Power grid resource visual display method for business expansion scheme

Abstract

The invention relates to the technical field of power management, and discloses a power grid resource visual display method for a business expansion scheme. According to the method, by collecting and processing the power grid operation data, the power grid topological data and the user power load historical data in real time, high-quality and more accurate fusion analysis of the data is guaranteed, static data is converted into dynamic information, the limitation that a traditional visualization tool can only provide outdated information is overcome, and the method is suitable for popularization and application. By means of calculation of short-term and long-term load prediction, the influence of a newly added load on the overall safety and stability of an existing power grid is effectively evaluated, and a user can visually observe voltage distribution of each node of the power grid, a branch current state and a real-time load condition through a visual display module, so that the user experience is improved. According to the comprehensive display scheme, the intelligence level of power resource configuration is improved, important support is provided for optimization management decision of power grid operation, and efficient utilization and further sustainable development of power grid resources can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to a method for visually displaying grid resources for a business expansion plan. Background Art

[0002] With the continuous acceleration of the urbanization process and the continuous growth of power demand, the expansion and upgrade of the power grid have become urgent problems to be solved. The business expansion plan is a process of optimizing and improving the existing power grid while meeting the load requirements of new users. This process not only includes the restructuring of the power grid structure and the reasonable allocation of loads, but also involves the effective management and sustainable utilization of grid resources. Therefore, it is particularly important to introduce a method for visually displaying grid resources. Through an intuitive visual interface, both power operators and users can more clearly understand the distribution and load conditions of grid resources, so as to make reasonable decisions and resource allocations. The visualization method can use various display means such as maps, charts, and dynamic simulations to make complex grid data intuitive and easy to understand, promote communication and collaboration among stakeholders, and thus improve the utilization efficiency and management level of grid resources.

[0003] Currently, most grid resource visualization technologies still have many deficiencies, which limit their effects in practical applications. Many existing visualization methods often rely too much on static data display and lack the ability of dynamic real-time monitoring, and cannot timely reflect the changes in the operating state of the power grid, which poses an obstacle to quickly responding to power emergencies and load changes. At the same time, existing visualization solutions usually target technical personnel, and it is difficult for ordinary users or decision-makers to understand and use them, which creates an information communication barrier and reduces the decision-making efficiency. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a method for visualizing grid resources for the business expansion plan. By collecting and processing grid operation data, grid topology data, and historical user power load data in real time, it not only ensures high-quality and more accurate fusion analysis of data, but also transforms static data into dynamic information, overcoming the limitation that traditional visualization tools can only provide outdated information. With the calculation of short-term and long-term load forecasting, the system can provide a scientific basis for the load distribution of the grid and the access plan for new users, thereby effectively evaluating the impact of the new load on the overall security and stability of the existing grid. Through the visualization display module, users can intuitively observe the voltage distribution of each grid node, the branch current status, and the real-time load situation, promoting information exchange between technical personnel and ordinary users, and enhancing the communication and collaboration capabilities of different stakeholders. This comprehensive display plan not only improves the intelligent level of power resource allocation, but also provides important support for the optimization management decision-making of grid operation, contributing to the efficient utilization of grid resources and further sustainable development, and solving the above problems.

[0006] (II) Technical Solution

[0007] To achieve the above object, the present invention provides the following technical solution: A method for visualizing grid resources for the business expansion plan, comprising the following steps:

[0008] S1. Real-time collect grid operation data, grid topology data, historical user power load data, and business expansion plan data through the power data acquisition unit;

[0009] S2. Conduct quality inspection on the grid operation data, grid topology data, historical user power load data, and business expansion plan data through the power data processing unit, remove redundant data, apply data fusion technology to integrate grid operation data, grid topology data, historical user power load data, and business expansion plan data from different sources into a unified format, use statistical analysis methods to analyze historical load data, predict future load change trends, and calculate short-term grid load forecasting values and long-term grid load forecasting values;

[0010] S3. After the data processing is completed, through the power data analysis unit, according to the short-term grid load forecasting value, the long-term grid load forecasting value, and the grid topology structure, conduct power flow calculation to obtain the voltage distribution of each grid node and the current status of the branch, introduce the load demand of new users, conduct load distribution, evaluate the impact of the new load on the overall load of the grid, and calculate the short-circuit current, system power flow value, and grid power stability coefficient;

[0011] S4. The real-time monitoring data and calculation results are presented in the form of charts, maps, and dashboards through the visualization display module, showing the grid operation status, which includes current, voltage, power distribution, and real-time power load conditions.

