Cross-power-supply-area intelligent load adjusting method based on envelope method

Abstract

The invention discloses a cross-power-supply-area intelligent load adjusting method based on an envelope method, and relates to the technical field of power grids, and the method comprises the following steps: obtaining a standard load adjusting index and an index type of a power supply area according to basic parameters and historical operation data of each power supply area; according to the index type and the standard load adjustment index, constructing a load adjustment analysis model across the power supply areas; acquiring real-time operation data of transformers in all power supply areas; extracting the real-time operation data according to the standard load adjustment index to obtain a load adjustment detection index, a detection type and a real-time detection parameter; generating a load adjustment detection factor of the real-time operation data according to the load adjustment detection index; inputting the load adjustment detection factor into a load adjustment analysis model to obtain a target detection module corresponding to the load adjustment detection factor; the management level of the power distribution network is improved and the power supply reliability is ensured.

Description

Technical Field

[0001] This invention relates to the field of power grid technology, and more specifically, to a smart load adjustment method for cross-power supply areas based on the envelope method. Background Technology

[0002] Uneven load distribution among power distribution areas is a long-standing problem in power system operation. This leads to overloaded transformers in some areas and low load rates in others, affecting power quality, reducing equipment lifespan, and increasing power losses. Traditional load adjustment methods are mostly limited to individual power distribution areas, lacking cross-area collaborative optimization mechanisms and struggling to cope with complex grid operation scenarios. With the expansion of power system scale and the diversification of electricity demand, cross-power distribution area load coordination has become crucial for improving grid operation efficiency. However, existing technologies lack systematic indicator systems and analytical models for cross-area load adjustment, relying heavily on manual experience for decision-making, resulting in low adjustment accuracy and slow response. Furthermore, the lack of sufficient integration of basic parameters, historical operating data, and location information between power distribution areas leads to insufficient scientific validity and feasibility of load adjustment schemes. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention aims to provide an intelligent load adjustment method for cross-power supply areas based on the envelope method.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for intelligent load adjustment across power supply areas based on the envelope method, comprising the following steps: The standard load adjustment indicators and indicator types for each power supply area are obtained based on the basic parameters and historical operating data of each power supply area. Construct a cross-power supply area load adjustment analysis model based on index types and standard load adjustment indicators; Obtain real-time operating data of transformers in each power supply area; extract load adjustment detection indicators, detection types, and real-time detection parameters from the real-time operating data according to standard load adjustment indicators; Based on the load adjustment detection index, load adjustment detection factors for real-time operation data are generated; the load adjustment detection factors are input into the load adjustment analysis model to obtain the target detection module corresponding to the load adjustment detection factors; the load adjustment detection factors are compared and analyzed with the standard reference factors of the target detection module to obtain the load adjustment factors that exceed the standard and the load adjustment factors that are missing. The excessive and missing load adjustment factors are processed and analyzed to obtain the comprehensive load adjustment coefficient of the target detection module in real-time operation data; The transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between substations, and the power supply radius.

[0005] Preferably, the standard load adjustment index and index type of each power supply area are obtained based on the basic parameters and historical operating data of each power supply area, specifically including the following steps: Determine the routine load adjustment indicators for the power supply area based on the basic parameters; Determine the abnormal load adjustment indicators for the power supply area based on historical operating data; Both routine load adjustment indicators and abnormal load adjustment indicators are marked as standard load adjustment indicators for the power supply area. The index types include load rate index, voltage deviation index, power factor index, shortest distance between substations index, and power supply radius adaptation index for power supply areas.

[0006] Preferably, a load adjustment analysis model across power supply substations is constructed based on the index type and standard load adjustment index, specifically including the following steps: A cross-regional load adjustment detection system is constructed based on the index types of standard load adjustment indicators; Based on the type of indicator, the standard load adjustment indicators are divided into standard reference factors for the load adjustment detection system; A cross-power supply area load adjustment analysis model was constructed based on the load adjustment detection system and standard reference factors.

