Optimization method and system for power transmission and transformation project design

Abstract

The invention discloses an optimization method and system for power transmission and transformation project design, applied to the field of power transmission and transformation projects, and the method comprises the steps: determining basic data of each power device; obtaining a topological relation graph of the target power transmission and transformation project; obtaining a carbon emission model of the target power transmission and transformation project; inputting the basic data into a carbon emission model to obtain first carbon emission data; applying the selected simulation environment event to the carbon emission model to obtain second carbon emission data; integrating the first carbon emission data and the second carbon emission data to obtain carbon emission information of the target power transmission and transformation project; determining each optimization node of the target power transmission and transformation project based on the carbon emission information and the topological relation graph; and obtaining a design scheme of the target power transmission and transformation project at least based on a regulation and control scheme formed for the optimization nodes. According to the optimization method and system for the power transmission and transformation project design, the stability of power transmission is improved, and the overall sustainable development capacity of the power transmission and transformation industry is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission and transformation engineering, and in particular to a power transmission and transformation engineering design optimization method and system. BACKGROUND

[0002] In the process of high-quality development of power grid engineering, the stability of power transmission is not only the core cornerstone of guaranteeing people's livelihood and supporting industrial production, but also the key prerequisite for maintaining energy security and promoting the construction of new power systems.

[0003] However, the existing design scheme of power transmission and transformation engineering considers the stability of power transmission from the traditional technical dimensions of mechanical strength of equipment selection and transmission efficiency of line path, but it ignores the fact that power transmission and transformation projects will continuously emit a large amount of carbon dioxide during operation, such as fossil energy consumption of auxiliary equipment in substations and use of fuel machinery in traditional transmission line operation and maintenance. The accumulation of carbon dioxide will block heat dissipation through the greenhouse effect, thereby causing power transmission and transformation equipment to operate in a high-temperature environment, accelerating equipment aging, increasing the probability of failure, and causing hidden and long-term impacts on the stability and reliability of power transmission. In the long run, it will also hinder the upgrading of the power transmission and transformation industry towards green and low-carbon, and reduce the overall sustainable development capability of the industry. SUMMARY

[0004] The present application provides a power transmission and transformation engineering design optimization method and system to solve the technical problem of power transmission stability, thereby achieving the effect of improving power transmission stability and improving the overall sustainable development capability of the power transmission and transformation industry.

[0005] To solve the above technical problems, the present application provides a power transmission and transformation engineering design optimization method and system, the method comprising: determining the basic data of each power device according to the design requirement information of the target power transmission and transformation project; analyzing the correlation information of each basic data to obtain a topological relationship diagram of the target power transmission and transformation project, wherein the correlation information is determined by solving the selected adjacency matrix in the quantitative analysis results of each basic data; based on the topological relationship diagram, simulating modeling of the target power transmission and transformation project to obtain a carbon emission model of the target power transmission and transformation project; inputting the basic data into the carbon emission model to obtain first carbon emission data of each power device; based on the obtained environmental information data of the target power transmission and transformation project, creating each simulation environment event; applying the selected simulation environment event to the carbon emission model to obtain second carbon emission data corresponding to the selected simulation environment event; integrating the first carbon emission data and the second carbon emission data to obtain carbon emission information of the target power transmission and transformation project; determining each optimization node of the target power transmission and transformation project based on the carbon emission information and the topological relationship diagram, the optimization node at least including one power equipment; obtaining a design scheme of the target power transmission and transformation project based on at least a regulation and control scheme formed by the optimization node.

[0006] Preferably, the simulation modeling of the target power transmission and transformation project based on the topological relationship diagram obtains a carbon emission model of the target power transmission and transformation project, including: constructing a power grid digital twin model based on power grid structured data obtained by analyzing the topological relationship diagram; performing power flow calculation on the power grid digital twin model to obtain a carbon source list of the target power transmission and transformation project; analyzing and processing the carbon source list in combination with a carbon emission factor database to obtain carbon flow distribution of the target power transmission and transformation project; obtaining the carbon emission model of the target power transmission and transformation project based on the carbon flow distribution.

[0007] Preferably, the target power transmission and transformation project at least includes one power equipment; the environment information data of the target power transmission and transformation project is obtained to create each simulation environment event, including: processing the obtained environment information data of the target power transmission and transformation project to obtain a standardized environment parameter set; converting the standardized environment parameter set into operation boundary conditions of at least one power equipment; creating each simulation environment event based on the operation boundary conditions.

[0008] Preferably, the integration of the first carbon emission data and the second carbon emission data to obtain the carbon emission information of the target power transmission and transformation project includes: obtaining a multi-dimensional carbon emission data set based on the first carbon emission data and the second carbon emission data; statistically analyzing the multi-dimensional carbon emission data set to obtain carbon emission characteristic data of the target power transmission and transformation project; analyzing and processing the carbon emission characteristic data to obtain the carbon emission information of the target power transmission and transformation project.

[0009] Preferably, the determination of each optimization node of the target power transmission and transformation project based on the carbon emission information and the topological relationship diagram, the optimization node at least including one power equipment, includes: The carbon emission information is subjected to threshold comparison processing to obtain an abnormal carbon emission node of the target power transmission and transformation project. The abnormal carbon emission node is mapped to the topological relationship graph to determine a corresponding associated device. Based on the abnormal carbon emission node and the corresponding associated device, the optimization node is determined.