[0012] Preferably, the formula for removing redundant data is as follows:

[0013]

[0014] In the formula, Cosine represents the cosine similarity value, A and B represent the point vectors of the grid operation data or grid topology data or user power load historical data or business expansion plan data for which redundant data needs to be removed, A·B represents the inner product of the point vectors, ||A|| represents the modulus of vector A, ||B|| represents the modulus of vector B, and ||A||*||B|| represents the length of the vector.

[0015] Preferably, the formula for integrating the data into a unified format is as follows:

[0016]

[0017] In the formula, Z represents the Z-score, which is used to unify the grid operation data or grid topology data or user power load historical data or business expansion plan data from different sources into the same data distribution standard. X represents the sample data point of the grid operation data or grid topology data or user power load historical data or business expansion plan data to be inspected, N represents the total number of data of the grid operation data or grid topology data or user power load historical data or business expansion plan data, X i represents the i-th data point in the dataset of the grid operation data or grid topology data or user power load historical data or business expansion plan data, i represents the counting subscript, represents the sum of all the numerical values in the dataset of the grid operation data or grid topology data or user power load historical data or business expansion plan data, thus obtaining the total sum of the data, represents calculating the square of the difference between each data point and the mean value, and adding all the results to obtain the overall degree of dispersion. Taking the square root represents the square root of the average deviation to obtain the standard deviation.

[0018] Preferably, the calculation formula for the short-term grid load prediction value is as follows:

[0019]

[0020] In the formula, L t+1 represents the short-term grid load prediction value, L t-jThe actual load data for the past n moments, representing the load values shifted from the current time to the past. j ranges from 0 to n - 1 representing the past n time points, and n represents the number of time points used for calculating the average. It represents the cumulative sum of the load values at the past n time points. It represents the average of the sum to obtain the predicted value for the next time point.

[0021] Preferably, the calculation formula for the long-term power grid load prediction value is as follows:

[0022] L t = s + k * t + ∈

[0023] In the formula, L t represents the long-term power grid load prediction value, s represents the load value when the time factor is zero, k represents the rate of change of the load with time, t represents the time variable, and ∈ is the error term representing the influence of other unaccounted variables.

[0024] Preferably, the calculation formula for the voltage distribution of the power grid nodes is as follows:

[0025]

[0026] In the formula, V p represents the voltage amplitude of the p-th node, V p,initial represents the initial voltage prediction value, Y pp represents the self-admittance of the p-th node, P p , Q p represent the active and reactive power demands of the p-th node, Y represents the node admittance matrix, Y pp -1 represents the reciprocal of the self-admittance of the p-th node.

[0027] Preferably, the calculation formula for the current state of the branch is as follows:

[0028] I f = Y f *(V j - V i )

[0029] In the formula, I f represents the current flowing through branch f, Y f represents the admittance of the branch, V j , V i represent the voltages of the two nodes connecting branch f.

[0030] Preferably, the calculation formula for the short-circuit current is as follows:

[0031]

[0032] In the formula, I sc represents the value of the short-circuit current, V base represents the system base voltage, Z th represents the equivalent impedance during short circuit.

[0033] Preferably, the calculation formula for the system power flow value is as follows:

[0034]

[0035] In the formula, P load represents the total active power of the system load, Gl L represents the power flow of the L-th branch, G represents the total number of branches connected to the power grid, and L represents the counting subscript. means summing over all branches from L = 1 to G to obtain the flow of total active power.

[0036] Preferably, the calculation formula for the power grid power stability coefficient is as follows:

[0037]

[0038] In the formula, Gwxs represents the power grid power stability coefficient, P new represents the updated power demand after loading, P old represents the power demand before loading, V new represents the adjusted voltage, V old represents the voltage in the initial state.