[0007] Preferably, the load adjustment detection factor is compared and analyzed with the standard reference factor of the target detection module to obtain the over-limit load adjustment factor and the missing load adjustment factor of the load adjustment detection factor, specifically including the following steps: Match the load adjustment detection factor with the standard reference factor of the target detection module; Mark the standard reference factors in the target detection module that do not match the load adjustment detection factors as missing load adjustment factors; Mark the standard reference factor in the target detection module that matches the load adjustment detection factor as the target reference factor; Mark the standard indicator parameters corresponding to the target reference factor as the target standard parameters; If the real-time detection parameters of the load adjustment detection factor do not meet the target standard parameters of the target reference factor, the load adjustment detection factor will be marked as an out-of-standard load adjustment factor.

[0008] Preferably, the excessive load adjustment factor and the missing load adjustment factor are processed and analyzed to obtain the comprehensive load adjustment coefficient of the real-time operating data in the target detection module, specifically including the following steps: The first load adjustment coefficient of the target detection module is obtained based on the analysis of the overload adjustment factor; The second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first and second load adjustment coefficients.

[0009] Preferably, the first load adjustment coefficient of the target detection module is obtained based on the overload adjustment factor analysis, specifically including the following steps: Set the index weights corresponding to the standard load adjustment indexes; among them, the regular load adjustment indexes correspond to regular weights; Calculate the parameter deviation between the real-time detection parameters of the overload adjustment factor and the target standard parameters of the target reference factor; and obtain the index weights corresponding to the overload adjustment factor. The factor adjustment coefficient of the over-limit adjustment factor is obtained based on the parameter deviation value and the index weight value; Obtain the total number of exceedance factors in the target detection module; The first load adjustment coefficient of the target detection module is obtained by summing the factor adjustment coefficients of the excess load adjustment factors in the target detection module based on the total number of excess factors.

[0010] Preferably, the second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis, specifically including the following steps: Obtain the index weights corresponding to the missing load adjustment factors, and mark the index weights as the factor load adjustment coefficients of the missing load adjustment factors; Obtain the total number of missing factors in the target detection module; The missing weight coefficient of the target detection module is obtained by summing the factor loading coefficients of the missing loading factors in the target detection module based on the total number of missing factors. Obtain the total number of standard factors for the standard reference factors in the target detection module; The missing detection ratio of missing load adjustment factors in the target detection module is obtained based on the total number of missing factors and the total number of standard factors. The missing percentage coefficient of real-time running data is obtained based on the missing detection percentage. The second load adjustment coefficient of the target detection module is obtained based on the missing weight coefficient and the missing proportion coefficient.

[0011] Preferably, the comprehensive load adjustment coefficient of the target detection module is obtained based on the first load adjustment coefficient and the second load adjustment coefficient, specifically including the following steps: Set the first load adjustment weight and the second load adjustment weight; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first load adjustment weight, the first load adjustment coefficient, the second load adjustment weight, and the second load adjustment coefficient.

[0012] Preferably, the transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between transformer substations, and the power supply radius, specifically including the following steps: The system weights of the target detection module are set according to the index types corresponding to the load adjustment detection system, and the system weights correspond to the index types; Based on the system weights of the target detection module and the comprehensive load adjustment coefficient of the target detection module in real-time operation data, the module load adjustment coefficient of the target detection module is obtained; The load adjustment coefficients of all detection modules in the load adjustment analysis model are accumulated to obtain the cross-station load adjustment coefficients corresponding to the real-time operating data. By combining the cross-regional load adjustment coefficient to calculate the shortest power supply path and the adaptation threshold of the power supply radius between power supply substations, and determining the load transfer ratio and load adjustment priority of each transformer, a cross-regional transformer load adjustment scheme is obtained.

[0013] Compared with the prior art, the present invention has the following beneficial effects: This invention determines standard load adjustment indicators and types by combining basic parameters and historical operating data of each power supply area. This comprehensively and accurately characterizes the operating characteristics of the power supply area, ensuring clear reference for load adjustment decisions and improving the targeting of load adjustment. A cross-power supply area load adjustment analysis model constructed based on indicator types and standard load adjustment indicators achieves systematic integration of multiple areas and multiple indicators. This model can effectively analyze real-time operating data, extract load adjustment detection indicators, types, and parameters, generate detection factors, and match target detection modules to identify excessive and missing load adjustment factors. This transforms load adjustment analysis from experience-driven to data-driven, significantly improving the accuracy and intelligence of load adjustment analysis. By processing and analyzing excessive and missing load adjustment factors, a comprehensive load adjustment coefficient is obtained. Combined with system weights, the shortest distance between substations, and the power supply radius, a transformer load adjustment scheme is determined, achieving the organic integration of electrical and geographical parameters. This effectively balances the load of each power supply area, reduces the risk of transformer overload, improves power supply voltage quality and power factor, and enhances the operating efficiency and stability of the entire power supply network. It also reduces equipment losses caused by uneven load distribution. This application aims to improve the management level of the power distribution network and ensure the reliability of power supply. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of an intelligent load adjustment method across power supply substations based on the envelope method proposed in this invention. Detailed Implementation

[0015] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0016] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0017] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0018] Reference Figure 1 As shown.

