-DC is the carbon potential of the AC bus, in kgCO2 / kWh.

[0094] In an optional implementation, the DC bus loss carbon flow rate can be obtained through energy flow analysis, allowing energy flow analysis of the DC bus system of a zero-carbon power supply station to be performed. Power supply-related data, including distributed generation power, DC load power, and energy storage power, combined with the law of conservation of energy, is used to analyze the energy input, output, and loss in the DC bus system. By establishing an energy flow model, the power loss borne by the DC bus can be accurately calculated. The DC bus loss carbon flow rate is then calculated based on the carbon potential of the AC bus.

[0095] In the embodiment of the present invention, each branch shares the total bus power loss according to its power ratio, and then multiplies it by the bus carbon potential to obtain the carbon flow rate of each branch loss;

[0096] For example, when the renewable energy generation capacity is insufficient, the loss carbon flow rate calculation formula of branch a (a=1, 2, 3) is:

[0097]

[0098] Where ΔP Total-AC is the total power loss at the AC bus, ΔP ZL-a is the power loss borne by branch a (a=1,2,3), P ZL-a is the power of branch a (a=1,2,3), the unit is kW.ZL-a It is the carbon loss rate at branch a (a=1, 2, 3), unit is kgCO2 / h.

[0099] For example, when the renewable energy generation capacity is insufficient, the loss carbon flow rate calculation formula of branch a (a=4,6) is:

[0100]

[0101] Where ΔP Total-DC is the total power loss at the DC bus, ΔP ZL-a is the power loss borne by branch a (a=4,6), P ZL-a is the power of branch a (a=4,6), in kW. ZL-a It is the carbon loss rate at branch a (a=4,6), unit is kgCO2 / h.

[0102] For example, when there is excess renewable energy generation, the loss carbon flow rate calculation formula of branch a (a=1,2) is:

[0103]

[0104] Where ΔP ZL-a is the power loss borne by branch a (a=1,2), P ZL-a is the power of branch a (a=1,2), in kW. ZL-a It is the carbon loss rate at branch a (a=1,2), unit is kgCO2 / h.

[0105] For example, when there is excess renewable energy generation, the carbon loss rate calculation formula for branch a (a=3, 4, 6) is:

[0106]

[0107] Where ΔP ZL-a is the power loss borne by branch a (a=3,4,6), P ZL-a is the power of branch a (a=3,4,6), in kW. ZL-a It is the carbon loss rate at branch a (a=3, 4, 6), unit is kgCO2 / h.

[0108] In an optional embodiment, the branch loss carbon flow rate can also be obtained by optimizing the allocation ratio through an intelligent algorithm, and the proportion of each branch's allocation of the total bus loss power according to the power ratio can be optimized by using a genetic algorithm, a particle swarm optimization algorithm, etc. The traditional allocation method based on power ratio may not be able to fully and accurately reflect the actual contribution of each branch to the bus loss. Through an intelligent algorithm, the allocation ratio is optimized and adjusted with the goal of minimizing the error between the calculated result of the branch loss carbon flow rate and the actual carbon emission monitoring data. The loss power borne by each branch is calculated based on the optimized allocation ratio, and then combined with the bus carbon potential to obtain a more accurate branch loss carbon flow rate.

[0109] It should be noted that the loss carbon flow rate refers to the carbon flow rate corresponding to the active power loss shared by the load and busbar. This invention calculates the loss carbon flow rate to allocate losses at the power station busbar, allocating a portion of the losses to the busbar and a portion to the individual loads connected to the busbar. This loss allocation calculation clearly defines the losses of the power station's AC and DC loads, providing optimization guidance for subsequent energy-saving and carbon-reduction measures.

