Zone area line loss evaluation method, device and equipment fusing photovoltaic multi-dimensional characteristics

Abstract

The invention provides a transformer area line loss evaluation method, device and equipment fusing photovoltaic multi-dimensional features, and relates to the technical field of power systems. The method comprises the steps of screening a typical transformer area from a to-be-evaluated area based on a predetermined line loss characteristic evaluation index; traversing and calculating all nodes representing the typical courts in the day, and obtaining a traversing data set of each node in all target courts; the target court is any court in the typical courts; based on the traversal data set of each node in all the target areas, determining the voltage of each node in all the target areas and the power distribution of branches; based on the voltage and power distribution of each node in all the target areas, determining increase and decrease inflection points of the influence of all the target indexes on the line loss; the target index is any index in the line loss characteristic evaluation indexes; and based on the increase and decrease inflection points of the influence of all the target indexes on the line loss, constructing a multi-dimensional quantitative evaluation model, and evaluating the line loss of the typical transformer area. The evaluation accuracy can be improved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, apparatus and equipment for evaluating line loss in transformer substations that integrates the multi-dimensional characteristics of photovoltaics. Background Technology

[0002] With the rapid advancement of new power system construction, the penetration rate of distributed photovoltaic (PV) power in distribution networks is continuously increasing. This has led to significant changes in the structural and operational characteristics of distribution network areas, transforming them from passive to active networks, and changing the flow direction of branch power from unidirectional to bidirectional. Factors such as the capacity, location, number of connected PV systems, and spatial coupling characteristics of source and load all affect the line loss of distribution areas, potentially reducing or increasing losses.

[0003] Currently, the evaluation methods for line losses in photovoltaic (PV) distribution areas mainly include assessments based on single PV characteristic parameters and assessments based on the ratio of PV power generation to the area's load power consumption. Single PV characteristic parameters, such as grid connection capacity and location, are analyzed to depict the evolution of line losses under parameter variations by examining their intrinsic correlation with the area's line losses. Assessments based on the ratio of PV power generation to the area's load power consumption reveal the changing patterns of the line loss rate from a supply-demand balance perspective. Both methods provide in-depth analysis of the line loss assessment problem and have achieved certain results.

[0004] However, the two assessment methods mentioned above consider only a few factors and fail to effectively assess the increase or decrease of line loss in the distribution area, making it difficult to solve the problems of high difficulty and low accuracy in assessing line loss in the distributed photovoltaic access scenario. Summary of the Invention

[0005] This invention provides a method, apparatus, and equipment for evaluating line loss in photovoltaic power distribution areas by integrating multi-dimensional characteristics, in order to solve the problems of high difficulty and low accuracy in current line loss assessment of photovoltaic power distribution areas.

[0006] In a first aspect, embodiments of the present invention provide a method for evaluating line loss in photovoltaic distribution areas that integrates multi-dimensional characteristics, including:

[0007] Based on predetermined line loss characteristic evaluation indicators, typical transformer substations are selected from the area to be evaluated.

[0008] Traverse and calculate all nodes representing typical transformer areas within the day to obtain the traversal dataset of all nodes in the target transformer area; the target transformer area is any one of the typical transformer areas.

[0009] Based on the traversal dataset of all nodes in all target transformer areas, determine the voltage and branch power distribution of each node in all target transformer areas.

[0010] Based on the voltage and branch power distribution of each node in all target transformer areas, determine the inflection points of increase or decrease of the impact of all target indicators on line loss; the target indicator is any one of the line loss characteristic evaluation indicators.

[0011] Based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed to evaluate the line loss of typical transformer areas.

[0012] Secondly, embodiments of the present invention provide a transformer substation line loss evaluation device that integrates multi-dimensional photovoltaic characteristics, comprising:

[0013] The screening module is used to screen typical transformer substations from the area to be evaluated based on pre-determined line loss characteristic evaluation indicators.

[0014] The data acquisition module is used to traverse and calculate all nodes of a typical transformer area representing the day, and obtain the traversed dataset of each node in all target transformer areas; the target transformer area is any one of the typical transformer areas.

[0015] The first determining module is used to determine the voltage and branch power distribution of each node in all target transformer areas based on the traversal dataset of each node in all target transformer areas.

[0016] The second determining module is used to determine the inflection point of the increase or decrease of the impact of all target indicators on line loss based on the voltage and power distribution of each node and branch in all target areas; the target indicator is any one of the line loss characteristic evaluation indicators.

[0017] The evaluation module is used to construct a multi-dimensional quantitative evaluation model based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, and to evaluate the line loss of typical transformer areas.

[0018] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation thereof.