[0019] The embodiments further illustrate the intelligent load adjustment method for cross-power supply areas based on the envelope method proposed in this invention.

[0020] A method for intelligent load adjustment across power supply areas based on the envelope method, comprising the following steps: The standard load adjustment indicators and indicator types for each power supply area are obtained based on the basic parameters and historical operating data of each power supply area. Construct a cross-power supply area load adjustment analysis model based on index types and standard load adjustment indicators; Obtain real-time operating data of transformers in each power supply area; extract load adjustment detection indicators, detection types, and real-time detection parameters from the real-time operating data according to standard load adjustment indicators; Based on the load adjustment detection index, load adjustment detection factors for real-time operation data are generated; the load adjustment detection factors are input into the load adjustment analysis model to obtain the target detection module corresponding to the load adjustment detection factors; the load adjustment detection factors are compared and analyzed with the standard reference factors of the target detection module to obtain the load adjustment factors that exceed the standard and the load adjustment factors that are missing. The excessive and missing load adjustment factors are processed and analyzed to obtain the comprehensive load adjustment coefficient of the target detection module in real-time operation data; The transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between substations, and the power supply radius.

[0021] Based on the basic parameters and historical operating data of each power supply area, the standard load adjustment indicators and indicator types for each power supply area are obtained, specifically including the following steps: Determine the routine load adjustment indicators for the power supply area based on the basic parameters; Determine the abnormal load adjustment indicators for the power supply area based on historical operating data; Both routine load adjustment indicators and abnormal load adjustment indicators are marked as standard load adjustment indicators for the power supply area. The types of indicators include load rate indicators, voltage deviation indicators, power factor indicators, shortest distance between substations indicators, and power supply radius adaptation indicators for power supply areas.

[0022] The basic parameters of the power supply area are the basis for determining the regular load adjustment index. For example, if the rated capacity of the transformer in the power supply area is 500kVA, its regular load rate index range is determined according to the regular load rate requirements of the power industry. For example, the load rate should be maintained between 30% and 70% during normal operation. This is the regular load adjustment index determined based on the basic parameters, which is used to reflect the load adjustment demand of the area under normal operating conditions.

[0023] Historical operating data is used to determine abnormal load adjustment indicators. Suppose that a certain power supply area has experienced overload conditions by having its transformer load rate exceed 85% multiple times during historically hot weather. Based on this historical operating data, abnormal load adjustment indicators are determined. For example, a load rate exceeding 80% falls under the category of abnormal load adjustment indicators, which is used to make judgments on load adjustment under unconventional operating conditions.

[0024] By marking both routine and abnormal load adjustment indicators as standard load adjustment indicators for the power supply area, a complete load adjustment indicator system is constructed, including load adjustment reference standards under both normal and abnormal operating conditions.

[0025] The indicator types include load rate indicators, voltage deviation indicators, power factor indicators, shortest distance between transformer substations indicators, and power supply radius adaptation indicators. The load factor index reflects the degree of transformer load. For example, if a transformer has an actual load of 300kVA and a rated capacity of 500kVA, its load factor is 60%. This index helps determine whether the transformer load is within a reasonable range. The voltage deviation index measures the degree of deviation between the supply voltage and the rated voltage. For example, if the rated voltage is 220V and the actual voltage is 215V, the voltage deviation is (215-220) / 220×100%≈-2.27%. This helps determine whether the voltage is within the allowable deviation range. The power factor index reflects the energy utilization efficiency of the power supply system. If the power factor is too low, it indicates large reactive power loss, requiring reactive power compensation and load adjustment. The shortest distance between distribution substations refers to the shortest geographical distance between different power supply substations. For example, the straight-line distance between substation A and substation B is 2 kilometers. This index provides a geographical basis for selecting the power supply path when adjusting load across substations. The power supply radius adaptation index is used to determine whether the power supply radius is within a reasonable range. If the power supply radius is too large, it will lead to increased voltage loss, requiring optimization through load adjustment.