[0010] Another aspect of the present application provides a power transmission and transformation project design optimization system, comprising: A determination module is configured to determine the basic data of each power device according to the design requirement information of the target power transmission and transformation project. An analysis module is configured to analyze the associated information of each basic data to obtain a topological relationship graph of the target power transmission and transformation project, wherein the associated information is determined by solving a selected adjacency matrix in the quantitative analysis result of the quantitative analysis of each basic data. A modeling module is configured to simulate and model the target power transmission and transformation project based on the topological relationship graph to obtain a carbon emission model of the target power transmission and transformation project. A first carbon emission module is configured to input the basic data into the carbon emission model to obtain first carbon emission data of each power device. An environmental event module is configured to create each simulation environmental event based on the obtained environmental information data of the target power transmission and transformation project. A second carbon emission module is configured to apply the selected simulation environmental event to the carbon emission model to obtain second carbon emission data corresponding to the selected simulation environmental event. A carbon emission information module is configured to integrate the first carbon emission data and the second carbon emission data to obtain carbon emission information of the target power transmission and transformation project. An optimization node module is configured to determine each optimization node of the target power transmission and transformation project based on the carbon emission information and the topological relationship graph, wherein the optimization node at least includes one power device. A regulation and control module is configured to obtain a design scheme of the target power transmission and transformation project based on at least a regulation and control scheme formed by the optimization node.

[0011] Preferably, the modeling module comprises: A construction unit is configured to construct a power grid digital twin model based on the power grid structured data obtained by analyzing the topological relationship graph. A carbon source list unit is configured to perform power flow calculation on the power grid digital twin model to obtain a carbon source list of the target power transmission and transformation project. An analysis unit is configured to analyze the carbon source list in combination with a carbon emission factor database to obtain a carbon flow distribution of the target power transmission and transformation project. A carbon emission model unit is configured to obtain the carbon emission model of the target power transmission and transformation project based on the carbon flow distribution.

[0012] Preferably, the target power transmission and transformation project comprises at least one power equipment. The environmental event module comprises: A standardization unit is configured to process the obtained environmental information data of the target power transmission and transformation project to obtain a set of standardized environmental parameters. A running boundary unit is configured to convert the set of standardized environmental parameters into running boundary conditions of at least one power equipment. A simulation environment unit is configured to create each simulation environmental event based on the running boundary conditions.

[0013] Preferably, the carbon emission information module comprises: A multi-dimensional unit is configured to obtain a multi-dimensional carbon emission data set based on the first carbon emission data and the second carbon emission data. A statistical unit is configured to statistically analyze the multi-dimensional carbon emission data set to obtain carbon emission characteristic data of the target power transmission and transformation project. A carbon emission unit is configured to analyze the carbon emission characteristic data to obtain the carbon emission information of the target power transmission and transformation project.

[0014] Preferably, the optimization node module comprises: A threshold comparison unit is configured to perform threshold comparison processing on the carbon emission information to obtain an abnormal carbon emission node of the target power transmission and transformation project. An associated equipment unit is configured to map the abnormal carbon emission node to the topological relationship graph to determine corresponding associated equipment. A determination unit is configured to determine the optimization node based on the abnormal carbon emission node and the corresponding associated equipment.

[0015] Compared with the prior art, the present application has at least one of the following advantages: This invention provides an optimization method and system for power transmission and transformation engineering design. First, basic equipment data is determined through design requirements, and a topology graph is constructed using adjacency matrix quantitative analysis. This leads to the establishment of a refined carbon emission model that includes operating losses and implicit carbon emissions. First, initial carbon emission data under normal operating conditions is obtained by inputting the basic data. Simultaneously, environmental information is combined to create simulated environmental events, simulating extreme operating conditions to obtain second carbon emission data. These are then integrated and analyzed to form multi-dimensional carbon emission information including total carbon emissions, distribution characteristics, and environmental sensitivity. Finally, the carbon emission information is cross-analyzed with the topology graph to accurately identify key optimization nodes and formulate targeted control schemes, resulting in a low-carbon optimized final design scheme. This method realizes a shift from traditional experience-based design to data-driven approaches. Through multi-scenario carbon emission simulation and precise location optimization, it improves the stability of power transmission and provides important technical support for building new power systems. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating an optimization method for power transmission and transformation engineering design in one embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of an optimization system for power transmission and transformation engineering design in one embodiment of the present invention; Figure label: The module includes: 11. Determination module; 12. Analysis module; 13. Modeling module; 14. First carbon emission module; 15. Environmental event module; 16. Second carbon emission module; 17. Carbon emission information module; 18. Optimization node module; and 19. Regulation module. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joint" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. The term "and / or" as used herein includes any and all combinations of one or more of the related listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0020] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0021] Stable and reliable power transmission is the cornerstone of people's livelihood, the lifeline of industrial operation, and the key to maintaining energy security and driving the construction of new power systems.

[0022] Existing power grid projects primarily focus on equipment strength and transmission efficiency during design, neglecting the carbon dioxide emissions generated by the consumption of fossil fuels during operation. These emissions exacerbate the greenhouse effect, lead to high-temperature environments, accelerate equipment aging and increase the risk of failure, and have a long-term impact on the stability and reliability of power transmission, hindering the industry's green and low-carbon transformation and sustainable development.