[0019] In this embodiment of the invention, firstly, predetermined line loss characteristic evaluation indicators are selected, and typical transformer substations are screened from the area to be evaluated. Next, all nodes of the typical substations representing the day are traversed and calculated to obtain the traversal dataset of each node within all target substations. Then, based on the traversal dataset of each node within all target substations, the voltage and branch power distribution of each node within all target substations are determined. Then, based on the voltage and branch power distribution of each node within all target substations, the inflection points of increase or decrease in the impact of all target indicators on line loss are determined. Finally, based on the inflection points of increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed to evaluate the line loss of typical substations. To overcome the limitations of traditional 'single electrical indicator evaluation' of substation line loss, this invention selects multiple target indicators, which constitute the line loss characteristic evaluation indicators. This invention first screens out typical substations with broad coverage and strong representativeness based on the determined line loss characteristic evaluation indicators. By acquiring the voltage and branch power distribution data for each node within all target transformer areas, the inflection point of each target indicator's impact on line loss can be accurately determined based on the actual operating conditions of the transformer area. Furthermore, based on the inflection points of all target indicators' impact on line loss, a multi-dimensional quantitative evaluation model can be constructed, thereby enabling accurate evaluation of the transformer area's line loss. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the implementation of the photovoltaic line loss evaluation method that integrates multi-dimensional photovoltaic features, as provided in this embodiment of the invention.

[0021] Figure 2 This is a schematic diagram of the line loss characteristic evaluation index provided in the embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the photovoltaic access location provided in an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram of the photovoltaic equivalent center and the user load equivalent center provided in the embodiments of the present invention;

[0024] Figure 5 This is a schematic diagram of the transformer area topology provided in an embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram illustrating the trend of the influence of photovoltaic penetration rate on line loss provided in an embodiment of the present invention;

[0026] Figure 7 This is a schematic diagram illustrating the influence trend of the power generation absorption ratio on line loss provided in an embodiment of the present invention;

[0027] Figure 8 This is a schematic diagram illustrating the trend of the impact of the highest load ratio on line loss provided in an embodiment of the present invention;

[0028] Figure 9 This is a schematic diagram illustrating the influence trend of the access location coefficient on line loss provided in an embodiment of the present invention;

[0029] Figure 10 This is a schematic diagram illustrating the influence trend of source-load center deviation on line loss provided in an embodiment of the present invention;

[0030] Figure 11 This is a schematic diagram of the structure of the photovoltaic power distribution area line loss evaluation device that integrates multi-dimensional photovoltaic features provided in an embodiment of the present invention;

[0031] Figure 12 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0032] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0033] As described in the background section, current line loss assessment in distribution transformer areas faces numerous challenges. On the one hand, the assessment is difficult, requiring the collection of massive amounts of operational data, involving multiple monitoring nodes and long-term data acquisition. Data processing and analysis are complex and cumbersome, demanding high levels of technical expertise and computational resources from professionals, resulting in lengthy assessment cycles and hindering timely support for power grid company decision-making. On the other hand, the assessment models suffer from poor adaptability. Due to a lack of comprehensive consideration of the complex relationships between multiple parameters, the models lack adaptability and generalization ability to actual operating conditions, and their accuracy is low. Furthermore, existing assessment methods fail to comprehensively consider the coupled effects of multiple characteristic parameters such as photovoltaic grid connection capacity, grid connection location, power generation, and load characteristics. They also fail to construct a comprehensive assessment system encompassing the synergistic effects and complex mapping relationships of multiple parameters, making it difficult to effectively grasp line loss trends and leading to discrepancies between assessment results and actual conditions.

[0034] Therefore, effectively assessing the impact of distributed photovoltaic (PV) grid connection on distribution transformer line losses is of great significance for guiding power grid companies in formulating loss reduction strategies and distribution transformer upgrade plans.

[0035] See Figure 1 The document illustrates a flowchart of the implementation of the photovoltaic power distribution line loss evaluation method integrating multi-dimensional photovoltaic features provided in this embodiment of the invention, detailed below:

[0036] S110. Based on predetermined line loss characteristic evaluation indicators, select typical transformer substations from the area to be evaluated.

[0037] In some embodiments, such as Figure 2As shown, the line loss characteristic evaluation indicators include photovoltaic penetration rate, power generation absorption ratio, peak load ratio, grid connection location coefficient, and source-load center deviation. These five line loss characteristic evaluation indicators are deeply correlated with five dimensions: capacity matching degree, absorption balance degree, peak load coordination degree, grid connection location, and source-load spatial coupling deviation.

[0038] Photovoltaic penetration rate is the ratio of photovoltaic grid connection capacity to distribution transformer capacity in the distribution area; power generation absorption ratio is the ratio of photovoltaic grid-connected electricity to user electricity consumption; peak load ratio is the ratio of peak photovoltaic output to peak user load; grid connection location coefficient is the ratio of photovoltaic grid connection capacity within 20% of the power supply distance to the total photovoltaic grid connection capacity in the distribution area; source-load center deviation is the spatial coupling deviation between the equivalent center of photovoltaic power generation and the equivalent center of user load in the distribution area.

[0039] In this embodiment, photovoltaic penetration rate refers to the ratio of photovoltaic grid connection capacity to the distribution transformer capacity in the distribution area, reflecting the capacity matching degree between photovoltaic grid connection capacity and distribution transformer capacity. Its expression is:

[0040]

[0041] Where ε represents photovoltaic penetration rate, S T S represents the transformer capacity of the distribution area. PV Represents the photovoltaic (PV) grid connection capacity, and its value is equal to the sum of the total PV capacity of the entire distribution area, i.e., S. PV =S PV1 +S PV2 +...+S PVN (where N is the number of photovoltaic grid connections).