[0026] Based on the index type and standard load adjustment index, a load adjustment analysis model for cross-power supply areas is constructed, which includes the following steps: A cross-regional load adjustment detection system is constructed based on the index types of standard load adjustment indicators; Based on the type of indicator, the standard load adjustment indicators are divided into standard reference factors for the load adjustment detection system; A cross-power supply area load adjustment analysis model was constructed based on the load adjustment detection system and standard reference factors.

[0027] A cross-transformer load adjustment detection system is constructed based on standard load adjustment index types. For example, corresponding detection subsystems are built for five index types: load rate, voltage deviation, power factor, shortest distance between transformers, and power supply radius adaptation. Taking the load rate index as an example, its detection subsystem clearly defines the load rate collection method, detection frequency, and data processing rules. For instance, it stipulates that transformer load data is collected every 15 minutes, and the load is judged to be normal by comparing real-time data with standard load adjustment indexes.

[0028] Based on the index type, standard load adjustment indices are categorized into standard reference factors for the load adjustment detection system. For example, under the load rate index type, the range of 30%-70% for regular load adjustment indices and the threshold of over 80% for abnormal load adjustment indices become standard reference factors for that type. These standard reference factors serve as benchmarks for subsequent detection and comparison. The standard load adjustment indices under each index type are broken down into corresponding standard reference factors, providing the load adjustment detection system with specific reference bases.

[0029] A cross-power supply area load adjustment analysis model is constructed based on the load adjustment detection system and standard reference factors. This model integrates detection subsystems for all index types and their corresponding standard reference factors, forming a comprehensive analytical framework. When real-time operating data of transformers in each power supply area is input, the model matches the data to the corresponding detection subsystem based on the index type, and then compares the real-time data with the standard reference factors under that system. For example, if the real-time load rate of a transformer in a certain area is 75%, the model matches it to the load rate index detection subsystem and compares it with the normal reference factors (30%-70%) and abnormal reference factors (>80%) under that system to determine its status, thus providing support for subsequent load adjustment decisions.

[0030] The load adjustment detection factor is compared and analyzed with the standard reference factor of the target detection module to obtain the over-limit load adjustment factor and the missing load adjustment factor. The specific steps include: Match the load adjustment detection factor with the standard reference factor of the target detection module; Mark the standard reference factors in the target detection module that do not match the load adjustment detection factors as missing load adjustment factors; Mark the standard reference factor in the target detection module that matches the load adjustment detection factor as the target reference factor; Mark the standard indicator parameters corresponding to the target reference factor as the target standard parameters; If the real-time detection parameters of the load adjustment detection factor do not meet the target standard parameters of the target reference factor, the load adjustment detection factor will be marked as an out-of-standard load adjustment factor.

[0031] The load adjustment detection factor is matched with the standard reference factor of the target detection module. For example, if the real-time load rate of a transformer in a power supply area is 75%, the real-time load rate data is the load adjustment detection factor. It is matched with the standard reference factor of the target detection module corresponding to the load rate index. The standard reference factor is 30%-70% for normal and greater than 80% for abnormal. Then, it is determined which reference factor range the detection factor belongs to.

[0032] In the target detection module, standard reference factors that do not match the load adjustment detection factor are marked as missing load adjustment factors. For example, in the target detection module for load rate, standard reference factors include a normal range of 30%-70% and an anomaly range of >80%, while the real-time detection factor is 75%, which is neither a normal nor an anomaly. In this case, both of these standard reference factors can be marked as missing load adjustment factors. However, if the detection factor is 85%, which matches the anomaly >80% standard reference factor, then the normal range of 30%-70% is marked as a missing load adjustment factor.

[0033] In the target detection module, the standard reference factor that matches the load adjustment detection factor is marked as the target reference factor. Taking load rate as an example, if the detection factor is 85%, and it matches the standard reference factor of "anomaly > 80%", then the standard reference factor "anomaly > 80%" becomes the target reference factor. The standard indicator parameter corresponding to the target reference factor is marked as the target standard parameter. For example, the standard indicator parameter corresponding to the target reference factor "anomaly > 80%" is a load rate exceeding 80%.