[0023] One embodiment of the present invention provides an optimization method for the design of power transmission and transformation projects. For details, please refer to [link to relevant documentation]. Figure 1 , Figure 1 The diagram shown illustrates a flowchart of an optimization method for power transmission and transformation engineering design according to one embodiment of the present invention. The method includes: S1. Determine the basic data of each power equipment based on the design requirements of the target power transmission and transformation project; S2. Analyze the correlation information of each basic data to obtain the topology diagram of the target power transmission and transformation project. The correlation information is determined by quantitative analysis of each basic data and the solution result of the selected adjacency matrix in the quantitative analysis results. S3. Based on the topology diagram, a simulation model of the target power transmission and transformation project is performed to obtain the carbon emission model of the target power transmission and transformation project; S4. Input the basic data into the carbon emission model to obtain the first carbon emission data for each power device; S5. Based on the acquired environmental information data of the target power transmission and transformation project, create various simulation environment events; S6. Apply the selected simulation environment event to the carbon emission model to obtain the second carbon emission data corresponding to the selected simulation environment event; S7. Integrate the first carbon emission data and the second carbon emission data to obtain the carbon emission information of the target power transmission and transformation project; S8. Based on carbon emission information and topology diagram, determine each optimized node of the target power transmission and transformation project. Each optimized node shall include at least one power equipment. S9. At least based on the control scheme of the optimized nodes, the design scheme of the target power transmission and transformation project is obtained.

[0024] Optimizing existing power transmission and transformation design schemes to reduce carbon emissions is an essential requirement for ensuring the long-term stable operation of the power grid and promoting the sustainable development of the industry. Traditional designs mainly focus on traditional technical dimensions such as mechanical strength and transmission efficiency, but neglect carbon emissions generated during the operation of power transmission and transformation systems due to energy consumption of substation auxiliary equipment and the use of fuel-powered machinery for line maintenance. These continuously emitted carbon dioxide emissions lead to a rise in local ambient temperature through the greenhouse effect, creating a sustained high-temperature operating environment, thereby accelerating the aging of equipment insulation and reducing mechanical performance, significantly increasing the probability of failure, and posing a hidden and long-term threat to the stability of power transmission. To consider carbon emissions from the design stage, it is necessary to systematically collect carbon footprint data of equipment throughout its entire life cycle, energy consumption intensity during construction, and carbon emission simulation data under different operating strategies during the design requirements acquisition phase. This basic data is the prerequisite for accurate quantitative simulation, enabling us to simulate, evaluate, and compare the carbon emission impact of different design schemes during the design phase, thereby selecting the optimal solution that ensures safety, stability, and transmission efficiency while also achieving low-carbon performance.

[0025] Based on the design requirements of the target power transmission and transformation project, the basic data for each power equipment is determined. Design requirements refer to the systematic input data used to define the basic technical specifications and performance objectives of the power transmission and transformation project. This data includes key dimensions such as grid interconnection requirements, load supply capacity, system stability indicators, and environmental adaptability standards. Specifically, this information first covers electrical parameter specifications, and then system operating conditions, such as voltage regulation methods, reactive power compensation requirements, and relay protection configuration principles. These requirements are specifically translated into tap changer adjustment ranges, shunt reactor capacities, and protection device operating time settings. Furthermore, it includes environmental adaptability indicators, such as altitude, pollution levels, and ambient temperature ranges. These conditions directly affect the equipment's external insulation level, creepage distance design, and temperature rise limit correction calculations. Finally, it involves life-cycle cost constraints, including investment limits, operation and maintenance cost targets, and equipment lifespan expectations. These economic parameters determine the technical and economic comparison schemes for equipment selection and the degree of standardized design. This structured and quantitative design requirements information collectively constitutes the basis for determining the basic data of the power equipment, ensuring that each equipment parameter directly responds to the overall technical and economic objectives of the project. The design requirements of the target power transmission and transformation project are analyzed and transformed into a set of specific and quantifiable basic equipment data. Step S1 obtains the identity and performance parameters of each key piece of equipment, such as the rated capacity and no-load loss of the main transformer, the rated breaking current of the circuit breaker, and the resistance and current carrying capacity of the transmission line. Simultaneously, its entire lifecycle information is obtained, including the types and weights of materials used in the manufacturing stage, the estimated energy consumption during assembly and transportation, and typical load curves and cooling methods during operation. This precise data is the fundamental basis for all subsequent simulation analysis and optimization design, ensuring that the design scheme meets traditional performance requirements while accurately assessing its carbon footprint and long-term operational efficiency.

[0026] In step S2, the correlation information of various basic data is analyzed to obtain the topology diagram of the target power transmission and transformation project. The correlation information is determined by quantitative analysis of each basic data point, using the results of solving the selected adjacency matrix from the quantitative analysis. After obtaining the precise geographical coordinates and electrical connection port types of all power equipment, the physical distance and electrical compatibility between equipment are calculated through quantitative analysis. An adjacency matrix that clearly represents the connection relationships between equipment is solved. Each row and column intersection in this matrix is ​​a quantified connection weight. When the weight exceeds a preset threshold, a topological connection edge is determined to exist between two devices. Finally, by parsing this complete adjacency matrix, the system automatically draws a clear topology diagram with devices as nodes and connection edges as lines.

[0027] One embodiment of the present invention employs a physical topology construction based on a rule engine and geographic information to achieve step S2. The geographic coordinates and electrical attributes of all devices are imported into the GIS system, and then spatial analysis is performed using predefined adjacency rules. For example, the system automatically searches for substations and transmission line terminals within a certain distance that match their voltage levels. When the distance between the two is less than a threshold and their electrical parameters are compatible, the rule engine fills in a connection identifier at the corresponding position in the adjacency matrix, thereby generating a batch of physically connected topologies.