[0042] The power generation absorption ratio (GEP) is the ratio of the amount of photovoltaic (PV) electricity fed into the grid to the amount of electricity consumed by users. It reflects the balance of power generation and is typically used to assess the grid's capacity to absorb PV power. Its expression is:

[0043]

[0044] Where θ represents the power generation absorption ratio, S G This represents the amount of photovoltaic power generated and fed into the grid. Its value is equal to the sum of all photovoltaic power generation in the distribution area, i.e., S. G =S G1 +S G2 +...+S GM M represents the number of photovoltaic cells connected to the grid; S U This represents the user's electricity consumption, and its value is equal to the sum of the electricity consumption of all users in the distribution area, i.e., S. G =S G1 +S G2 +...+S GN N is the number of users.

[0045] The peak load ratio is the ratio of peak photovoltaic (PV) power output to peak user load. It reflects the PV power generation's ability to cover peak electricity demand. The higher the ratio, the stronger the PV's peak-shaving capability, and the lower the dependence of users in the distribution area on the power grid. Its expression is:

[0046]

[0047] Where η represents the peak load ratio, P G P represents the peak photovoltaic output, and its value is taken as the maximum value representing the daily photovoltaic output; U This represents the peak user load, and its value is the maximum value representing the daily user load.

[0048] The access location coefficient refers to the ratio of the photovoltaic access capacity within 20% of the power supply distance to the total photovoltaic access capacity of the entire distribution area. Its expression is:

[0049]

[0050] Where Δ represents the access location coefficient, S 20％ S represents the photovoltaic grid connection capacity within 20% of the power supply distance. PV Represents the photovoltaic (PV) grid connection capacity, and its value is equal to the sum of the total PV capacity of the entire distribution area, i.e., S. PV =S PV1 +S PV2 +...+S PVN N represents the number of photovoltaic (PV) connections.

[0051] Based on the distance to the power supply, the access location can be divided into three distinct categories: front-end, end-end, and others. Front-end refers to a photovoltaic access point that is very close to the transformer in a complete transformer substation topology, such as... Figure 3 As shown at point A. The term "end" indicates that in a complete transformer substation topology, the photovoltaic access point is far from the transformer, as shown in the example. Figure 3 Point B is shown in the diagram. To quantify the photovoltaic access locations described by front-end and end-end: those within 20% of the power supply distance are defined as front-end access, and those beyond 80% of the power supply distance are defined as end-end access.

[0052] In this embodiment, the deviation value of the target line can first be determined based on the ratio of the distance between the photovoltaic equivalent center of the target line and the transformer to the distance between the equivalent center of the user load and the transformer. Here, the target line is any line within the target distribution area.

[0053] Then, based on the square root of the sum of the squares of the deviation values ​​of all target lines in the target transformer area, the source-load center deviation of the target transformer area is determined.

[0054] Specifically, the source-load center deviation describes the spatial coupling deviation between the equivalent center of photovoltaic (PV) power generation and the equivalent center of user load within a distribution area. The calculation approach is as follows: The entire distribution area is broken down into distributed PV and user loads based on a single line. The equivalent center of PV and the equivalent center of user load are calculated for each single line, and the distance deviation between them is calculated. Finally, the deviation results of all lines are combined to form the overall deviation value for the entire distribution area, which is used as the source-load center deviation value for the area. A detailed algorithm illustration is shown below. Figure 4 As shown,

[0055] Taking line 1 as an example, the deviation value of this line, that is, the ratio of the photovoltaic equivalent center to the user load equivalent center, is calculated as follows:

[0056]

[0057] Where L1 is the distance between the photovoltaic equivalent center and the transformer, and L2 is the distance between the user load equivalent center and the transformer; ζ is the source-load center deviation, reflecting the physical proximity of the two. A value of 100% indicates that the two overlap, and electrical energy does not need to be transmitted over long distances, at which point the line loss is minimal. The larger the ζ value is than or less than 100%, the greater the deviation, and the greater the line loss.

[0058] Using the same method, the deviation value of line 2 is calculated, and ζ1 and ζ2 of the two lines are obtained. Then, the source-load center deviation value of the entire transformer area can be obtained, and its expression is:

[0059]

[0060] Based on these five line loss characteristic evaluation indicators, typical transformer substations can be selected from the area to be evaluated.

[0061] By encompassing five dimensions of evaluation indicators—capacity matching, absorption balance, peak load coordination, access location coefficient, and source-load spatial coupling deviation—this method achieves a first-ever comprehensive 'capacity-time-space' coupled evaluation, overcoming the limitations of traditional 'single electrical indicator evaluation' of transformer substation line loss. It considers more comprehensive factors and employs a more scientific evaluation method.

[0062] In addition, in order to accurately reflect the degree of matching between photovoltaic and load in spatial distribution and to achieve a quantitative assessment of spatial synergy, the physical location relationship is also transformed into a quantifiable index, thus obtaining the source-load spatial coupling deviation.

[0063] S120: Traverse and calculate all nodes representing typical substations within the day to obtain the traversal dataset of all nodes within all target substations.