[0034] If the real-time detection parameters of the load adjustment detection factor do not meet the target standard parameters of the target reference factor, the load adjustment detection factor is marked as an out-of-limit load adjustment factor. For example, if the target standard parameter of the target reference factor is a load rate > 80%, and the real-time detection parameter is 85%, which meets the target standard parameter, then it is not marked as out of limit. However, if the target standard parameter is a load rate ≤ 80%, and assuming a change in the normal anomaly classification, the real-time detection parameter is 85%, which does not meet the target standard parameter, then this load adjustment detection factor is marked as an out-of-limit load adjustment factor. This method can identify missing and out-of-limit situations in the load adjustment process, providing crucial information for the subsequent calculation of the comprehensive load adjustment coefficient and the formulation of the load adjustment scheme.

[0035] The excessive and missing load adjustment factors are processed and analyzed to obtain the comprehensive load adjustment coefficient of the target detection module in real-time operation data. The specific steps include: The first load adjustment coefficient of the target detection module is obtained based on the analysis of the overload adjustment factor; The second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first and second load adjustment coefficients.

[0036] The first load adjustment coefficient of the target detection module is obtained based on the overload adjustment factor analysis, specifically including the following steps: Set the index weights corresponding to the standard load adjustment indexes; among them, the regular load adjustment indexes correspond to regular weights; Calculate the parameter deviation between the real-time detection parameters of the overload adjustment factor and the target standard parameters of the target reference factor; and obtain the index weights corresponding to the overload adjustment factor. The factor adjustment coefficient of the over-limit adjustment factor is obtained based on the parameter deviation value and the index weight value; Obtain the total number of exceedance factors in the target detection module; The first load adjustment coefficient of the target detection module is obtained by summing the factor adjustment coefficients of the excess load adjustment factors in the target detection module based on the total number of excess factors.

[0037] Set the weights for the standard load adjustment indicators, with regular load adjustment indicators corresponding to regular weights. For example, a regular load adjustment indicator (such as a load rate of 30%-70%) is set to a regular weight of 0.6, and an abnormal load adjustment indicator (such as a load rate >80%) is set to an abnormal weight of 0.8.

[0038] Calculate the parameter deviation between the real-time detection parameters of the over-standard load adjustment factor and the target standard parameters of the target reference factor, and obtain the index weight corresponding to the over-standard load adjustment factor. Assuming the real-time detection parameter of a certain over-standard load adjustment factor is 85%, and the target standard parameter of the target reference factor is ≤80%, then the parameter deviation is 85%-80%=5%; simultaneously, the index weight corresponding to this over-standard load adjustment factor is 0.8, and it is assumed to be an abnormal load adjustment index.

[0039] The factor load adjustment coefficient for the excess load adjustment factor is obtained based on the parameter deviation value and the index weight value. The calculation formula is: Factor load adjustment coefficient = Parameter deviation value × Index weight value. Substituting the above data, we get the factor load adjustment coefficient = 5% × 0.8 = 0.04.

[0040] Obtain the total number of excess load factors in the target detection module. For example, if there are 2 excess load factors in the target detection module with load rate, then the total number of excess factors is 2.

[0041] The first load adjustment coefficient of the target detection module is calculated by summing the load adjustment coefficients of the excess load factors in the target detection module based on the total number of excess factors. Assuming that the load adjustment coefficient of another excess load factor is 0.03, then the first load adjustment coefficient = 0.04 + 0.03 = 0.07.

[0042] The second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis, specifically including the following steps: Obtain the index weights corresponding to the missing load adjustment factors, and mark the index weights as the factor load adjustment coefficients of the missing load adjustment factors; Obtain the total number of missing factors in the target detection module; The missing weight coefficient of the target detection module is obtained by summing the factor loading coefficients of the missing loading factors in the target detection module based on the total number of missing factors. Obtain the total number of standard factors for the standard reference factors in the target detection module; The missing detection ratio of missing load adjustment factors in the target detection module is obtained based on the total number of missing factors and the total number of standard factors. The missing percentage coefficient of real-time running data is obtained based on the missing detection percentage. The second load adjustment coefficient of the target detection module is obtained based on the missing weight coefficient and the missing proportion coefficient.