[0028] After obtaining the topology analysis diagram, a simulation model of the target power transmission and transformation project is performed based on the topology relationship diagram to obtain the carbon emission model of the target power transmission and transformation project. Based on the grid structured data obtained by parsing the topology relationship diagram, a digital twin model of the power grid is constructed. Power flow calculations are performed on the digital twin model of the power grid to obtain the carbon source inventory of the target power transmission and transformation project. The carbon source inventory is analyzed and processed in conjunction with a carbon emission factor database to obtain the carbon flow distribution of the target power transmission and transformation project. Based on the carbon flow distribution, the carbon emission model of the target power transmission and transformation project is obtained. Using power grid digital twin technology, abstract carbon emissions are spatially located and quantitatively tracked within the power grid. The topology relationship of the target power transmission and transformation project is analyzed, and physical equipment such as substations, transmission lines, and switches, as well as their electrical connections, are transformed into node and branch data that can be identified and processed by computers, forming a structured power grid data foundation. Based on this precise structured data, a digital twin model that is synchronously simulated and dynamically interacts with the real power grid is constructed on a simulation platform. The Newton-Raphson method is used for power flow calculations to solve for the electrical quantity distribution of the power grid under specific operating conditions. Through calculation, the active power flowing through each transmission line, the load condition of each transformer winding, and the distribution of network losses across the entire network can be accurately obtained. These calculation results constitute a carbon source inventory, yielding all carbon emission sources and their values ​​caused by power transmission and losses. Then, a database containing carbon emission coefficients per unit of power generation for different energy types, such as coal-fired, gas-fired, wind-fired, and photovoltaic power, is accessed. The power data in the carbon source inventory is multiplied by the corresponding carbon emission factors, thus converting the power flow into a carbon flow. Based on the carbon flow distribution map, feature extraction and parametric modeling are performed, transforming the visualized data into node carbon potential vectors and branch carbon flow density matrices, establishing a mapping relationship between the power grid topology and carbon flow data. Next, graph theory and the law of conservation of energy are used to construct a set of node carbon flow balance equations. By introducing admittance matrices, a mathematical relationship between node injected power and branch carbon flow is established, forming the core algorithm for carbon flow calculation. Then, numerical calculation methods are used to solve this set of equations, employing the Newton-Raphson method for iterative solution to ensure the convergence and accuracy of the node carbon potential calculation. Based on this, a carbon flow sensitivity analysis model was established to calculate the Jacobian matrix of the system carbon flow distribution affected by changes in node injection power, quantifying the impact of operating parameter changes on carbon emissions. Finally, through model validation and calibration, historical operating data was used to inversely calculate the model parameters, and the least squares method was used to optimize the model accuracy, ensuring that the error between the model output and the actual measurement data was controlled within the allowable range, ultimately forming a mathematical model for carbon emissions with predictive analysis capabilities.

[0029] The purpose of simulation modeling for target power transmission and transformation projects is to transform the abstract physical connections of the power grid into a dynamic computational framework capable of quantifying and analyzing carbon emissions. The topology diagram precisely defines the electrical connections and energy transmission paths of various components in the power grid, such as transformers, transmission lines, and circuit breakers. This forms the physical basis for tracking and distributing carbon flows within the power grid. Without this topology, carbon emission calculations can only be limited to total estimations on the generation side, failing to reveal the complete spatiotemporal distribution of carbon emissions as they are transmitted, distributed, and ultimately consumed by electricity. Through topology-based simulation modeling, a digital twin of the power grid can be constructed, and power flow calculations can be used to accurately solve for the power distribution and losses of each line. This allows for precise tracing and allocation of the carbon emission intensity injected into the network from the generation side to each network node and branch, based on the direction and proportion of energy flow. Ultimately, this process will result in a carbon emission model that reflects the actual operating status of the power grid. This model will not only output the total carbon emissions of the system, but also reveal the source composition, transmission paths, and distribution density of carbon emissions in the network. This will provide an indispensable scientific basis for identifying carbon emission hotspots and optimizing power grid operation to achieve low-carbon dispatch.

[0030] The basic data is then input into the carbon emission model to obtain the initial carbon emission data for each power device. Based on a node carbon potential calculation framework, the carbon emission intensity on the generation side is transmitted to each node in the network via a topological correlation matrix. An improved carbon flow tracing algorithm is used to allocate carbon emissions based on the actual contribution of each device during power transmission. For transmission lines, the carbon emissions corresponding to transmission losses are calculated based on the line power flow direction and carbon flow density matrix. For transformers, load carbon emissions and no-load carbon emissions are calculated separately based on winding load rate and core loss characteristics. For reactive power compensation equipment such as circuit breakers and capacitors, the implicit carbon emissions generated by their ancillary services are indirectly calculated by analyzing the impact of their reactive power on system network losses. Finally, the model outputs a precise carbon emission inventory for each device throughout its entire lifecycle, providing a quantitative basis for subsequent carbon asset management and emission reduction strategy formulation.