[0110] In the embodiment of the present invention, step S106 calculates the carbon loss flow rate of the zero-carbon power station based on the branch power and the carbon potential of the bus to which the branch belongs, in combination with the renewable energy power generation scenario, including the following steps C1-C2:

[0111] C1: If the branch carbon flow rate and loss carbon flow rate exceed the set threshold, the area where the branch is located will be marked as a high carbon emission area;

[0112] C2: Analyze high-carbon emission areas and formulate differentiated energy allocation strategies based on the analysis results.

[0113] Specifically, when analyzing high-carbon emission areas, analyze the functions and power consumption characteristics of each branch. If the cause is an AC load branch, determine the load type, evaluate the energy efficiency of the equipment, and consider equipment upgrades or optimizing usage time to reduce carbon emissions. If the loss carbon flow rate is excessively high, check the busbar and branch connections and analyze whether the power transmission path is reasonable.

[0114] Based on the analysis results, differentiated energy allocation strategies are developed. If renewable energy generation is insufficient, priority is given to allocating power from energy storage or adjusting power distribution from the upstream power grid to ensure clean energy supply. If equipment consumption is high, operating parameters are adjusted through intelligent control systems. If losses are significant, consideration is given to renovating the busbar with low-loss materials, optimizing the layout, or rationally adjusting branch power distribution to achieve effective governance and rational energy allocation in high-carbon emission areas.

[0115] Example 3, reference Figure 4Tables 1 to 4 are an embodiment of the present invention. Based on the above embodiment, a method for calculating the carbon flow rate of a zero-carbon power supply is provided, which is scientifically demonstrated through experiments.

[0116] The specific structure of a power supply station is as follows Figure 4 As shown, Figure 4 The AC loads on floors 1 to 5 of the central power station are connected to the AC380V busbar. When the distributed power output is insufficient to maintain the power station's load supply, the upper-level power grid discharges energy to the AC380V busbar of the power station through the XP power station's charging pile transformer.

[0117] The power station's microgrid structure includes rooftop photovoltaics, carport photovoltaics, wind turbines, energy storage, and bidirectional charging stations. All devices within the microgrid are connected to the DC750V busbar. The power station's DC loads, such as air conditioners and lighting, are connected to the DC220V busbar. The AC380V busbar is connected to the DC750V busbar via a flexible bidirectional converter. The DC750V busbar is connected to the DC220V busbar via a DC / DC converter. Because power measurement devices are not currently installed at the branch where the bidirectional charging column is located and at the node where the upper power grid disconnects power to the power station's DC750V busbar via the XX upper power transformer, the impact of the power flow of the bidirectional charging column and the power delivered to the power station's DC750V busbar via the XX upper power transformer on subsequent calculations are not considered.

[0118] We selected a typical workday at the XP power station and calculated the hourly power consumption of each device at hourly intervals. We then calculated losses and branch carbon flow rates at corresponding moments for two different scenarios: insufficient and excessive renewable energy generation. We set the loss allocation coefficient a to 0.5.

[0119] For the scenario where the renewable energy power generation is insufficient, such as Figure 2 As shown in Figure 1, the power flowing through the flexible bidirectional converter is negative, indicating insufficient renewable energy generation in the microgrid. Therefore, 5:00 AM meets Scenario 1. The calculated branch carbon flow rate and loss carbon flow rate at this time are shown in Tables 1 and 2.

[0120] Table 1 Calculation results of branch carbon flow rate at 5 am

[0121]

[0122] Table 2 Calculation results of carbon loss flow rate at 5 am

[0123]

[0124]

[0125] Tables 1 and 2 show that under insufficient renewable energy generation, the branch carbon flow rate of the XP power station charging pile transformer is relatively high, reaching 1.717 kgCO₂ / h. This indicates that the upstream power grid contributes significantly to carbon emissions. Furthermore, the flexible bidirectional converter between the AC380V busbar and the DC750V busbar also exhibits a certain branch carbon flow rate (0.694 kgCO₂ / h), indicating that this equipment also generates certain carbon emissions during power transmission. Regarding the loss carbon flow rate, the AC380V and DC750V busbars bear relatively high loss carbon flow rates of 0.258 kgCO₂ / h and 0.269 kgCO₂ / h, respectively. This indicates that the busbars experience significant power losses during power transmission, leading to higher carbon emissions. Future efforts should focus on optimizing the busbar's transmission efficiency. Furthermore, AC and DC loads at each level also contribute to the loss carbon flow rate, reflecting the combined impact of various components of the power supply system on carbon emissions.