[0043] Obtain the index weights corresponding to the missing load adjustment factors and directly label them as the factor load adjustment coefficients of the missing load adjustment factors. For example, if a missing load adjustment factor belongs to a regular load adjustment index and its index weight is 0.5, then the factor load adjustment coefficient of the missing load adjustment factor is 0.5.

[0044] Obtain the total number of missing load factors in the target detection module. For example, if there are 3 missing load factors in a certain target detection module, then the total number of missing factors is 3.

[0045] The missing weight coefficient of the target detection module is calculated by summing the factor loading coefficients of the missing factors based on the total number of missing factors. If the factor loading coefficients of the three missing factors are 0.5, 0.4, and 0.3 respectively, then the missing weight coefficient = 0.5 + 0.4 + 0.3 = 1.2.

[0046] Obtain the total number of standard factors in the standard reference factors of the object detection module. For example, if the object detection module has 5 standard reference factors, then the total number of standard factors is 5.

[0047] The missing detection ratio of missing factors in the target detection module is obtained based on the total number of missing factors and the total number of standard factors. The calculation formula is: Missing detection ratio = Total number of missing factors ÷ Total number of standard factors. Substituting the data, the missing detection ratio is 3 ÷ 5 = 0.6.

[0048] The missing percentage coefficient of the real-time running data is obtained based on the missing detection percentage value. Here, the missing percentage coefficient is equal to the missing detection percentage value, that is, the missing percentage coefficient is 0.6.

[0049] The second load adjustment coefficient of the target detection module is obtained based on the missing weight coefficient and the missing percentage coefficient. The calculation formula is: Second load adjustment coefficient = Missing weight coefficient × Missing percentage coefficient. Substituting the data, we get the second load adjustment coefficient = 1.2 × 0.6 = 0.72.

[0050] The comprehensive load adjustment coefficient of the target detection module is obtained based on the first and second load adjustment coefficients, specifically including the following steps: Set the first load adjustment weight and the second load adjustment weight; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first load adjustment weight, the first load adjustment coefficient, the second load adjustment weight, and the second load adjustment coefficient.

[0051] A first load adjustment weight and a second load adjustment weight are set to measure the importance of the first load adjustment coefficient and the second load adjustment coefficient in the overall load adjustment coefficient. For example, based on the requirements of the load adjustment scenario, the first load adjustment weight is set to 0.6 and the second load adjustment weight is set to 0.4.

[0052] Based on the first load adjustment weight, the first load adjustment coefficient, the second load adjustment weight, and the second load adjustment coefficient, the comprehensive load adjustment coefficient of the real-time operating data in the target detection module is obtained. The calculation formula is: Comprehensive Load Adjustment Coefficient = First Load Adjustment Weight × First Load Adjustment Coefficient + Second Load Adjustment Weight × Second Load Adjustment Coefficient. Assuming the first load adjustment coefficient is 0.5 and the second load adjustment coefficient is 0.6, substituting these values ​​into the above formula yields the comprehensive load adjustment coefficient = 0.6 × 0.5 + 0.4 × 0.6 = 0.3 + 0.24 = 0.54.

[0053] By weighting and integrating the first load adjustment coefficient corresponding to the excess situation and the second load adjustment coefficient corresponding to the missing situation according to the set weights, the comprehensive impact of real-time operating data on load adjustment in the target detection module can be quantified in a comprehensive and reasonable manner. This provides key quantitative indicators for determining the subsequent cross-regional load adjustment scheme, enabling load adjustment decisions to consider both excess and missing factors, thereby improving the scientific nature and comprehensiveness of load adjustment.

[0054] The transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between transformer substations, and the power supply radius. The specific steps include: The system weights of the target detection module are set according to the index types corresponding to the load adjustment detection system, and the system weights correspond to the index types; Based on the system weights of the target detection module and the comprehensive load adjustment coefficient of the target detection module in real-time operation data, the module load adjustment coefficient of the target detection module is obtained; The load adjustment coefficients of all detection modules in the load adjustment analysis model are accumulated to obtain the cross-station load adjustment coefficients corresponding to the real-time operating data. By combining the cross-regional load adjustment coefficient to calculate the shortest power supply path and the adaptation threshold of the power supply radius between power supply substations, and determining the load transfer ratio and load adjustment priority of each transformer, a cross-regional transformer load adjustment scheme is obtained.