[0031] The primary carbon emission data, serving as a carbon emission profile under normal system operation, accurately reveals the carbon emission contribution of equipment such as transformers and transmission lines under standard environmental conditions. This provides an indispensable benchmark for subsequent assessments of the carbon emission impact of environmental disturbances such as abnormal weather. This benchmark data enables subsequent analysis of carbon emission changes under different environmental scenarios. It can quantify the additional carbon emissions caused by increased line losses due to rain and snow, and assess the impact of increased energy consumption in transformer cooling systems under high-temperature conditions on the carbon footprint, thereby constructing a complete carbon emission impact assessment chain from baseline to abnormal operating conditions.

[0032] Based on the acquired environmental information data of the target power transmission and transformation project, various simulation environmental events are created. The acquired environmental information data of the target power transmission and transformation project is processed to obtain a standardized environmental parameter set. The standardized environmental parameter set is then transformed into the operating boundary conditions of at least one of the power equipment. Based on the operating boundary conditions, various simulation environmental events are created. First, the original environmental information data is standardized and preprocessed. Data cleaning algorithms are used to remove outliers and missing items. The Z-score standardization method is applied to transform heterogeneous meteorological data such as temperature, humidity, and wind speed into a dimensionless standardized environmental parameter set, ensuring the comparability and calculability of parameters with different dimensions. Subsequently, by establishing a mapping function between environmental parameters and equipment operating characteristics, the standardized parameters are transformed into the operating boundary conditions of specific power equipment. For example, based on the heat balance equation, the ambient temperature and wind speed parameters are transformed into constraints on the temperature rise of the transformer top oil. According to the IEEE 738 standard, the solar radiation, ambient temperature, and wind speed parameters are comprehensively calculated into the dynamic threshold of the maximum allowable current carrying capacity of the overhead conductor, and the critical value of the insulator string flashover voltage is corrected using rainfall intensity data. Finally, based on these quantified equipment operating boundary conditions, an event-driven modeling approach is used to construct simulated environmental events. By combining the temporal variation patterns of different environmental parameters, a set of typical operating scenarios is formed, including but not limited to events such as the tightening of conductor thermal stability limits under high-temperature and high-load conditions, the doubling of line mechanical loads under freezing weather, and the degradation of external insulation strength under humid salt spray conditions. This allows for the accurate reproduction of the impact of multi-dimensional environmental stress on the power grid's operating status on a digital twin platform. The fundamental reason for creating these simulated environmental events is that the actual operating status of the power grid and its carbon footprint are strongly dependent on the external environment. A single standard operating condition simulation cannot reflect the full picture of real carbon emissions. It is necessary to construct a multi-dimensional set of environmental events covering extreme weather and seasonal changes to comprehensively assess the carbon emission resilience of transmission and transformation projects throughout their entire life cycle and provide reliable data support for formulating low-carbon operation strategies that adapt to climate change.

[0033] The selected simulated environmental events are applied to the carbon emission model to obtain second carbon emission data corresponding to the selected simulated environmental events. The specific implementation process is the same as step S4. Different simulation environments are selected for power transmission and transformation projects in different regions to obtain second carbon emission data. For example, for power transmission and transformation projects in coastal areas, high salt spray and humidity environmental events are applied to simulate the risk of line outages caused by increased insulator flashover probability, and then calculate the additional carbon emissions generated by the commissioning of backup lines. For projects in plateau areas, low air pressure and strong ultraviolet radiation environmental events are applied to correct the heat dissipation efficiency of switchgear and the arc extinguishing capacity of circuit breakers, and quantify the carbon emission increment corresponding to the increase in network losses caused by equipment de-rated operation. For densely industrialized areas, acid rain corrosion environmental events are applied to simulate the phenomenon of increased resistance caused by conductor cross-section deterioration, and calculate the carbon emission increase curve caused by increased power transmission loss. By defining the transfer function between environmental stress factor and carbon emission sensitivity, the system constructs a complete mapping relationship from geographical and climatic characteristics to operational carbon emissions. The final output second carbon emission data forms a differentiated carbon footprint spectrum covering regional characteristics, providing a key decision-making basis for formulating regional adaptive emission reduction strategies.

[0034] After obtaining the first and second carbon emission data, step S7 integrates them to obtain the carbon emission information of the target power transmission and transformation project. The goal of this integration is to construct a comprehensive evaluation system that can fully reflect the carbon emission characteristics of the power transmission and transformation project under baseline operating conditions and multi-dimensional environmental stresses. First, a data fusion matrix is ​​established, linking the equipment-level carbon emission vector represented by the first carbon emission data under baseline operating conditions with the carbon emission change matrix corresponding to each simulated environmental event in the second carbon emission data. Then, a weighted superposition algorithm is used to assign corresponding weight coefficients based on the historical probability and duration of different environmental events, calculating the expected carbon emission value of each power device under the comprehensive operating scenario. On this basis, a carbon emission resilience index quantification system is introduced. By calculating the deviation of the second carbon emission data from the first baseline data, the disturbance intensity and impact range of extreme environmental events on the system's carbon footprint are analyzed. Finally, through spatiotemporal aggregation calculations, a multi-dimensional carbon emission information spectrum covering equipment level, subsystem level and network level is generated. This information spectrum not only includes the total static carbon emissions, but also reveals the dynamic characteristics and weak links of system carbon emissions as environmental conditions change, providing a complete quantitative decision-making basis for carbon asset management, adaptive emission reduction planning and climate resilience construction of power transmission and transformation projects.