[0039] Compared with the prior art, the present invention provides a method for visualizing power grid resources for the business expansion plan, having the following beneficial effects:

[0040] By collecting and processing power grid operation data, power grid topology data, and historical user power load data in real time, the present invention not only ensures high-quality and more accurate fusion analysis of data, but also transforms static data into dynamic information, overcoming the limitation that traditional visualization tools can only provide outdated information. With the calculation of short-term and long-term load forecasting, the system can provide a scientific basis for the load distribution of the power grid and the access plan for new users, thereby effectively evaluating the impact of the new load on the overall safety and stability of the existing power grid. Through the visualization display module, users can intuitively observe the voltage distribution of each node of the power grid, the branch current status, and the real-time load situation, promoting information exchange between technical personnel and ordinary users, and enhancing the communication and collaboration capabilities of different stakeholders. This comprehensive display solution not only improves the intelligent level of power resource allocation, but also provides important support for the optimization management decision-making of power grid operation, contributing to the efficient utilization of power grid resources and further sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a schematic diagram of the method steps of the present invention. Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] In view of the problem that many existing visualization methods often rely too much on static data display, lack dynamic real-time monitoring capabilities, and cannot reflect the changes in the power grid operation status in a timely manner, which poses an obstacle to quickly responding to power emergencies and load changes, a visualization display method for power grid resources for the business expansion plan is proposed. Please refer to Figure 1 and the method includes the following steps:

[0044] S1. Real-time collect power grid operation data, power grid topology data, historical data of user power load, and business expansion plan data through a power data collection unit;

[0045] The data collection unit adopts high-precision sensors and intelligent metering devices to real-time monitor power grid operation parameters such as current, voltage, and power, and transmits the data to the central processing system through wireless communication technology. At the same time, the geographical information system (GIS) technology is used to capture the topological structure information of the power grid to ensure that the obtained data reflects the actual operation status of the power grid. In addition, the system also integrates the load measurement devices at the user end to obtain the historical change situation of the user power load. All the collected data is preliminarily processed and screened through edge computing technology to ensure the accuracy and real-time nature of the data, thereby providing a reliable basis for subsequent data analysis and decision-making;

[0046] S2. Conduct quality inspection on the power grid operation data, power grid topology data, historical data of user power load, and business expansion plan data through a power data processing unit, remove redundant data, apply data fusion technology to integrate the power grid operation data, power grid topology data, historical data of user power load, and business expansion plan data from different sources into a unified format, use statistical analysis methods to analyze the historical load data, predict the future load change trend, and calculate the short-term power grid load prediction value and the long-term power grid load prediction value;

[0047] Among them, the formula for removing redundant data is as follows:

[0048]

[0049] Removing redundant data is a crucial step in ensuring data quality and accuracy. Redundant data not only occupies storage space but may also lead to inaccurate data analysis results. In the power grid, if the same set of data is collected multiple times, it will increase the complexity of data processing and may result in incorrect decision-making bases. In the formula, Cosine represents the cosine similarity value, A and B represent the point vectors of power grid operation data or power grid topology data or user power load historical data or business expansion plan data for which redundant data needs to be removed, A·B represents the dot product of the point vectors, ||A|| represents the norm of vector A, ||B|| represents the norm of vector B, ||A||*||B|| represents the length of the vector. When the cosine similarity value Cosine is higher than 0.95, it indicates that the data point is redundant, and at this time, redundant data removal is performed. By removing redundant data, the system can process information faster, thereby improving work efficiency and ensuring the reliability of analysis results, ultimately helping power operators make timely and reasonable decisions;

[0050] The formula for integrating data into a unified format is as follows:

[0051]