[0126] For the scenario of excess renewable energy generation, such as Figure 3 As shown, the power flowing through the flexible bidirectional converter is positive, indicating excess renewable energy generation in the microgrid at this time. Therefore, 12:00 noon meets Scenario 2. The calculated branch carbon flow rate and loss carbon flow rate at this time are shown in Tables 3 and 4.

[0127] Table 3 Calculation results of branch carbon flow rate at 12 noon

[0128]

[0129]

[0130] Table 4 Calculation results of carbon loss flow rate at 12 noon

[0131]

[0132] Tables 3 and 4 show that in the scenario of excess renewable energy generation, the branch carbon flow rate of the four-layer AC load is the highest, reaching 4.166 kgCO₂ / h. The branch carbon flow rate of the XP power station charging pile transformer is also relatively high, at 5.132 kgCO₂ / h, indicating that these two components have high power in this scenario and correspondingly significant carbon emissions. Notably, the branch carbon flow rate of the energy storage device is 0, indicating that during the period of excess renewable energy generation, the energy storage device may be fully charged or not participating in power transmission. In terms of loss carbon flow rate, the AC380V bus has a higher loss carbon flow rate (1.382kgCO2 / h), while the DC750V bus, total DC load, DC lighting load, DC220V bus, flexible bidirectional converter between the AC380V bus and DC750V bus, and energy storage equipment have a loss carbon flow rate of 0. This is related to the power distribution and transmission characteristics when renewable energy power generation is in excess. At this time, reasonable power allocation may be used to effectively control the power loss of some equipment and reduce the corresponding carbon emissions.

[0133] Example 4. The above is a schematic scheme of a method for calculating the carbon flow rate of a zero-carbon power supply. It should be noted that the technical scheme of the system for calculating the carbon flow rate of a zero-carbon power supply is based on the same concept as the technical scheme of the method for calculating the carbon flow rate of a zero-carbon power supply. For details not described in detail in the technical scheme of the system for calculating the carbon flow rate of a zero-carbon power supply in this embodiment, please refer to the description of the technical scheme of the method for calculating the carbon flow rate of a zero-carbon power supply.

[0134] This embodiment also provides a system for calculating the carbon flow rate of a zero-carbon power supply, including:

[0135] A data acquisition module, used to acquire power supply related data;

[0136] A primary calculation module is used to obtain branch power based on power supply related data;

[0137] The secondary calculation module is used to calculate the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the busbar to which the branch belongs; and calculate the loss carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the busbar to which the branch belongs, combined with the renewable energy power generation scenario;

[0138] The identification and optimization module is used to identify high-carbon emission areas based on branch carbon flow rate and loss carbon flow rate, and optimize the energy distribution strategy of zero-carbon power supply stations.

[0139] This embodiment also provides an electronic device suitable for calculating the carbon flow rate of a zero-carbon power supply, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method for calculating the carbon flow rate of a zero-carbon power supply as proposed in the above embodiment.

[0140] This embodiment further provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for calculating the carbon flow rate of a zero-carbon power supply as proposed in the above embodiment.

