A device reconstruction selection method and terminal based on low-carbon economy

Abstract

The application discloses a kind of equipment reconstruction selection method and terminal based on low-carbon economy, obtains the physical regional boundary of the power system where the target equipment to be reconstructed is located;The low-carbon economy evaluation index of the target equipment to be reconstructed and the limit value of low-carbon economy evaluation index are obtained;Remove the alternative equipment that does not meet the limit value requirement of low-carbon economy evaluation index;According to the low-carbon economy evaluation index, the alternative equipment is sorted, and the equipment in the front of sorting is used as the optimal alternative equipment;The operation simulation of power system is carried out on the power system after replacing the best alternative equipment;According to the simulation result, it is judged whether the best alternative equipment meets the carbon emission economy reconstruction requirement, if yes, the best alternative equipment is output, otherwise the best alternative equipment is removed from the alternative equipment and then selected again.The optimization result of equipment selection carbon emission economy before and after power flow simulation is ensured, and the optimal alternative power equipment is selected for power reconstruction personnel to refer.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission neutralization, and in particular to a method and terminal for equipment modification and selection based on low-carbon economy. Background Art

[0002] In order to achieve the medium- and long-term goals of carbon peak and carbon neutrality, the market has accelerated the optimization of energy structure, strictly controlled fossil energy consumption, and actively promoted the development of clean energy such as wind power and photovoltaics. Low carbon refers to lower (lower) greenhouse gas (mainly carbon dioxide) emissions. The connotation of low carbon is: low-carbon society, low-carbon economy, low-carbon production, low-carbon consumption, low-carbon life, low-carbon city, low-carbon community, low-carbon family, low-carbon tourism, low-carbon culture, etc. The core content is low-carbon life and low-carbon economy.

[0003] However, due to the regional energy characteristics and the traditional structure of the power system under the current market background, traditional energy power generation still accounts for a relatively high proportion. As the power industry is the industry with the largest carbon dioxide emissions, with the market's demand for carbon neutrality and the development of a low-carbon economy, the transformation of the existing power system is also an important issue at present. The update of power system equipment requires corresponding procurement costs, manufacturing energy consumption and environmental pollution costs. Only by effectively selecting power system equipment and reducing manufacturing energy consumption and environmental pollution costs can we meet both economic requirements and achieve low-carbon development of the power grid.

[0004] However, there is no good method in the prior art for selecting the power equipment to obtain the best power equipment. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and terminal for equipment transformation selection based on low-carbon economy, which can select the best alternative power equipment for reference by power transformation personnel.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for selecting equipment for transformation based on low-carbon economy comprises the following steps:

[0008] S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located;

[0009] S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed;

[0010] S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements;

[0011] S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment;

[0012] S5. Conducting an operation simulation of the power system after replacing the optimal alternative equipment;

[0013] S6. Determine whether the optimal candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the optimal candidate device. Otherwise, remove the optimal candidate device from the candidate devices and re-execute steps S4-S6.

[0014] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0015] A low-carbon economy-based equipment modification and selection terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0016] S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located;

[0017] S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed;

[0018] S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements;

[0019] S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment;

[0020] S5. Conducting an operation simulation of the power system after replacing the best alternative equipment;

[0021] S6. Determine whether the best candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the best candidate device. Otherwise, remove the best candidate device from the candidate devices and re-execute steps S4-S6.

[0022] The beneficial effects of the present invention are: a method and terminal for equipment transformation and selection based on low-carbon economy, which ranks all alternative equipment by calculating the low-carbon economy evaluation index of each alternative equipment, and after the simulation flow calculation is completed, the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions is judged based on the simulation data. When the carbon emission benefit evaluation value is poor, the remaining alternative equipment is subjected to cyclic iterative judgment to seek the alternative equipment with the best carbon emission benefit. This cyclic iterative judgment and the aforementioned multi-index factors jointly ensure the optimization result of the carbon emission economy of equipment selection before and after the flow simulation, and select the best alternative power equipment for reference by power transformation personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of a process for selecting equipment for transformation based on low-carbon economy according to an embodiment of the present invention;

[0024] Figure 2 This is a structural schematic diagram of an equipment modification and selection terminal based on low-carbon economy in an embodiment of the present invention.