[0052] Data from different sources often have their own specific formats and structures. The integrated data can eliminate compatibility issues and facilitate comprehensive analysis and visual display. This integration into a unified format can improve data interactivity, making it less likely to lose valid information when data flows between multiple systems and also facilitating data sharing between different departments or users. In the formula, Z represents the Z-score, which is used to unify power grid operation data or power grid topology data or user power load historical data or business expansion plan data from different sources into the same data distribution standard. X represents a sample data point of power grid operation data or power grid topology data or user power load historical data or business expansion plan data to be inspected. N represents the total number of data of power grid operation data or power grid topology data or user power load historical data or business expansion plan data. X i represents the i-th data point in the dataset of power grid operation data or power grid topology data or user power load historical data or business expansion plan data, and i represents the counting subscript. represents adding up all the numerical values in the dataset of power grid operation data or power grid topology data or user power load historical data or business expansion plan data to obtain the total sum of the data. represents calculating the square of the difference between each data point and the mean and adding up all the results to obtain the overall degree of dispersion. Taking the square root represents the square root of the average deviation to obtain the standard deviation. Through data integration, power companies can comprehensively understand the operation of each part of the power grid, promoting the overall efficient management and optimization of the power grid;

[0053] The calculation formula for the short-term power grid load prediction value is as follows:

[0054]

[0055] Calculating the short-term power grid load forecast value can help the power system respond to load fluctuations in a timely manner and optimize power supply. By analyzing historical load data and real-time monitoring information, short-term forecasting enables grid regulators to anticipate load changes in the next few hours or days, which is crucial for ensuring the stability of the power grid and avoiding power shortages or grid overload problems caused by unexpected loads. In the formula, L t+1 represents the short-term power grid load forecast value, and L t-j is the actual load data at the past n moments, representing the load values shifted from the current time to the past. j from 0 to n - 1 represents the past n time points, and n represents the number of time points used for calculation of the average. represents the cumulative calculation of the load values at the past n time points to obtain the total sum. represents the averaging of the total sum to obtain the forecast value for the next time point. Accurate short-term load forecasting helps with power dispatching, achieving the matching of power generation and electricity consumption demands, and improving the utilization efficiency of grid resources.

[0056] The calculation formula for the long-term power grid load forecast value is as follows:

[0057] L t = s + k * t + ∈

[0058] The calculation of the long-term power grid load forecast value is an important basis for power grid planning and improvement. It is based on long-term trend analysis and can help power companies identify load growth or decline trends in the next few months to years, and conduct reasonable power generation and transmission resource planning. In the formula, L t represents the long-term power grid load forecast value, s represents the load value when the time factor is zero, k represents the rate of load change over time, t represents the time variable, and ∈ is the error term, representing the influence of other unaccounted variables. Through accurate long-term forecasting, power companies can make targeted infrastructure investments to ensure that the power grid can meet future electricity demands. At the same time, long-term forecasting can also be used to evaluate the impact of different business expansion plans on the overall power grid, supporting decision-makers in making strategic plans for resource allocation and power grid expansion.

[0059] S3. After data processing, through the power data analysis unit, based on the short-term power grid load forecast value, the long-term power grid load forecast value, and the topological structure of the power grid, power flow calculation is carried out to obtain the voltage distribution of each power grid node and the current status of the branches. The load demand of newly added users is introduced, load distribution is carried out, the impact of the newly added load on the overall load of the power grid is evaluated, and the short-circuit current, system power flow value, and power grid power stability coefficient are calculated.

[0060] The calculation formula for the voltage distribution of power grid nodes is as follows:

[0061]

[0062] By calculating the voltage distribution of each power grid node, grid managers can timely grasp the voltage operation status of each node in the power grid, which helps to discover problems of insufficient or excessive voltage, and then carry out corresponding regulation and optimization. In the formula, V p represents the voltage amplitude of the p-th node, and V p,initial represents the initial voltage prediction value, and Y pp represents the self-admittance of the p-th node, and P p , Q p represent the active and reactive power demands of the p-th node, Y represents the node admittance matrix, and Y pp -1 represents the reciprocal of the self-admittance of the p-th node. Accurate voltage distribution information is of great significance for the reasonable design and operation of the power grid. It can help predict the performance of the power grid under different load conditions, ensure high-quality power transmission, reduce the risk of equipment damage caused by voltage fluctuations, and improve user satisfaction;

[0063] The calculation formula for the current state of a branch is as follows:

[0064] I f = Y f *(V j - V i )