[0055] The system weights of the target detection modules are set according to the corresponding index types in the load adjustment detection system, with each weight corresponding to an index type. For example, the load rate index type has a significant impact on load adjustment decisions, so its system weight is set to 0.3; the voltage deviation index type has a system weight of 0.25; the power factor index type has a weight of 0.2; the shortest distance between transformer substations index type has a weight of 0.15; and the power supply radius adaptation index type has a weight of 0.1. These weights reflect the different levels of importance of different index types in the load adjustment system.

[0056] Based on the system weights of the target detection module and the comprehensive load adjustment coefficient of the real-time operating data, the module load adjustment coefficient of the target detection module is obtained. The calculation formula is: Module load adjustment coefficient = System weights × Comprehensive load adjustment coefficient. For example, assuming that the system weight of a target detection module (such as the load rate index module) is 0.3 and the comprehensive load adjustment coefficient is 0.5, then the module load adjustment coefficient of this module = 0.3 × 0.5 = 0.15.

[0057] The cross-regional load adjustment coefficient is obtained by summing the load adjustment coefficients of all detection modules in the load adjustment analysis model. For example, in addition to the load rate module mentioned above, there are also voltage deviation module (module load adjustment coefficient 0.125), power factor module (0.1), shortest distance between substations module (0.075), and power supply radius adaptation module (0.05). Then the cross-regional load adjustment coefficient = 0.15 + 0.125 + 0.1 + 0.075 + 0.05 = 0.5.

[0058] By combining the cross-regional load adjustment coefficient to calculate the shortest power supply path and the matching threshold of the power supply radius between power supply substations, the load transfer ratio and load adjustment priority of each transformer are determined to obtain the cross-regional transformer load adjustment scheme. For example, if the cross-regional load adjustment coefficient is 0.5, it indicates that the overall load adjustment demand is at a medium level. In this case, the shortest power supply path between substation A and substation B is calculated. If the distance is close and the power supply radius matching threshold meets the requirements, part of the load of the transformer with a high load rate in substation A is transferred to the transformer in substation B. The load transfer ratio is determined according to the overload and underload status of each transformer. For example, if the load rate of a transformer in substation A exceeds the standard, 30% of the load needs to be transferred. The load adjustment priority is determined according to the load adjustment coefficient and equipment importance. For example, the load of transformers in densely populated residential power supply areas is adjusted first, and then the commercial substations are processed. Finally, a complete cross-regional transformer load adjustment scheme is formed.

[0059] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0060] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent load adjustment across power supply areas based on the envelope method, characterized in that, The method includes the following steps: The standard load adjustment indicators and indicator types for each power supply area are obtained based on the basic parameters and historical operating data of each power supply area. Construct a cross-power supply area load adjustment analysis model based on index types and standard load adjustment indicators; Obtain real-time operating data of transformers in each power supply area; extract load adjustment detection indicators, detection types, and real-time detection parameters from the real-time operating data according to standard load adjustment indicators; Based on the load adjustment detection index, load adjustment detection factors for real-time operation data are generated; the load adjustment detection factors are input into the load adjustment analysis model to obtain the target detection module corresponding to the load adjustment detection factors; the load adjustment detection factors are compared and analyzed with the standard reference factors of the target detection module to obtain the load adjustment factors that exceed the standard and the load adjustment factors that are missing. The excessive and missing load adjustment factors are processed and analyzed to obtain the comprehensive load adjustment coefficient of the target detection module in real-time operation data; The transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between substations, and the power supply radius.

2. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 1, characterized in that, Based on the basic parameters and historical operating data of each power supply area, the standard load adjustment indicators and indicator types for each power supply area are obtained, specifically including the following steps: Determine the routine load adjustment indicators for the power supply area based on the basic parameters; Determine the abnormal load adjustment indicators for the power supply area based on historical operating data; Both routine load adjustment indicators and abnormal load adjustment indicators are marked as standard load adjustment indicators for the power supply area. The index types include load rate index, voltage deviation index, power factor index, shortest distance between substations index, and power supply radius adaptation index for power supply areas.

3. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 1, characterized in that, Based on the index type and standard load adjustment index, a load adjustment analysis model for cross-power supply areas is constructed, which includes the following steps: A cross-regional load adjustment detection system is constructed based on the index types of standard load adjustment indicators; Based on the type of indicator, the standard load adjustment indicators are divided into standard reference factors for the load adjustment detection system; A cross-power supply area load adjustment analysis model was constructed based on the load adjustment detection system and standard reference factors.

4. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 3, characterized in that, The load adjustment detection factor is compared and analyzed with the standard reference factor of the target detection module to obtain the over-limit load adjustment factor and the missing load adjustment factor. The specific steps include: Match the load adjustment detection factor with the standard reference factor of the target detection module; Mark the standard reference factors in the target detection module that do not match the load adjustment detection factors as missing load adjustment factors; Mark the standard reference factor in the target detection module that matches the load adjustment detection factor as the target reference factor; Mark the standard indicator parameters corresponding to the target reference factor as the target standard parameters; If the real-time detection parameters of the load adjustment detection factor do not meet the target standard parameters of the target reference factor, the load adjustment detection factor will be marked as an out-of-standard load adjustment factor.

5. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 4, characterized in that, The excessive and missing load adjustment factors are processed and analyzed to obtain the comprehensive load adjustment coefficient of the target detection module in real-time operation data. The specific steps include: The first load adjustment coefficient of the target detection module is obtained based on the analysis of the overload adjustment factor; The second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first and second load adjustment coefficients.

6. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 5, characterized in that, The first load adjustment coefficient of the target detection module is obtained based on the overload adjustment factor analysis, specifically including the following steps: Set the index weights corresponding to the standard load adjustment indexes; among them, the regular load adjustment indexes correspond to regular weights; Calculate the parameter deviation between the real-time detection parameters of the overload adjustment factor and the target standard parameters of the target reference factor; and obtain the index weights corresponding to the overload adjustment factor. The factor adjustment coefficient of the over-limit adjustment factor is obtained based on the parameter deviation value and the index weight value; Obtain the total number of exceedance factors in the target detection module; The first load adjustment coefficient of the target detection module is obtained by summing the factor adjustment coefficients of the excess load adjustment factors in the target detection module based on the total number of excess factors.

7. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 5, characterized in that, The second load adjustment coefficient of the target detection module is obtained based on the missing load adjustment factor analysis, specifically including the following steps: Obtain the index weights corresponding to the missing load adjustment factors, and mark the index weights as the factor load adjustment coefficients of the missing load adjustment factors; Obtain the total number of missing factors in the target detection module; The missing weight coefficient of the target detection module is obtained by summing the factor loading coefficients of the missing loading factors in the target detection module based on the total number of missing factors. Obtain the total number of standard factors for the standard reference factors in the target detection module; The missing detection ratio of missing load adjustment factors in the target detection module is obtained based on the total number of missing factors and the total number of standard factors. The missing percentage coefficient of real-time running data is obtained based on the missing detection percentage. The second load adjustment coefficient of the target detection module is obtained based on the missing weight coefficient and the missing proportion coefficient.

8. The intelligent load adjustment method across power supply areas based on the envelope method according to claim 7, characterized in that, The comprehensive load adjustment coefficient of the target detection module is obtained based on the first and second load adjustment coefficients, specifically including the following steps: Set the first load adjustment weight and the second load adjustment weight; The comprehensive load adjustment coefficient of the target detection module is obtained based on the first load adjustment weight, the first load adjustment coefficient, the second load adjustment weight, and the second load adjustment coefficient.

9. A method for intelligent load adjustment across power supply areas based on the envelope method according to claim 8, characterized in that, The transformer load adjustment scheme is determined based on the comprehensive load adjustment coefficient, the system weight of the target detection module, the shortest distance between transformer substations, and the power supply radius. The specific steps include: The system weights of the target detection module are set according to the index types corresponding to the load adjustment detection system, and the system weights correspond to the index types; Based on the system weights of the target detection module and the comprehensive load adjustment coefficient of the target detection module in real-time operation data, the module load adjustment coefficient of the target detection module is obtained; The load adjustment coefficients of all detection modules in the load adjustment analysis model are accumulated to obtain the cross-station load adjustment coefficients corresponding to the real-time operating data. By combining the cross-regional load adjustment coefficient to calculate the shortest power supply path and the adaptation threshold of the power supply radius between power supply substations, and determining the load transfer ratio and load adjustment priority of each transformer, a cross-regional transformer load adjustment scheme is obtained.

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