[0025] Description of labels:

[0026] 1. A terminal for selecting equipment for retrofitting based on low-carbon economy; 2. Processor; 3. Memory. DETAILED DESCRIPTION

[0027] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0028] Please refer to Figure 1 , a method for selecting equipment for transformation based on low-carbon economy, comprising the steps of:

[0029] S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located;

[0030] S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed;

[0031] S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements;

[0032] S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment;

[0033] S5. Conducting an operation simulation of the power system after replacing the best alternative equipment;

[0034] S6. Determine whether the best candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the best candidate device. Otherwise, remove the best candidate device from the candidate devices and re-execute steps S4-S6.

[0035] From the above description, it can be seen that the beneficial effects of the present invention are: a method and terminal for equipment transformation and selection based on low-carbon economy, which ranks all alternative equipment by calculating the low-carbon economy evaluation index of each alternative equipment, and after the simulation flow calculation is completed, the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions is judged based on the simulation data. When the carbon emission benefit evaluation value is poor, the remaining alternative equipment is subjected to cyclic iterative judgment to seek the alternative equipment with the best carbon emission benefit. This cyclic iterative judgment and the aforementioned multi-index factors jointly ensure the optimization result of the carbon emission economy of equipment selection before and after the flow simulation, and select the best alternative power equipment for reference by power transformation personnel.

[0036] Furthermore, the economic evaluation indicators include one or more of the transformation cost, transformation cycle, carbon emission difference before and after transformation, carbon emission trading cost corresponding to the carbon emission difference, and unit energy conversion efficiency difference after and before transformation.

[0037] From the above description, it can be seen that the equipment selection is carried out accordingly using multiple index factors such as the transformation cost E, the transformation period T, the carbon emission difference ΔC before and after the transformation, the carbon emission trading cost β corresponding to the carbon emission difference ΔC in the carbon emission market, and the unit energy conversion efficiency difference Δε after and before the transformation. The equipment selection is quickly screened and optimized from multiple different dimensions to ensure that the selection plan complies with the principles of a low-carbon economy.

[0038] Furthermore, the low-carbon economy evaluation index θ is calculated according to the following formula:

[0039]

[0040] Where E is the transformation cost, T is the transformation period, ΔC is the difference in carbon emissions before and after the transformation, β is the carbon emission trading cost corresponding to the carbon emission difference ΔC in the carbon emission market, and Δε is the difference in unit energy conversion efficiency after and before the transformation.

[0041] From the above description, it can be seen that a specific calculation scheme for the low-carbon economy evaluation index θ is given.

[0042] Furthermore, the operation simulation of the power system includes user-side load fluctuation prediction simulation, power generation side output regulation simulation and power system flow calculation simulation.

[0043] From the above description, it can be seen that the power system status after equipment replacement can be predicted based on the simulation calculation results.

[0044] Furthermore, the carbon emission economic transformation requirement specifically requires that the carbon emission benefit evaluation value Z be less than 0, and the carbon emission benefit evaluation value Z is calculated according to the following formula:

[0045]

[0046] Where μ is the carbon emissions of the best alternative equipment under steady-state simulation based on power system flow calculations, D is the transformation cost of the best alternative equipment, ΔC is the difference in carbon emissions before and after the transformation, and β is the carbon emission trading cost corresponding to the carbon emission difference ΔC in the carbon emission market.

[0047] From the above description, it can be seen that the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions is judged based on the simulation data. When the carbon emission benefit evaluation value is poor, the remaining alternative equipment is judged iteratively to find the alternative equipment with the best carbon emission benefit.

[0048] A low-carbon economy-based equipment modification and selection terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0049] S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located;

[0050] S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed;

[0051] S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements;

[0052] S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment;

[0053] S5. Conducting an operation simulation of the power system after replacing the best alternative equipment;

[0054] S6. Determine whether the best candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the best candidate device. Otherwise, remove the best candidate device from the candidate devices and re-execute steps S4-S6.

[0055] From the above description, it can be seen that the beneficial effects of the present invention are: a method and terminal for equipment transformation and selection based on low-carbon economy, which ranks all alternative equipment by calculating the low-carbon economy evaluation index of each alternative equipment, and after the simulation flow calculation is completed, the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions is judged based on the simulation data. When the carbon emission benefit evaluation value is poor, the remaining alternative equipment is subjected to cyclic iterative judgment to seek the alternative equipment with the best carbon emission benefit. This cyclic iterative judgment and the aforementioned multi-index factors jointly ensure the optimization result of the carbon emission economy of equipment selection before and after the flow simulation, and select the best alternative power equipment for reference by power transformation personnel.

[0056] Furthermore, the economic evaluation indicators include one or more of the transformation cost, transformation cycle, carbon emission difference before and after transformation, carbon emission trading cost corresponding to the carbon emission difference, and unit energy conversion efficiency difference after and before transformation.