[0064] The representative date plays a crucial role in theoretical line loss calculation. By scientifically and rationally selecting a representative date and using its operational data as a basis for theoretical line loss calculation, the power grid line loss situation can be assessed efficiently and accurately. The representative date is determined according to the principles of moderate load level, stable operation mode, and complete data records.

[0065] A moderate load level means selecting dates when the load is within the normal fluctuation range, avoiding special situations where the load is extremely low or high, so as to ensure that the load level can better reflect the daily operating status of the transformer area.

[0066] Stable operation means that the operation mode of the power grid should remain relatively stable, without large-scale maintenance, renovation or equipment switching operations, so as to ensure that the power grid parameters and operating status are more repeatable and analyzable, and facilitate accurate calculation of line losses.

[0067] Complete data records mean that the representative must have complete and accurate operating data, including voltage, current, power, power generation, and power consumption, and the time interval of the data records should meet the calculation requirements to ensure that the load changes and power flow distribution can be accurately depicted.

[0068] After determining the representative date for calculation, we can traverse all nodes within all target transformer areas to obtain the traversed dataset. Here, the target transformer area is any one of the typical transformer areas.

[0069] In some embodiments, the traversal dataset includes the transformer substation topology, operational data, and photovoltaic resource distribution. The transformer substation topology includes radial, ring, and trunk patterns. In this embodiment, the most common radial pattern is selected.

[0070] Operational data includes electricity consumption by end users and transformer operation data. Transformer operation data refers to the daily representative data of current, voltage, active power, and reactive power at the low-voltage side outlet of the distribution transformer, collected every 15 minutes.

[0071] The distribution of photovoltaic resources includes the number of photovoltaic units connected to the grid in the area, the grid capacity, and the grid location.

[0072] S130. Based on the traversal dataset of all nodes in all target transformer areas, determine the voltage and branch power distribution of each node in all target transformer areas.

[0073] In some embodiments, power flow equations can first be constructed based on a traversal dataset of all nodes within all target transformer areas. Then, the power flow equations are solved using the Newton-Raphson power flow method to obtain the voltage and branch power distribution of each node within all target transformer areas.

[0074] In this embodiment, the power flow equations are often nonlinear and cannot be solved directly, thus requiring a numerical method for solving nonlinear equations. The Newton-Raphson method is characterized by strong convergence and high accuracy. Its core idea is to transform the power flow equations into a nonlinear algebraic equation system and then iteratively approximate the final solution.

[0075] The steps for calculating line loss in a transformer substation using the Newton-Raphson method are as follows:

[0076] 1) Data Initialization: Input the transformer topology, node parameters, and branch parameters. Initialize the node voltages, typically setting the PQ node voltage to 1∠0°, the PV node voltage to its rated voltage, and the Slack node voltage as the reference node.

[0077] 2) Power flow equation calculation: Calculate the injected power of each node based on the node voltage, and calculate the power imbalance.

[0078] 3) Jacobian matrix calculation: Calculate the Jacobian matrix based on the current node voltage.

[0079] 4) Solving the linear equation system: Solve the linear equation system J*Δx=-F, where Δx is the voltage correction amount.

[0080] 5) Voltage update: Update the node voltage according to the voltage correction amount: x^(k+1)=x^(k)+Δx.

[0081] 6) Convergence check: Determine if the convergence criterion is met, for example, check if the maximum value of the power imbalance is less than a preset threshold. If the convergence criterion is met, the algorithm ends; otherwise, return to step 2 and continue iterating.

[0082] S140. Based on the voltage and branch power distribution of each node in all target transformer areas, determine the inflection points of the increase or decrease of the impact of all target indicators on line loss.

[0083] The target indicator is any one of the line loss characteristic evaluation indicators.

[0084] In some embodiments, the voltage and power distribution of each node in all target transformer areas can be analyzed based on the control variable method to determine the inflection point of the increase or decrease of the impact of all target indicators on line loss.

[0085] In this embodiment, the impact on line loss is observed by fixing other characteristic variables and changing only a single variable. Its common mathematical expression is as follows: Suppose the dependent variable Y is affected by independent variables x1, x2, ..., xn. The controlled variable method studies the relationship Y = f(x1) by fixing x2, ..., xn.

[0086] Specifically, a controlled variable test was conducted on indicator 1 – photovoltaic penetration rate. The photovoltaic penetration rate was changed while the other four characteristic indicators remained the same, thus quantifying the impact of photovoltaic penetration rate on the line loss of the transformer area.

[0087] Controlled variable tests were conducted on feature 2 - the power generation absorption ratio. The power generation absorption ratio was changed while the other four feature indicators were kept the same, and the impact of the power generation absorption ratio on the line loss of the transformer area was quantified.

[0088] A controlled variable test was conducted on characteristic 3 - the maximum load ratio. The maximum load ratio was changed while the other four characteristic indicators were kept the same, thus quantifying the impact of the maximum load ratio on the line loss of the transformer area.

[0089] Controlled variable tests were conducted on feature 4 – access location coefficient – ​​while changing the access location coefficient and keeping the other four feature indicators the same, to quantify the impact of the access location coefficient on the line loss of the transformer area.