[0141] The storage medium proposed in this embodiment and the method for calculating the carbon flow rate of a zero-carbon power supply proposed in the above embodiment belong to the same inventive concept. For technical details not described in detail in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0142] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general hardware, and of course can also be implemented by hardware. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0143] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for calculating the carbon flow rate of a zero-carbon power supply, characterized in that: include: Acquire power supply related data, and acquire branch power according to the power supply related data; Calculating the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the busbar to which the branch belongs; Based on the branch power and the carbon potential of the busbar to which the branch belongs, and in combination with the renewable energy power generation scenario, the loss carbon flow rate of the zero-carbon power station is calculated; Based on the branch carbon flow rate and loss carbon flow rate, high carbon emission areas are identified and the energy distribution strategy of the zero-carbon power supply station is optimized.

2. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 1, wherein: Based on the branch power and the carbon potential of the bus to which the branch belongs, the branch carbon flow rate of the zero-carbon power supply station is calculated, including: According to the branch type, obtain the carbon potential of the busbar to which the branch belongs; Calculate the product of the branch power and the carbon potential of the bus to which the branch belongs to obtain the branch carbon flow rate.

3. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 2, wherein: Calculate the carbon loss rate of a zero-carbon power station based on the renewable energy power generation scenario, including: Renewable energy generation scenarios include insufficient and excessive renewable energy generation; The carbon flow rate of AC bus loss, the carbon flow rate of DC bus loss and the carbon flow rate of branch loss are calculated respectively when the renewable energy power generation is insufficient and when the renewable energy power generation is excessive.

4. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 3, wherein: Calculate the AC bus loss carbon flow rate, DC bus loss carbon flow rate, and branch loss carbon flow rate when renewable energy power generation is insufficient or excessive, including: Based on the power supply related data, the total AC bus power loss is calculated, and the allocation coefficient is introduced to calculate the AC bus power loss, which is then multiplied by the AC bus carbon potential to obtain the AC bus loss carbon flow rate; Calculate the total power loss of the DC bus based on the power supply related data, determine the power loss borne by the DC bus in combination with the power loss borne by the AC bus, and then multiply it by the carbon potential of the AC bus to obtain the DC loss carbon flow rate; Each branch shares the total bus power loss according to its power ratio, and then multiplies it by the bus carbon potential to obtain the carbon loss flow rate of each branch.

5. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 4, wherein: Based on the branch carbon flow rate and loss carbon flow rate, high carbon emission areas are identified and the energy allocation strategy of the zero-carbon power supply station is optimized, including: If the branch carbon flow rate and loss carbon flow rate exceed the set threshold, the area where the branch is located is marked as a high carbon emission area; Analyze the high carbon emission areas and formulate differentiated energy allocation strategies based on the analysis results.

6. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 2, wherein: According to the branch type, obtain the carbon potential of the busbar to which the branch belongs, including: If the branch is an AC load, the carbon potential of the branch power is the carbon potential of the AC bus; If the branch is a DC load, the carbon potential of the branch power is the carbon potential of the DC bus.

7. The method for calculating the carbon flow rate of a zero-carbon power supply according to claim 6, wherein: Also includes: If the AC bus injects power into the DC bus, the carbon potential of the injected power is the carbon potential of the AC bus; If the DC bus injects power into the AC bus, the carbon potential of the injected power is the carbon potential of the DC bus.

8. A system for calculating the carbon flow rate of a zero-carbon power supply, applying the method according to any one of claims 1 to 7, characterized in that: include: A data acquisition module, used to acquire power supply related data; A primary calculation module, used to obtain branch power according to the power supply related data; A secondary calculation module is used to calculate the branch carbon flow rate of the zero-carbon power supply station based on the branch power and the carbon potential of the bus to which the branch belongs; based on the branch power and the carbon potential of the bus to which the branch belongs, and in combination with the new energy power generation scenario, calculate the loss carbon flow rate of the zero-carbon power supply station; The identification and optimization module is used to identify high-carbon emission areas based on the branch carbon flow rate and loss carbon flow rate, and optimize the energy distribution strategy of the zero-carbon power supply station.

9. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for calculating the carbon flow rate of a zero-carbon power supply station as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for calculating the carbon flow rate of a zero-carbon power supply according to any one of claims 1 to 7.

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