[0057] From the above description, it can be seen that the equipment selection is carried out accordingly using multiple index factors such as the transformation cost E, the transformation period T, the carbon emission difference ΔC before and after the transformation, the carbon emission trading cost β corresponding to the carbon emission difference ΔC in the carbon emission market, and the unit energy conversion efficiency difference Δε after and before the transformation. The equipment selection is quickly screened and optimized from multiple different dimensions to ensure that the selection plan complies with the principles of a low-carbon economy.

[0058] Furthermore, the low-carbon economy evaluation index θ is calculated according to the following formula:

[0059]

[0060] Where E is the transformation cost, T is the transformation period, ΔC is the difference in carbon emissions before and after the transformation, β is the carbon emission trading cost corresponding to the carbon emission difference ΔC in the carbon emission market, and Δε is the difference in unit energy conversion efficiency after and before the transformation.

[0061] From the above description, it can be seen that a specific calculation scheme for the low-carbon economy evaluation index θ is given.

[0062] Furthermore, the operation simulation of the power system includes user-side load fluctuation prediction simulation, power generation side output regulation simulation and power system flow calculation simulation.

[0063] From the above description, it can be seen that the power system status after equipment replacement can be predicted based on the simulation calculation results.

[0064] Furthermore, the carbon emission economic transformation requirement specifically requires that the carbon emission benefit evaluation value Z be less than 0, and the carbon emission benefit evaluation value Z is calculated according to the following formula:

[0065]

[0066] Where μ is the carbon emissions of the best alternative equipment under steady-state simulation based on power system flow calculations, D is the transformation cost of the best alternative equipment, ΔC is the difference in carbon emissions before and after the transformation, and β is the carbon emission trading cost corresponding to the carbon emission difference ΔC in the carbon emission market.

[0067] From the above description, it can be seen that the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions is judged based on the simulation data. When the carbon emission benefit evaluation value is poor, the remaining alternative equipment is judged iteratively to find the alternative equipment with the best carbon emission benefit.

[0068] The present invention is used in power system transformation to select alternative power equipment.

[0069] Please refer to Figure 1 , embodiment 1 of the present invention is:

[0070] A method for selecting equipment for transformation based on low-carbon economy includes the following steps:

[0071] S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located.

[0072] S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limit values ​​of the target equipment to be transformed.

[0073] The low-carbon economy index θ is composed of the following factors:

[0074] Renovation cost E;

[0075] Transformation cycle T;

[0076] The difference in carbon emissions before and after the renovation, ΔC;

[0077] The carbon emission transaction cost β corresponding to the carbon emission difference ΔC in the carbon emission market;

[0078] The difference in unit energy conversion efficiency Δε between before and after the transformation.

[0079] S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements.

[0080] Before determining the target equipment for improvement, set corresponding limit ranges for the transformation cost E, transformation period T, carbon emission difference ΔC before and after transformation, and energy conversion efficiency difference Δε. Alternative equipment that does not meet the limit range does not meet the carbon emission transformation requirements. For example, if the transformation period limit of the target equipment is 15 days, if there is an alternative equipment A that can significantly reduce carbon emissions, but its transformation period exceeds 15 days, then the alternative equipment A cannot meet the low-carbon economic equipment transformation selection requirements;

[0081] For example, if alternative equipment B is selected, the energy conversion efficiency will be greatly improved after the transformation compared with before the transformation. However, if the difference in carbon emissions before and after the transformation does not fall within the limit, it means that the carbon emission transformation effect of alternative equipment B does not meet the requirements.

[0082] S4. Sort the alternative equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal alternative equipment.

[0083] According to the above limit range, after excluding the backup equipment that obviously does not meet the requirements, the low-carbon economic evaluation index θ of each backup equipment can be calculated:

[0084]

[0085] The candidate devices are arranged in descending order according to the value of θ, and the candidate device corresponding to the maximum value of θ is set as the optimal candidate device, followed by the suboptimal candidate device, and so on.

[0086] S5. Conduct operation simulation of the power system after replacing the optimal alternative equipment.

[0087] The operation simulation of the power system includes user-side load fluctuation prediction simulation, power generation side output regulation simulation and power system flow calculation simulation.