[0090] Controlled variable tests were conducted on characteristic 5 – source-load center deviation – while changing the source-load center deviation and ensuring that the other four characteristic indicators remained the same, to quantify the impact of load center deviation on line loss in the transformer area.

[0091] S150. Based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed to evaluate the line loss of typical transformer areas.

[0092] In some embodiments, a target indicator evaluation function can be constructed first, based on the inflection point of the target indicator's impact on line loss and the weight of the target indicator.

[0093] Then, based on the sum of all target indicator evaluation functions, a multi-dimensional quantitative evaluation model is constructed.

[0094] Finally, based on a multi-dimensional quantitative evaluation model, the line loss of typical transformer substations is evaluated.

[0095] In this embodiment, the numerical values ​​of the line loss characteristic evaluation index of the target transformer area can be input into the multi-dimensional quantitative evaluation model to obtain the degree of increased loss of the target transformer area.

[0096] Then, based on the loss increase values ​​of all target transformer areas and the preset loss increase evaluation rules, the line loss of all target transformer areas is evaluated.

[0097] Specifically, by identifying the inflection points of increase or decrease in the impact of each target indicator on line loss, the target indicators can be directly divided into intervals based on these inflection points, and reference values ​​for each target indicator can be determined based on these inflection points. The weight of each target indicator is determined through expert scoring.

[0098] When determining the reference value for each target indicator based on the inflection points of increase or decrease, one of the inflection point values ​​can be directly used as the reference value, or the reference value can be determined based on the average value of the inflection points; no limitation is made here. The weights and reference values ​​of the line loss characteristic evaluation indicators are shown in Table 1 below:

[0099] Table 1. Weights of Feature Indicators and Algorithm Principles

[0100]

[0101] Among them, Ψ i (i = 1, 2, ..., 5) represent the weight of each characteristic indicator in the online loss evaluation system, expressed as a percentage, and they satisfy the following relationship:

[0102] Ψ1+Ψ2+Ψ3+Ψ4+Ψ5=100%;

[0103] δ i (i = 1, 2, ..., 5) represents the reference value for each indicator. The selection of this value is determined by the inflection point of increase or decrease of each target indicator. Finally, the multi-dimensional quantitative evaluation model is constructed as follows:

[0104] F(x i )=[(ε-δ1)*Ψ1+(θ-δ2)*Ψ2+(η-δ3)*Ψ3+(Δ-δ4)*Ψ4+|(ζ-δ5)|*Ψ5]*100

[0105] Where, x i (i = 1, 2, ..., n) represents the i-th selected photovoltaic area, F(x i ) represents the degree of increase or decrease in the i-th photovoltaic area. According to F(x) i The calculation results show that the impact of distributed photovoltaic (PV) grid connection on line losses in transformer substations can be divided into two categories: increased losses and decreased losses.

[0106]

[0107] To fully assess the severity of losses in a transformer substation and guide its loss reduction upgrades, it is possible to base decisions on F(x). i The numerical values ​​are used to categorize the evaluation results into three types: slight increase / decrease, moderate increase / decrease, and severe increase / decrease. The classification is based on the following formula:

[0108]

[0109] To facilitate understanding, a specific example will be used for illustration:

[0110] First, based on the line loss characteristic evaluation index, typical transformer substations with broad coverage and strong representativeness were selected. The seven selected typical transformer substations are shown in Table 2:

[0111] Table 2 shows the typical transformer substations selected.

[0112]

[0113] Next, adhering to the principles of moderate load levels, stable operation, and complete data recording, two representative calculation days were selected in summer and two in winter, representing summer with and without solar power, and winter with and without solar power, respectively. All nodes in the distribution area were traversed to obtain the area's topology, operational data, and solar resource distribution. Taking distribution area 1 as an example, the topology of the area was plotted based on the collected data as follows: Figure 5 As shown.

[0114] Then, the Newton-Raphson power flow method is used to linearize each node in a typical transformer substation and iteratively solve for the voltage of each node and the power distribution of the branch.

[0115] Secondly, by using the controlled variable method, the inflection points of the increase or decrease in the impact of each target indicator on line loss are calculated.

[0116] Simulation analysis revealed that with increased photovoltaic (PV) capacity, the line loss rate in the distribution area initially decreased and then increased regardless of summer or winter, reaching its lowest point when PV penetration was around 80%. The impact of PV penetration was quantified and summarized into three scenarios: less than 80%, 80%-100%, and greater than 100%, with the following trends observed in their influence on line loss. Figure 6 As shown.

[0117] Simulation analysis revealed that with a gradual increase in photovoltaic (PV) power generation, the line loss rate of the distribution area initially decreased and then increased, regardless of summer or winter. The PV power absorption ratio reached its lowest point when the line loss rate was around 130%. The impact of the power absorption ratio was quantified and summarized into three scenarios: less than 130%, 130%-200%, and greater than 200%, showing the trend of its influence on line loss. Figure 7 As shown.

[0118] Simulation analysis revealed that when the peak load ratio was less than 120%, the transformer substations generally showed a decreasing loss trend, while when the peak load ratio exceeded 300%, the loss trend generally increased. The impact of the peak load ratio was quantified and summarized into three scenarios: less than 120%, between 120% and 300%, and greater than 300%. The trend of the impact on line losses is shown below. Figure 8 As shown.