[0065] Calculating the current state of a branch can effectively monitor the load situation of the power grid and ensure balanced loading of each branch. This calculation can reveal possible overload situations in the power grid, thus providing a basis for the dispatching and maintenance of the power grid. In the formula, I f represents the current flowing through branch f, Y f represents the admittance of the branch, and V j , V i represent the voltages of the two nodes connecting branch f. By real-time monitoring of the branch current, power companies can respond to faults faster, take timely measures to reduce losses, and at the same time understanding the current state of each branch helps to optimize the operation parameters of the power grid, improve the overall efficiency, and reduce line losses;

[0066] The calculation formula for the short-circuit current is as follows:

[0067]

[0068] By calculating the short-circuit current, power companies can determine the magnitude of the current borne by equipment in the event of a short circuit, so as to carry out reasonable protection configuration and selection. In the formula, I sc represents the value of the short-circuit current, and V base represents the system base voltage, and Zth It represents the equivalent impedance during a short circuit. An accurate short-circuit current value helps ensure the safety of power distribution equipment, prevent equipment damage due to overload, and ensure that the power grid can quickly recover in case of a fault;

[0069] The calculation formula for the system power flow value is as follows:

[0070]

[0071] The calculation of the system power flow value can reflect the energy flow and distribution in the power grid under different load conditions. This calculation provides key data for power system dispatching, ensuring that electricity is effectively and economically distributed between power plants and end-users. In the formula, P load represents the total active power of the system load, Gl L represents the power flow of the l-th branch, G represents the total number of branches connected to the power grid, and L represents the counting subscript. denotes the summation from L = 1 to G for all branches to obtain the total active power flow. By monitoring and analyzing the power flow, power operators can optimize power generation and transmission strategies, reduce energy losses, and thus lower operating costs. Accurate power flow calculations can also help identify potential system bottlenecks and support the intelligent dispatching and operation of the power grid;

[0072] The calculation formula for the power grid power stability coefficient is as follows:

[0073]

[0074] By analyzing the power stability coefficient, power companies can evaluate whether the power grid can maintain stable operation under specific loads and operating conditions, and predict possible voltage and frequency fluctuations, so as to take appropriate control measures. In the formula, Gwxs represents the power grid power stability coefficient, P new represents the updated power demand after loading, P old represents the power demand before loading, V new represents the adjusted voltage, V old represents the voltage in the initial state. Effective monitoring of the power stability coefficient helps reduce the risks brought by system instability, improve the reliability of the power grid, ensure stable power supply for a long time, and enhance user trust and satisfaction;

[0075] S4. Through the visualization display module, the real-time monitoring data and calculation results are presented in the forms of charts, maps, and dashboards to display the power grid operation status, and the power grid operation status includes current, voltage, power distribution, and real-time power load conditions;

[0076] This module utilizes the advanced data visualization technology WebGL to dynamically render high-quality charts and maps, presenting current, voltage, power distribution, and real-time load conditions in a vivid manner. Geographic Information System (GIS) technology can be used to construct a power grid topology map, achieving spatial visualization of real-time current and voltage distributions, and helping management personnel quickly identify hot issues and potential risks in the power grid;

[0077] The dashboard display presents key performance indicators in the form of real-time numbers and graphics, enabling operators to monitor the operating status of the power grid in real time and make timely adjustments. At the same time, the system provides more comprehensive background information for decision-making by loading historical data. During the impact assessment process of the new business expansion plan, real-time monitoring data and calculation results can help analyze the specific impact of the newly added load on the overall operation of the power grid, predict the load change trend and its potential impact on the power grid stability, and support power operators to take targeted measures to ensure the safe and stable operation of the power grid;

[0078] In addition, the system also integrates interactive functions. Users can customize data views according to their needs, select specific time ranges or nodes for detailed analysis, and quickly obtain the required information. This efficient visualization technology not only improves the management efficiency of the power system but also promotes communication and cooperation among relevant units, thereby providing strong support for the optimization, upgrading, and sustainable development of the power grid. Through the integration of these advanced technologies, the power system can handle complex and changing electricity demands with ease and improve the overall operation efficiency.

[0079] By applying the above methods, not only the high quality and more accurate fusion analysis of data are ensured, but also static data is transformed into dynamic information, overcoming the limitation that traditional visualization tools can only provide outdated information. With the calculation of short-term and long-term load forecasts, the system can provide a scientific basis for the load distribution of the power grid and the access plan of new users, thus effectively evaluating the impact of the newly added load on the overall safety and stability of the existing power grid.