[0035] After obtaining carbon emission information, based on the carbon emission information and topology diagram, the optimization nodes of the target power transmission and transformation project are determined. Each optimization node includes at least one power device. Optimization nodes refer to key power devices or network locations identified in the carbon flow analysis of the power transmission and transformation project that have significant emission reduction potential and regulatory value. These nodes typically possess one or more of the following characteristics: they are located on critical paths of energy transmission in the topology, and their operating status is highly sensitive to the overall carbon emissions of the system; they themselves carry high-density carbon flows or generate large amounts of carbon emissions, such as core transformers in load centers or heavily loaded transmission lines; adjustments to their operating parameters can effectively change the power flow distribution, thus significantly affecting the system's carbon footprint, such as the installation point of reactive power compensation devices or the location of tie switches. By implementing targeted regulation of these key nodes, such as adjusting transformer tap settings, optimizing line current carrying capacity, or reconfiguring reactive power compensation, the overall optimization of system carbon emissions can be achieved at the lowest cost, providing precise intervention targets for the low-carbon transformation of the power grid. First, a correlation matrix between equipment carbon emission intensity and network location is established. The absolute carbon emissions of each device are normalized according to the electrical centrality of its topology to form a carbon emission impact factor index. Subsequently, a multi-level screening mechanism was employed. At the first level, Pareto analysis based on absolute carbon emissions identified a set of high-carbon-emission equipment whose cumulative contribution exceeded 80%. At the second level, carbon flow sensitivity analysis was used to calculate the Jacobian matrix of the effect of node power injection changes on the total carbon emissions of the system, identifying sensitive nodes where unit power adjustments could cause significant changes in system carbon emissions. At the third level, topology analysis was combined with calculations of node betweenness centrality and electrical distance to locate hub equipment located at the intersection of multiple critical carbon flow paths. Finally, the intersection of these three screening results was used to determine key power equipment possessing both high carbon emission characteristics and high control sensitivity as optimized nodes. Examples include main transformers located at the network's electrical center with consistently high load rates or important interconnecting lines connecting different carbon intensity regions. Optimizing these nodes will enable a precise improvement in the overall carbon emission efficiency of the system.

[0036] After obtaining the optimized nodes, the design scheme for the target power transmission and transformation project is derived based on the control scheme formed for these optimized nodes. First, for the identified optimized nodes, equipment-level control strategies are generated through carbon flow sensitivity analysis. For example, for the main transformer located on the carbon flow critical path, a coordinated control scheme of on-load tap changer and intelligent cooling system is proposed. By dynamically adjusting the fan operation mode through real-time monitoring of winding temperature, no-load losses are reduced by 15%. For transmission corridors with high carbon emission density, a dynamic capacity expansion and renovation scheme is formulated, replacing the conventional conductors in the original design with carbon fiber composite core conductors, increasing the current carrying capacity by 30% and reducing line resistance losses under the same cross-section. Subsequently, a multi-objective optimization algorithm is used to systematically integrate these discrete strategies, using the annualized carbon emission reduction and investment payback period as dual objective functions. Under constraints such as N-1 safety verification, the optimal combination of technical parameters is solved. Finally, the optimization results are mapped to the engineering design dimension, and the equipment selection parameters, control system logic interlocks and protection settings in the original scheme are corrected to form the final design scheme, which includes accurate equipment specifications, modification construction drawings and carbon emission performance prediction reports, thus completing the entire process transformation from analysis and diagnosis to engineering implementation.

[0037] Another embodiment of the present invention provides an optimization system for power transmission and transformation engineering design; please refer to [link to relevant documentation]. Figure 2 , Figure 2 The diagram shows a structural schematic of an optimization system for power transmission and transformation engineering design according to one embodiment of the present invention. The system includes: Module 11 is used to determine the basic data of each power equipment based on the design requirements of the target power transmission and transformation project. Analysis module 12 is used to analyze the correlation information of each of the basic data to obtain the topology diagram of the target power transmission and transformation project. The correlation information is determined by performing quantitative analysis on each of the basic data and using the solution result of the selected adjacency matrix in the quantitative analysis result. Modeling module 13 is used to perform simulation modeling of the target power transmission and transformation project based on the topology diagram to obtain the carbon emission model of the target power transmission and transformation project; The first carbon emission module 14 is used to input the basic data into the carbon emission model to obtain the first carbon emission data for each of the power devices. The environmental event module 15 is used to create various simulation environmental events based on the acquired environmental information data of the target power transmission and transformation project; The second carbon emission module 16 is used to apply the selected simulated environmental event to the carbon emission model to obtain second carbon emission data corresponding to the selected simulated environmental event; Carbon emission information module 17 is used to integrate the first carbon emission data and the second carbon emission data to obtain the carbon emission information of the target power transmission and transformation project; The optimization node module 18 is used to determine each optimization node of the target power transmission and transformation project based on the carbon emission information and the topology diagram, wherein the optimization node includes at least one of the power equipment. The control module 19 is used to obtain the design scheme of the target power transmission and transformation project based at least on the control scheme formed by the optimized nodes.

[0038] The modeling module 13 includes: The construction unit is used to construct a digital twin model of the power grid based on the power grid structured data obtained by parsing the topology diagram; The carbon source inventory unit is used to perform power flow calculations on the digital twin model of the power grid to obtain the carbon source inventory of the target power transmission and transformation project. The analysis unit is used to analyze and process the carbon source inventory in conjunction with the carbon emission factor database to obtain the carbon flow distribution of the target power transmission and transformation project; A carbon emission model unit is used to obtain the carbon emission model of the target power transmission and transformation project based on the carbon flow distribution.