[0119] Table 3 shows the impact of the grid connection location coefficient on line loss. Simulation analysis reveals that the location of the photovoltaic grid connection has a significant impact on the line loss of the distribution area. For example, simulations of the power generation absorption ratio show that if the grid connection location is concentrated at the front end of the distribution area (Distribution Area 7), even with a power generation absorption ratio of 200%, the distribution area still experiences reduced losses. The ability to withstand photovoltaic backfeeding is stronger, but the entry into the loss-increasing phase is relatively delayed. The impact of the grid connection location is quantified by defining the grid connection location coefficient as greater than 80% and less than 80%. The trend of the impact on line loss is shown below. Figure 9 As shown.

[0120] Table 3. Impact of Access Location Coefficient on Line Loss

[0121]

[0122]

[0123] Table 4 shows the impact of source-load center deviation on line loss. Simulation analysis reveals that when the source-load center deviation is between 90% and 110%, the transformer area shows good loss reduction, indicating a small source-load spatial coupling deviation and effective absorption of photovoltaic power by nearby user loads. When the source-load center deviation is less than 90% or greater than 110%, the transformer area shows no loss reduction effect, indicating a large source-load spatial coupling deviation and potential photovoltaic backfeeding. The trend of the impact of source-load center deviation on line loss is shown below. Figure 10 As shown.

[0124] Table 4. Impact of Load Center Deviation on Line Loss

[0125] Taiwan Source-load center deviation Impact of line loss Channel 1 110％ Loss reduction Channel 2 89％ Reduce losses or break even Channel 3 104％ Loss reduction Channel 4 90％ Loss reduction No. 5 station area 79％ Increase or decrease or break even Channel 6 112％ Reduce losses or break even Channel 7 64％ Increase / Decrease

[0126] Based on the analysis of the inflection points of the impact of all the above target indicators on line loss, the reference values ​​are determined as follows: photovoltaic penetration rate 80%, power generation absorption ratio 130%, peak load ratio 120%, grid connection location coefficient 80%, and source-load center deviation 100%. The reference values ​​for photovoltaic penetration rate, power generation absorption ratio, peak load ratio, and grid connection location coefficient are all determined based on the inflection point values ​​of loss reduction, while the reference value for source-load center deviation is determined based on the average of two inflection points.

[0127] Finally, based on the expert scoring method, clear evaluation standards and weights were established for the above evaluation indicators, and a multi-dimensional quantitative evaluation model was constructed to evaluate the line loss of typical transformer areas.

[0128] Table 5 shows the reference values ​​and weights of the line loss characteristic evaluation indicators, and a multi-dimensional quantitative evaluation model is constructed based on the weights and reference values ​​of each indicator.

[0129] Table 5 Weights and Algorithms of Line Loss Characteristic Evaluation Indicators

[0130]

[0131] Based on the table above, the established multi-dimensional quantitative evaluation model is as follows:

[0132] F(x i )=[(ε-80%)*10%+(θ-130%)*20%+(η-120%)*30%+(δ4-80%)*30%+|(δ5-10

[0133] 0% | * 10%] * 100.

[0134] Based on this evaluation model, the representative winter days and representative summer days of seven typical substations were calculated and evaluated, and the evaluation results are shown in Table 6.

[0135] Table 6 Evaluation Results

[0136]

[0137] It can be seen that there are 5 transformer substations with high line loss, 4 with medium line loss, 3 with low line loss, and 2 with reduced line loss. This method effectively assesses the degree of increase or decrease in line loss of transformer substations after distributed photovoltaic grid connection.

[0138] The method for evaluating line loss in transformer substations provided by this invention first selects pre-determined line loss characteristic evaluation indicators and screens typical transformer substations from the area to be evaluated. Next, iterates through and calculates all nodes representing typical substations within a day, obtaining a traversal dataset of each node in all target substations. Then, based on the traversal dataset of each node in all target substations, it determines the voltage and branch power distribution of each node in all target substations. Then, based on the voltage and branch power distribution of each node in all target substations, it determines the inflection points of increase or decrease in the impact of all target indicators on line loss. Finally, based on the inflection points of increase or decrease in the impact of all target indicators on line loss, it constructs a multi-dimensional quantitative evaluation model to evaluate the line loss of typical substations. This invention first screens out typical substations with broad coverage and strong representativeness based on determined line loss characteristic evaluation indicators. By using the obtained voltage and branch power distribution of each node in all target substations, it can accurately determine the inflection points of increase or decrease in the impact of each target indicator on line loss according to the actual operating conditions of the substations. Furthermore, based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed, which can accurately evaluate the line loss of the transformer area.

[0139] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0140] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0141] Figure 11 A schematic diagram of the structure of the photovoltaic power distribution line loss evaluation device integrating multi-dimensional photovoltaic features provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0142] like Figure 11 As shown, the photovoltaic (PV) transformer area line loss assessment device 1100, which integrates multi-dimensional characteristics, includes:

[0143] The screening module 1110 is used to screen typical transformer substations from the area to be evaluated based on predetermined line loss characteristic evaluation indicators.