[0088] The user-side load fluctuation prediction simulation is to simulate the fluctuation of user load in a future time period. The load simulation can be based on the historical data of user-side load fluctuation within the boundary, and use interpolation fitting or linear regression iterative convergence for prediction. The historical data can be multi-dimensional data, which can be the corresponding curve of historical user load and temperature, or the corresponding curve of historical user load and each time period of the day, or a three-dimensional curve. The Z-axis is the historical user load, the X-axis is the each time period of the day, and the Y-axis is the full load rate of each power supply node. After obtaining the curves corresponding to these historical data, the temperature, time period or predicted load rate of each power supply node to be simulated in the future period are substituted into these curves, and the corresponding expected user load value is obtained by interpolation or linear regression iteration as a series of load simulation data, and drawn into the user-side load fluctuation prediction simulation curve F.

[0089] The power generation side output regulation simulation is based on the user-side fluctuation prediction simulation curve, with the ratio of carbon emissions to energy consumption of the optimal candidate equipment being the optimization target. The optimal candidate equipment and other on-grid equipment combinations within a unit time (such as a day, a week, a month, or other scheduling period) are introduced. The optimal combination is selected based on the power system constraints or the small disturbance stability analysis-based eigenvalue analysis of the equipment combination operation simulation within a unit time.

[0090] The constraints include: peak load constraints of each unit on the grid, voltage and reactive power constraints of each unit during operation, and network line loss constraints.

[0091] In one embodiment, the ratio of carbon emissions to energy consumption of the optimal candidate device is optimized, and the optimal combination selection operation is performed by introducing the combination of the optimal candidate device and other devices on the network within a unit time (such as a day, a week, a month, or other scheduling period) as follows:

[0092] Assuming that the unit time is T, the optimization goal of the combination of the best candidate device and other devices on the network is as follows:

[0093]

[0094] Among them, C b (t) is the predicted carbon emission value of the alternative equipment at time t, which can be obtained by querying the load / emission curve set when the alternative equipment leaves the factory based on the power borne by the alternative equipment in the user-side load fluctuation prediction simulation curve. b (t) Yes, P b (t) is the power value of the alternative equipment at time t, F(t) is the power value at time t on the user-side load fluctuation prediction simulation curve, and C r (t) is the predicted value of carbon emissions of other network devices at time t. The carbon emissions C can be obtained by establishing a corresponding relationship between carbon emission monitoring values ​​and load power in the past historical data of other network devices, and based on the power borne by other network devices in the user-side load fluctuation prediction simulation curve. r (t), P r (t) is the power value of other devices in the network at time t.

[0095] Among them, the power system flow calculation simulation is to use the PQ decomposition method to solve the nonlinear Jacobian matrix under the assumption that the power system network conditions at the current point remain unchanged, express the power of each node in the network as the polar coordinate form of the voltage vector, use the active power error as the basis for correcting the voltage vector angle, and use the reactive power error as the basis for correcting the voltage amplitude. Active and reactive power are selected separately to achieve rapid convergence of the flow calculation.

[0096] S6. Determine whether the optimal candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the optimal candidate device. Otherwise, remove the optimal candidate device from the candidate devices and re-execute steps S4-S6.

[0097] Based on the results of the tidal flow calculation, the ratio of the energy consumption rate to the carbon emission value of the optimal alternative equipment under the current simulation conditions is calculated and compared with the ratio of the energy consumption rate to the carbon emission value of the original equipment before the transformation to see whether the optimal alternative equipment under the simulation conditions can meet the carbon emission economic transformation requirements.

[0098] Divide the carbon emission μ by the transformation cost D of the optimal alternative equipment, and compare it with the ratio of the carbon emission difference ΔC to the carbon emission transaction cost β in step S2,

[0099] Right now:

[0100]

[0101] Among them, Z is the carbon emission benefit evaluation value. If Z is less than 0, it is determined that the selection of the optimal alternative equipment is correct, and the optimal alternative equipment is determined as the selection result; if Z is greater than or equal to 0, it means that the selection economy of the optimal alternative equipment is poor. After removing the optimal alternative equipment from the alternative equipment, steps S4-S6 are re-executed, that is, the suboptimal alternative equipment is used instead of the aforementioned optimal alternative equipment for flow calculation, and steps S5 and S6 are completed. The Z value is calculated based on the suboptimal alternative equipment until Z is less than 0, and the optimal alternative equipment is output. If the Z value is still greater than or equal to 0, the remaining alternative equipment is traversed.

[0102] Afterwards, the power system personnel can replace the original equipment based on the optimal alternative equipment obtained by the above method to complete the transformation and selection of the power system equipment.

[0103] Please refer to Figure 2 , the second embodiment of the present invention is:

[0104] A low-carbon economy-based equipment modification and selection terminal 1 includes a memory 3, a processor 2, and a computer program stored in the memory 3 and executable on the processor 2. When the processor 2 executes the computer program, the steps of the above-mentioned embodiment 1 are implemented.