[0080] Example 1:

[0081] In this experiment, by installing voltage sensors at different voltage nodes, the following node voltage data was collected. The initial voltage V of node A p,initial = 230V, the self-admittance Y of node A A = 5 - j10, the normal active power P of node A A = 40W, the normal reactive power Q of node A A = 10Var. According to the voltage node calculation formula, the voltage value of node A can be calculated:

[0082] V A = V A,initial -(Y A-1 *S A )*V A (1)

[0083] The self - admittance matrix is as follows:

[0084] Y A = 5 - j10

[0085] Calculate the extreme values of the admittance:

[0086]

[0087] The conjugate of the admittance:

[0088]

[0089] Calculate the product of power and admittance:

[0090] Y A -1 *S A =(0.04 + j0.08)*(40 + j10)

[0091] = 0.04*40+0.04*j10 + 0.08j*40 + j0.08*j10 = 0.08 + j3.6 Substitute into the voltage formula for calculation:

[0092] V A = V A,initial -(Y A -1 *S A ) = 230-(0.8 + j3.6)= 229.2 - j3.6

[0093] Amplitude calculation:

[0094]

[0095] Since the voltage node value is equal to 229.4V, and the normal voltage node value is 230V. Compared with the normal state, the voltage amplitude has decreased slightly (by about 0.8V). This situation usually means that there are potential problems in the power system, such as increased equipment load or uneven current flow in the network, resulting in voltage fluctuations. At this time, the visualization display module will display the calculated abnormal results on the electronic screen for power personnel to analyze;

[0096] Example 2:

[0097] In this experiment, by installing voltage sensors on different voltage nodes, the following node voltage data is collected. The initial voltage V of node A p,initial = 230V, the self - admittance Y of node A A= 5 - j10, the normal active power P of node A A = 20 W, the normal reactive power Q of node A A = 10 Var. According to the voltage node calculation formula, the voltage value of node A can be calculated as follows:

[0098] V A = V A,initial - (Y A -1 * S A ) * V A (1)

[0099] The self - admittance matrix is:

[0100] Y A = 5 - j10

[0101] Calculate the extreme value of the admittance:

[0102]

[0103] The conjugate of the admittance:

[0104]

[0105] Calculate the product of power and admittance:

[0106] Y A -1 * S A = (0.04 + j0.08) * (20 + j10)

[0107] = 0.04 * 20 + 0.04 * j10 + 0.08j * 20 + j0.08 * j10 = j2.0

[0108] Substitute into the voltage formula for calculation:

[0109] V A = V A,initial - (Y A -1 * S A ) = 230 - j2.0

[0110] Amplitude calculation:

[0111]

[0112] Since the voltage node value is approximately equal to 230 V, and the normal voltage node value is 230 V. Compared with the normal state, the voltage amplitude is in the normal state. This indicates that the power system is operating normally. At this time, the visualization display module will display the calculated normal results on the electronic screen.

[0113] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for visualizing power grid resources for a business expansion solution, characterized in that: The following steps are involved: S1. Collect power grid operation data, power grid topology data, user power load history data and business expansion plan data in real time through the power data acquisition unit; S2. Perform quality checks on power grid operation data, power grid topology data, user power load history data, and business expansion plan data through the power data processing unit, remove redundant data, apply data fusion technology to integrate power grid operation data, power grid topology data, user power load history data, and business expansion plan data from different sources into a unified format, use statistical analysis methods to analyze historical load data, predict future load change trends, and calculate short-term power grid load forecast values ​​and long-term power grid load forecast values; S3. After the data processing is completed, the power data analysis unit performs power flow calculation according to the short-term power grid load forecast value, the long-term power grid load forecast value and the topological structure of the power grid, obtains the voltage distribution of each power grid node and the current state of the branch, introduces the load demand of the new user, performs load distribution, evaluates the impact of the new load on the overall load of the power grid, and calculates the short-circuit current, system power flow value and power grid power stability coefficient; S4. The real-time monitoring data and calculation results are presented in the form of charts, maps, and dashboards through the visual display module to display the grid operation status, which includes current, voltage, power distribution, and real-time power load conditions.