[0039] The target power transmission and transformation project includes at least one power equipment; The environmental event module 15 includes: The standardization unit is used to process the acquired environmental information data of the target power transmission and transformation project to obtain a standardized environmental parameter set; A boundary unit is used to transform the standardized environmental parameter set into operational boundary conditions for at least one of the power devices. The simulation environment unit is used to create various simulation environment events based on the said operational boundary conditions.

[0040] The carbon emission information module 17 includes: A multi-dimensional unit is used to obtain a multi-dimensional carbon emission dataset based on the first carbon emission data and the second carbon emission data; The statistical unit is used to perform statistical analysis on the multi-dimensional carbon emission dataset to obtain the carbon emission characteristic data of the target power transmission and transformation project. A carbon emission unit is used to analyze and process the carbon emission characteristic data to obtain the carbon emission information of the target power transmission and transformation project.

[0041] The optimized node module 18 includes: A threshold comparison unit is used to perform threshold comparison processing on the carbon emission information to obtain the abnormal carbon emission nodes of the target power transmission and transformation project. The associated device unit is used to map the abnormal carbon emission node to the topology graph and determine the corresponding associated device. The determining unit is used to determine the optimized node based on the abnormal carbon emission node and the corresponding associated equipment.

[0042] Another embodiment of the present invention provides a construction method for optimizing power transmission and transformation stations. The following 24 green technologies are selected to replace typical technologies, and the carbon emissions of typical construction technologies and green construction technologies are calculated respectively. Finally, the results are summarized and compared. Table 1 shows the typical technologies that are replaced by green technologies.

[0043] Table 1. Typical technologies that green technologies replace. As a crucial component of substation construction, the selection of overhead transmission lines with higher compatibility plays a vital role in ensuring the reliability of the power system and the continuity of electrical energy.

[0044] A comparative analysis of the cost differences between projects using traditional aluminum stranded wire and high-conductivity aluminum stranded wire revealed that the initial investment cost of high-conductivity aluminum stranded wire was slightly higher than that of traditional aluminum stranded wire. However, related research indicates that the dynamic investment payback period for the high-conductivity aluminum stranded wire solution is shorter, and the total operating cost of the line is lower than that of the traditional aluminum stranded wire solution. Considering all factors, high-conductivity aluminum stranded wire offers better economic benefits.

[0045] Table 2 Comparison of parameters for different conductors Table 3. Cost Comparison of Different Conductors 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 program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0046] Accordingly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform steps in the optimization method for power transmission and transformation engineering design as described in the above embodiments, for example... Figure 1 Steps S1 to S9 as described above.

[0047] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0048] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: This invention discloses an optimization method and system for power transmission and transformation engineering design. The method includes: determining the basic parameters of each power equipment based on design requirements; quantitatively analyzing the parameter correlation based on the adjacency matrix algorithm to construct a complete power grid topology diagram; and establishing a refined carbon emission simulation model covering operational energy consumption and implicit carbon footprint based on this model. By inputting the basic parameters, benchmark carbon emission data under normal operating conditions is obtained. Simultaneously, a typical operating condition event set is constructed by combining environmental monitoring data to simulate carbon emission characteristics under different environmental conditions. Finally, this is integrated to form a panoramic carbon emission assessment report including total emission distribution, structural characteristics, and environmental response characteristics. Based on the collaborative analysis of this report and the power grid topology, key nodes affecting carbon emissions can be accurately located, and differentiated control strategies can be formulated accordingly, forming a low-carbon optimization design scheme throughout the entire life cycle. This invention realizes the transformation from traditional experience-based design to digital intelligent design. Through multi-dimensional carbon emission simulation and precise optimization, it significantly improves the carbon emission control efficiency and operational reliability of power transmission and transformation engineering.

Claims

1. An optimization method for power transmission and transformation engineering design, characterized in that, include: Based on the design requirements of the target power transmission and transformation project, determine the basic data of each power equipment; By analyzing the correlation information of each of the basic data, the topology diagram of the target power transmission and transformation project is obtained. The correlation information is determined by performing quantitative analysis on each of the basic data and solving the selected adjacency matrix in the quantitative analysis results. Based on the aforementioned topology diagram, a simulation model of the target power transmission and transformation project is performed to obtain the carbon emission model of the target power transmission and transformation project. The basic data is input into the carbon emission model to obtain the first carbon emission data for each of the power devices. Based on the acquired environmental information data of the target power transmission and transformation project, various simulation environment events are created; The selected simulated environmental event is applied to the carbon emission model to obtain second carbon emission data corresponding to the selected simulated environmental event; The carbon emission data of the target power transmission and transformation project are obtained by integrating the first carbon emission data and the second carbon emission data. Based on the carbon emission information and the topology diagram, each optimized node of the target power transmission and transformation project is determined, and each optimized node includes at least one of the power equipment. The design scheme for the target power transmission and transformation project is obtained based at least on the control scheme formed by the optimized nodes.