[0105] In summary, the present invention provides a method and terminal for equipment transformation and selection based on low-carbon economy, which ranks all alternative equipment by calculating the low-carbon economy evaluation index of each alternative equipment, and after the simulation flow calculation is completed, judges the carbon emission benefit evaluation value of the equipment to be selected under steady-state operating conditions based on the simulation data. When the carbon emission benefit evaluation value is poor, a cyclic iterative judgment is performed on the remaining alternative equipment to seek the alternative equipment with the best carbon emission benefit. This cyclic iterative judgment and the aforementioned multi-index factors jointly ensure the optimization result of the carbon emission economy of equipment selection before and after the flow simulation, and selects the best alternative power equipment for reference by power transformation personnel.

[0106] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for selecting equipment for transformation based on low-carbon economy, characterized in that: Including steps: S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located; S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed; S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements; S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment; S5. Conducting an operation simulation of the power system after replacing the optimal alternative equipment; S6. Determine whether the optimal candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the optimal candidate device. Otherwise, remove the optimal candidate device from the candidate devices and re-execute steps S4-S6. The low-carbon economy evaluation indicators include the transformation cost, transformation period, the difference in carbon emissions before and after the transformation, the carbon emission trading cost corresponding to the carbon emission difference, and the difference in unit energy conversion efficiency after and before the transformation; The low-carbon economy evaluation index is calculated according to the following formula : ； Where, E is the transformation cost, T is the transformation period, is the difference in carbon emissions before and after the transformation. is the carbon emissions difference, is the corresponding carbon emission transaction cost in the carbon emission market, It is the difference in unit energy conversion efficiency between before and after the transformation.

2. The method for selecting equipment for transformation based on low-carbon economy according to claim 1, characterized in that: The operation simulation of the power system includes user-side load fluctuation prediction simulation, power generation side output regulation simulation and power system flow calculation simulation.

3. The method for selecting equipment for transformation based on low-carbon economy according to claim 2, characterized in that: The carbon emission economic transformation requirement is specifically that the carbon emission benefit evaluation value Z is less than 0, and the carbon emission benefit evaluation value Z is calculated according to the following formula: ； Where, is the carbon emission of the optimal alternative equipment under steady-state simulation based on the power system flow calculation, D is the transformation cost of the optimal alternative equipment, It is the difference in carbon emissions before and after the transformation.

4. A low-carbon economy-based equipment modification and selection terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: S1. Obtain the physical geographical boundaries of the power system where the target equipment to be transformed is located; S2. Obtain low-carbon economic evaluation indicators and low-carbon economic evaluation indicator limits for the target equipment to be transformed; S3. Eliminate the alternative equipment that does not meet the low-carbon economy evaluation index limit requirements; S4. Sort the candidate equipment according to the low-carbon economy evaluation index, and take the equipment with the highest ranking as the optimal candidate equipment; S5. Conducting an operation simulation of the power system after replacing the optimal alternative equipment; S6. Determine whether the optimal candidate device meets the carbon emission economic transformation requirements based on the simulation results. If so, output the optimal candidate device. Otherwise, remove the optimal candidate device from the candidate devices and re-execute steps S4-S6. The low-carbon economy evaluation indicators include the transformation cost, transformation period, the difference in carbon emissions before and after the transformation, the carbon emission trading cost corresponding to the carbon emission difference, and the difference in unit energy conversion efficiency after and before the transformation; The low-carbon economy evaluation index is calculated according to the following formula : ； Where, E is the transformation cost, T is the transformation period, is the difference in carbon emissions before and after the transformation. is the carbon emissions difference, is the corresponding carbon emission transaction cost in the carbon emission market, It is the difference in unit energy conversion efficiency between before and after the transformation.

5. The low-carbon economy-based equipment transformation and selection terminal according to claim 4, characterized in that: The operation simulation of the power system includes user-side load fluctuation prediction simulation, power generation side output regulation simulation and power system flow calculation simulation.

6. The low-carbon economy-based equipment transformation and selection terminal according to claim 5, characterized in that: The carbon emission economic transformation requirement is specifically that the carbon emission benefit evaluation value Z is less than 0, and the carbon emission benefit evaluation value Z is calculated according to the following formula: ； Where, is the carbon emission of the optimal alternative equipment under steady-state simulation based on the power system flow calculation, D is the transformation cost of the optimal alternative equipment, It is the difference in carbon emissions before and after the transformation.

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