[0144] The data acquisition module 1120 is used to traverse and calculate all nodes of a typical transformer area representing the day, and to obtain the traversal dataset of each node in all target transformer areas; the target transformer area is any one of the typical transformer areas.

[0145] The first determining module 1130 is used to determine the voltage and branch power distribution of each node in all target transformer areas based on the traversal dataset of each node in all target transformer areas.

[0146] The second determining module 1140 is used to determine the inflection point of the increase or decrease of the impact of all target indicators on line loss based on the voltage and power distribution of each node and branch in all target areas; the target indicator is any one of the line loss characteristic evaluation indicators.

[0147] Evaluation module 1150 is used to construct a multi-dimensional quantitative evaluation model based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, and to evaluate the line loss of typical transformer areas.

[0148] In one possible implementation, the evaluation module 1150 is used to construct a target indicator evaluation function based on the inflection point of the target indicator's increase or decrease and the weight of the target indicator.

[0149] A multi-dimensional quantitative evaluation model is constructed based on the sum of all target indicator evaluation functions.

[0150] Based on a multi-dimensional quantitative evaluation model, the line loss of typical transformer substations is evaluated.

[0151] In one possible implementation, the evaluation module 1150 is used to input the numerical values ​​of the line loss characteristic evaluation index of the target transformer area into the multi-dimensional quantitative evaluation model to obtain the degree of loss increase of the target transformer area.

[0152] Based on the loss increase values ​​of all target transformer areas and the preset loss increase evaluation rules, the line loss of all target transformer areas is evaluated.

[0153] In one possible implementation, the line loss characteristic evaluation indicators include photovoltaic penetration rate, power generation absorption ratio, peak load ratio, grid connection location coefficient, and source-load center deviation.

[0154] Photovoltaic penetration rate is the ratio of photovoltaic grid connection capacity to distribution transformer capacity in the distribution area; power generation absorption ratio is the ratio of photovoltaic grid-connected electricity to user electricity consumption; peak load ratio is the ratio of peak photovoltaic output to peak user load; grid connection location coefficient is the ratio of photovoltaic grid connection capacity within 20% of the power supply distance to the total photovoltaic grid connection capacity in the distribution area; source-load center deviation is the spatial coupling deviation between the equivalent center of photovoltaic power generation and the equivalent center of user load in the distribution area.

[0155] In one possible implementation, the process for determining the source load center deviation is as follows:

[0156] The deviation value of the target line is determined based on the ratio of the distance between the photovoltaic equivalent center of the target line and the transformer to the distance between the user load equivalent center and the transformer; where the target line is any line in the target distribution area.

[0157] The source-load center deviation of the target transformer area is determined by the square root of the sum of the squares of the deviations of all target lines in the target transformer area.

[0158] In one possible implementation, the second determining module 1140 is used to analyze the voltage and power distribution of each node in all target areas based on the control variable method, and determine the inflection points of increase or decrease of all target indicators.

[0159] In one possible implementation, the first determining module 1130 is used to construct the power flow equation based on the traversal dataset of each node in all target areas;

[0160] The power flow equations are solved using the Newton-Raphson power flow method to obtain the voltage and branch power distribution of each node in all target transformer areas.

[0161] In one possible implementation, the dataset is traversed, including the transformer substation topology, operational data, and photovoltaic resource distribution.

[0162] The topological structure of the transformer area includes radial, ring network, and trunk network structures;

[0163] Operational data includes electricity consumption by end users and transformer operation data;

[0164] The distribution of photovoltaic resources includes the number of households connected to photovoltaic systems in the distribution area, the connected capacity, and the connection location.

[0165] Figure 12 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. For example... Figure 12As shown, the electronic device 12 of this embodiment includes a processor 120 and a memory 121. The memory 121 stores a computer program 122. When the processor 120 executes the computer program 122, it implements the steps in the various method embodiments described above. Alternatively, when the processor 120 executes the computer program 122, it implements the functions of each module / unit in the various device embodiments described above.

[0166] For example, computer program 122 may be divided into one or more modules / units, which are stored in memory 121 and executed by processor 120 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 122 in electronic device 12.

[0167] Electronic device 12 may include, but is not limited to, processor 120 and memory 121. Those skilled in the art will understand that... Figure 12 This is merely an example of electronic device 12 and does not constitute a limitation on electronic device 12. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 12 may also include input / output devices, network access devices, buses, etc.

[0168] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0169] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0170] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such 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, and should all be included within the protection scope of the present invention.

Claims

1. A method for evaluating line loss in photovoltaic distribution areas that integrates multi-dimensional characteristics, characterized in that, include: Based on predetermined line loss characteristic evaluation indicators, typical transformer substations are selected from the area to be evaluated. Traverse and calculate all nodes representing the typical transformer area within the day to obtain the traversal dataset of all nodes in the target transformer area; the target transformer area is any one of the typical transformer areas. Based on the traversal dataset of all nodes in all target transformer areas, determine the voltage and branch power distribution of each node in all target transformer areas. Based on the voltage and branch power distribution of each node in all target transformer areas, determine the inflection points of increase or decrease of the impact of all target indicators on line loss; the target indicator is any one of the line loss characteristic evaluation indicators. Based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed to evaluate the line loss of the typical transformer area.