2. The optimization method for power transmission and transformation engineering design as described in claim 1, characterized in that, The simulation modeling of the target power transmission and transformation project based on the topology diagram to obtain the carbon emission model of the target power transmission and transformation project includes: Based on the structured power grid data obtained by parsing the aforementioned topology diagram, a digital twin model of the power grid is constructed. Power flow calculations are performed on the digital twin model of the power grid to obtain the carbon source inventory of the target power transmission and transformation project; By analyzing and processing the carbon source inventory using a carbon emission factor database, the carbon flow distribution of the target power transmission and transformation project is obtained. Based on the carbon flow distribution, the carbon emission model of the target power transmission and transformation project is obtained.

3. The optimization method for power transmission and transformation engineering design as described in claim 1, characterized in that, The target power transmission and transformation project includes at least one power equipment; Based on the acquired environmental information data of the target power transmission and transformation project, various simulation environment events are created, including: The acquired environmental information data of the target power transmission and transformation project is processed to obtain a standardized set of environmental parameters; The standardized environmental parameter set is transformed into operating boundary conditions for at least one of the power devices; Based on the aforementioned operational boundary conditions, each of the aforementioned simulation environment events is created.

4. The optimization method for power transmission and transformation engineering design as described in claim 1, characterized in that, The process of integrating the first carbon emission data and the second carbon emission data to obtain the carbon emission information of the target power transmission and transformation project includes: Based on the first carbon emission data and the second carbon emission data, a multi-dimensional carbon emission dataset is obtained; Statistical analysis was performed on the multi-dimensional carbon emission dataset to obtain the carbon emission characteristic data of the target power transmission and transformation project; The carbon emission characteristic data are analyzed and processed to obtain the carbon emission information of the target power transmission and transformation project.

5. The optimization method for power transmission and transformation engineering design as described in claim 1, characterized in that, The process involves determining optimized nodes for the target power transmission and transformation project based on the carbon emission information and the topology diagram. Each optimized node includes at least one of the power equipment, including: The carbon emission information is subjected to threshold comparison processing to obtain the abnormal carbon emission nodes of the target power transmission and transformation project; The abnormal carbon emission nodes are mapped to the topology graph to determine the corresponding associated devices; Based on the abnormal carbon emission nodes and the corresponding associated devices, the optimized nodes are determined.

6. An optimization system for power transmission and transformation engineering design, characterized in that, include: The determination module is used to determine the basic data of each power equipment based on the design requirements of the target power transmission and transformation project; The analysis module is used to analyze the correlation information of each of the basic data to obtain the topology diagram of the target power transmission and transformation project. The correlation information is determined by performing quantitative analysis on each of the basic data and solving the selected adjacency matrix in the quantitative analysis results. The modeling module is used to perform simulation modeling of the target power transmission and transformation project based on the topology diagram, and obtain the carbon emission model of the target power transmission and transformation project; The first carbon emission module is used to input the basic data into the carbon emission model to obtain the first carbon emission data for each of the power devices. The environmental event module is used to create various simulation environmental events based on the acquired environmental information data of the target power transmission and transformation project. The second carbon emission module is used to apply the selected simulated environmental event to the carbon emission model to obtain second carbon emission data corresponding to the selected simulated environmental event. The carbon emission information module is used to integrate the first carbon emission data and the second carbon emission data to obtain the carbon emission information of the target power transmission and transformation project. An optimization node module is used to determine each optimization node of the target power transmission and transformation project based on the carbon emission information and the topology diagram, wherein the optimization node includes at least one of the power equipment. The control module is used to obtain the design scheme of the target power transmission and transformation project based at least on the control scheme formed by the optimized nodes.

7. The optimization system for power transmission and transformation engineering design as described in claim 6, characterized in that, The modeling module includes: The construction unit is used to construct a digital twin model of the power grid based on the power grid structured data obtained by parsing the topology diagram; The carbon source inventory unit is used to perform power flow calculations on the digital twin model of the power grid to obtain the carbon source inventory of the target power transmission and transformation project. The analysis unit is used to analyze and process the carbon source inventory in conjunction with the carbon emission factor database to obtain the carbon flow distribution of the target power transmission and transformation project; A carbon emission model unit is used to obtain the carbon emission model of the target power transmission and transformation project based on the carbon flow distribution.

8. The optimization system for power transmission and transformation engineering design as described in claim 6, characterized in that, The target power transmission and transformation project includes at least one power equipment; The environmental event module includes: The standardization unit is used to process the acquired environmental information data of the target power transmission and transformation project to obtain a standardized environmental parameter set; A boundary unit is used to transform the standardized environmental parameter set into operational boundary conditions for at least one of the power devices. The simulation environment unit is used to create various simulation environment events based on the said operational boundary conditions.

9. The optimization system for power transmission and transformation engineering design as described in claim 6, characterized in that, The carbon emission information module includes: A multi-dimensional unit is used to obtain a multi-dimensional carbon emission dataset based on the first carbon emission data and the second carbon emission data; The statistical unit is used to perform statistical analysis on the multi-dimensional carbon emission dataset to obtain the carbon emission characteristic data of the target power transmission and transformation project. A carbon emission unit is used to analyze and process the carbon emission characteristic data to obtain the carbon emission information of the target power transmission and transformation project.

10. The optimization system for power transmission and transformation engineering design as described in claim 6, characterized in that, The optimized node module includes: A threshold comparison unit is used to perform threshold comparison processing on the carbon emission information to obtain the abnormal carbon emission nodes of the target power transmission and transformation project. The associated device unit is used to map the abnormal carbon emission node to the topology graph and determine the corresponding associated device. The determining unit is used to determine the optimized node based on the abnormal carbon emission node and the corresponding associated equipment.

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