2. According to claim 1, a method for visualizing power grid resources for a business expansion solution is characterized by: The formula for removing redundant data is as follows: In the formula, Cosine represents the cosine similarity value, A and B represent point vectors whose redundant data need to be removed, namely, power grid operation data or power grid topology data or user power load history data or business expansion plan data, A·B represents the point vector inner product, ||A|| represents the modulus of vector A, ||B|| represents the modulus of vector B, and ||A||*||B|| represents the length of the vector.

3. A method for visualizing power grid resources for a business expansion solution according to claim 2, characterized in that: The formula for integrating the data into a unified format is as follows: In the formula, Z represents the Z score, which is used to unify the grid operation data or grid topology data or user power load history data or business expansion plan data from different sources into the same data distribution standard, X represents the sample data point of the grid operation data or grid topology data or user power load history data or business expansion plan data to be checked, N represents the total number of grid operation data or grid topology data or user power load history data or business expansion plan data, and X i It represents the i-th data point in the data set of power grid operation data, power grid topology data, user power load history data, or business expansion plan data, where i represents the count subscript. It means adding all the values ​​in the grid operation data, grid topology data, user power load history data, or business expansion plan data to get the total of the data. It means calculating the square of the difference between each data point and the mean, and adding all the results to get the overall degree of dispersion. The square root sign represents the square root of the mean deviation, and the standard deviation is obtained.

4. The method for visualizing power grid resources for a business expansion solution according to claim 3, characterized in that: The calculation formula of the short-term power grid load forecast value is as follows: In the formula, L t+1 Represents the short-term grid load forecast value, L t-j is the actual load data of the past n moments, indicating the load value from the current time to the past. j ranges from 0 to n-1, representing the past n time points, and n represents the number of time points used to calculate the average. It means to calculate the total of the load values ​​at the past n time points by accumulating them. It means averaging the sum to get the predicted value at a future time point.

5. A method for visualizing power grid resources for a business expansion solution according to claim 4, characterized in that: The calculation formula of the long-term power grid load forecast value is as follows: L t =s+k*t+∈ In the formula, L t represents the long-term grid load forecast value, s represents the load value when the time factor is zero, k represents the rate at which the load changes over time, t represents the time variable, and ∈ is the error term, which represents the impact of other uncaptured variables.

6. A method for visualizing power grid resources for a business expansion solution according to claim 5, characterized in that: The voltage distribution calculation formula of the grid node is as follows: In the formula, V p Represents the voltage amplitude of the pth node, V p,initial represents the initial voltage prediction value, Y ph represents the self-admittance of the pth node, P p , Q p represents the active and reactive power requirements of the pth node, Y represents the node admittance matrix, Y pp -1 Represents the inverse of the p-th node self-admittance.

7. A method for visualizing power grid resources for a business expansion solution according to claim 6, characterized in that: The current state calculation formula of the branch is as follows: I f =Y f *(V j -Y i ) In the formula, I f represents the current flowing through branch f, Y f represents the admittance of the branch, V j 、V i Represents the voltage of the two nodes connecting branch f.

8. A method for visualizing power grid resources for a business expansion solution according to claim 7, characterized in that: The calculation formula of the short-circuit current is as follows: In the formula, I sc Indicates the value of short-circuit current, V base Represents the system reference voltage, Z th Indicates the equivalent impedance when short circuit occurs.

9. A method for visualizing power grid resources for a business expansion solution according to claim 8, characterized in that: The calculation formula of the system power flow value is as follows: In the formula, P load Indicates the total active power of the system load, Gl L represents the power flow of the Lth branch, G represents the total number of branches connected to the power grid, and L represents the count subscript. It means that the total active power flow is obtained by summing all branches from L=1 to G.

10. A method for visualizing power grid resources for a business expansion solution according to claim 9, characterized in that: The calculation formula of the power grid power stability coefficient is as follows: In the formula, Gwxs represents the power stability factor of the power grid, P new represents the updated power requirement after loading, P old Indicates the power requirement before loading, V new Represents the adjusted voltage, V old Indicates the voltage in the initial state.

Images