2. The method for evaluating transformer substation line loss based on integrating multi-dimensional photovoltaic characteristics according to claim 1, characterized in that, Based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, a multi-dimensional quantitative evaluation model is constructed to evaluate the line loss of the typical transformer area, including: Based on the inflection point of the increase or decrease of the target indicator's impact on line loss and the weight of the target indicator, an evaluation function for the target indicator is constructed. Based on the sum of all the target indicator evaluation functions, the multi-dimensional quantitative evaluation model is constructed. Based on the aforementioned multi-dimensional quantitative evaluation model, the line loss of the typical transformer area is evaluated.

3. The method for evaluating transformer substation line loss based on integrating multi-dimensional photovoltaic characteristics according to claim 2, characterized in that, The evaluation of line loss in the typical transformer area based on the multi-dimensional quantitative evaluation model includes: The numerical values ​​of the line loss characteristic evaluation index of the target transformer area are input into the multi-dimensional quantitative evaluation model to obtain the degree of loss increase of the target transformer area. Based on the loss increase values ​​of all target transformer areas and the preset loss increase evaluation rules, the line loss of all target transformer areas is evaluated.

4. The method for evaluating transformer substation line loss by integrating multi-dimensional photovoltaic characteristics according to claim 1, characterized in that, The line loss characteristic evaluation indicators include photovoltaic penetration rate, power generation absorption ratio, peak load ratio, grid connection location coefficient, and source-load center deviation. The photovoltaic penetration rate is the ratio of photovoltaic grid connection capacity to distribution transformer capacity in the distribution area; the power generation absorption ratio is the ratio of photovoltaic grid-connected power to user power consumption; the peak load ratio is the ratio of peak photovoltaic output to peak user load; the grid connection location coefficient is the ratio of photovoltaic grid connection capacity within 20% of the power supply distance to the total photovoltaic grid connection capacity in the distribution area; and the source-load center deviation is the spatial coupling deviation between the equivalent center of photovoltaic power in the distribution area and the equivalent center of user load.

5. The method for evaluating line loss in photovoltaic distribution areas by integrating multi-dimensional characteristics according to claim 4, characterized in that, The process for determining the source load center deviation is as follows: The deviation value of the target line is determined based on the ratio of the distance between the photovoltaic equivalent center of the target line and the transformer to the distance between the user load equivalent center and the transformer; wherein, the target line is any line in the target distribution area; The source-load center deviation of the target transformer area is determined by the square root of the sum of the squares of the deviation values ​​of all target lines in the target transformer area.

6. The method for evaluating the line loss of a photovoltaic distribution area by integrating multi-dimensional characteristics according to any one of claims 1-5, characterized in that, Based on the voltage and branch power distribution of each node within all target transformer areas, the inflection points of increase or decrease in the impact of all target indicators on line loss are determined, including: Based on the controlled variable method, the voltage and power distribution of each node in all target transformer areas are analyzed to determine the inflection points of the increase or decrease of the impact of all target indicators on line loss.

7. The method for evaluating the line loss of a photovoltaic distribution area by integrating multi-dimensional characteristics according to any one of claims 1-5, characterized in that, The determination of voltage and branch power distribution for each node within all target transformer areas, based on a traversal dataset of nodes within all target transformer areas, includes: Power flow equations are constructed based on the traversal dataset of all nodes within all target transformer areas; The power flow equations are solved using the Newton-Raphson power flow method to obtain the voltage and branch power distribution of each node in all target transformer areas.

8. The method for evaluating the line loss of a photovoltaic distribution area by integrating multi-dimensional characteristics according to any one of claims 1-5, characterized in that, The traversal dataset includes the topology of the transformer area, operational data, and the distribution of photovoltaic resources. The topological structure of the transformer area includes radial, ring network, and trunk-like structures. The operational data includes end-user electricity consumption and transformer operational data; The distribution of photovoltaic resources includes the number of households connected to photovoltaic systems in the distribution area, the connected capacity, and the connected location.

9. A device for evaluating line loss in a photovoltaic distribution area, integrating multi-dimensional characteristics, characterized in that, include: The screening module is used to screen typical transformer substations from the area to be evaluated based on pre-determined line loss characteristic evaluation indicators. The data acquisition module is used to traverse and calculate all nodes representing the typical transformer area within the day, and obtain the traversed dataset of each node in all target transformer areas; the target transformer area is any one of the typical transformer areas. The first determining module is used to determine the voltage and branch power distribution of each node in all target transformer areas based on the traversal dataset of each node in all target transformer areas. The second determining module is used to determine the inflection point of increase or decrease of the impact of all target indicators on line loss based on the voltage and power distribution of each node and branch in all target areas; the target indicator is any one of the line loss characteristic evaluation indicators. The evaluation module is used to construct a multi-dimensional quantitative evaluation model based on the inflection points of the increase or decrease in the impact of all target indicators on line loss, and to evaluate the line loss of the typical transformer area.

10. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 8.

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