A power distribution network distributed photovoltaic access capacity planning method based on margin evaluation

Abstract

The application provides a power distribution network distributed photovoltaic access capacity planning method based on margin evaluation, a distributed photovoltaic openable capacity calculation model is established, the distributed photovoltaic openable capacity of the planning line is calculated, the load rate and the power load of the corresponding voltage level are considered as constraint conditions, the openable capacity of the distributed photovoltaic of the planning line is optimized and adjusted under the condition of meeting the constraint conditions, the power distribution network planning of the planning line is reasonably carried out, the equipment utilization rate and the power resource utilization rate are improved, and the power grid planning and engineering practice have very important significance.

Description

Technical Field

[0001] This invention relates to the field of distribution network management technology, and mainly to a method for capacity planning of distributed photovoltaic (PV) grid access in distribution networks based on margin evaluation. Background Technology

[0002] Assessing the open capacity of distribution networks is a key challenge and a critical aspect of power grid planning and operation management. Excessive load or renewable energy connections to distribution network equipment can lead to heavy overload operation, causing safety hazards and reliability issues. Conversely, insufficient load or renewable energy connections can result in light-load operation, low equipment utilization, and wasted power resources.

[0003] Given the limited capacity of the power grid to connect distributed photovoltaic (PV) systems, an optimized method for predicting the connectable capacity of distributed PV systems is proposed to meet the requirements for the safe and stable operation of the power grid, taking into account the load capacity of the power grid equipment and the development level of the power grid load.

[0004] CN108376996B, "A Practical Method for Estimating the Distributed Photovoltaic Adoption Capacity of Distribution Networks," discloses "a practical method for estimating the distributed photovoltaic adoption capacity of distribution networks, which decomposes the distributed photovoltaic adoption capacity into the local absorption capacity of distributed photovoltaic and the grid's transmission capacity of distributed photovoltaic; estimates the adoption capacity of basic unit equipment such as low-voltage distribution transformers, medium-voltage lines, and high-voltage substations for distributed photovoltaic, and accumulates them by voltage level under the condition of meeting the capacity constraints of the upper-level power supply equipment to obtain the overall regional and voltage-level distributed photovoltaic adoption capacity; the method includes: (1) calculation of the local absorption capacity of distributed photovoltaic; (2)..." (3) Calculation of the grid's capacity to transmit distributed photovoltaic power; (4) Calculation of the basic unit equipment's capacity to accept distributed photovoltaic power; (5) Calculation of the regional distributed photovoltaic absorption capacity; (6) Hierarchical description of the regional distributed photovoltaic absorption capacity. This invention method does not require a large amount of data support to estimate the overall absorption capacity of the region and simultaneously give the absorption scale of each voltage level. However, in contrast, the existing technology cannot solidify the relevant boundary conditions for calculating the open capacity standard of the distribution network, and cannot accurately confirm the thermal stability limit load of the 10kV line and the simulation boundary conditions for the maximum access distributed power source of the 10kV line, resulting in poor equipment utilization and power resource utilization. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this application provides a capacity planning method for distributed photovoltaic (PV) grid integration based on margin evaluation. The technical solution of this application is as follows:

[0006] A method for capacity planning of distributed photovoltaic (PV) grid access in a distribution network based on margin evaluation, comprising the following steps:

[0007] A calculation model for the available capacity of distributed photovoltaic installations is established with the target being the available capacity of distributed photovoltaic installations. Relevant parameters of the planned lines are obtained, and the available capacity of distributed photovoltaic installations of the planned lines is calculated based on the relevant parameters of the planned lines.

[0008] The simulation platform is used to simulate the planned route throughout the year to obtain the simulation operation results of the planned route. The simulation operation results of the planned route are analyzed by charts to obtain relevant data on the operation of the route. Based on the relevant data on the operation of the route, the maximum and minimum values ​​of the equivalent load rate of the route are calculated.

[0009] The maximum equivalent load factor of the line determines whether to adjust the planned distributed photovoltaic (PV) installation capacity. If adjustment is required, the planned distributed PV installation capacity is calculated by considering the two-level boundary conditions, and the corresponding margin index is calculated based on the planned distributed PV installation capacity. If no adjustment is required, the corresponding margin index is calculated based on the distributed PV installation capacity.

[0010] Based on the corresponding margin indicators, the development of distributed photovoltaic capacity is divided into regions, and the distribution network planning for distributed photovoltaic access is carried out according to the divided regions.

[0011] Preferably, the relevant parameters of the planned route include the area of ​​the land plots supplied by the planned route, the building density of the land plots supplied by the planned route, the power load under N-1 verification for each circuit, the maximum power supply capacity of a single line of the distribution network, the rated capacity of photovoltaic equipment in the distribution network, and the conversion rate of photovoltaic equipment.

[0012] Preferably, the specific mathematical expression for calculating the openable capacity of the distributed photovoltaic installation is as follows:

[0013] S PV =S·α·β;

[0014] In the formula, S PV The area to be installed for distributed photovoltaic power generation is represented by S, the area of ​​the land plot supplied by the planned power line is represented by α, the building density index of the land plot supplied by the planned power line is represented by β, and the photovoltaic installation coefficient is represented by β.

[0015] P PV =S PV ·γ;

[0016] In the formula, P PV γ represents the open capacity of distributed photovoltaic installations, and γ represents the conversion efficiency of photovoltaic equipment.

[0017] Preferably, the simulation results represent the line operation status for the entire year, specifically including the main / distribution transformers, line power load, actual line operating load, and photovoltaic output load for each month.

[0018] Preferably, the step of obtaining relevant data on line operation status by performing graphical analysis of the simulation results includes:

[0019] The simulation results are compiled into charts to obtain the overall feeder load situation and the overall feeder load feedback situation;

[0020] Based on the overall feeder load situation, the day with the highest load throughout the year is selected for analysis to obtain the value of the maximum power load, the corresponding time node, and the maximum photovoltaic output load on that day;

[0021] Based on the overall feeder load feedback situation, the day with the largest feedback load throughout the year is selected for analysis to obtain the value of the largest feedback load, the corresponding time node, and the maximum photovoltaic output load on that day.

[0022] Preferably, the calculation of the maximum and minimum values ​​of the line's equivalent load rate based on relevant data on line operation specifically involves:

[0023] The maximum and minimum equivalent load rates of the line are calculated by combining the maximum reverse power load and the maximum photovoltaic output load of the day with the rated capacity of the photovoltaic equipment in the distribution network. The corresponding mathematical expressions are as follows:

[0024]

[0025]

[0026] In the formula, η max η represents the maximum equivalent load factor of the line. min P represents the minimum equivalent load factor of the line. L，max P represents the maximum reverse power load. SS，max S represents the maximum photovoltaic output load for that day. e This indicates the rated capacity of photovoltaic equipment in the power distribution network.

[0027] Preferably, the method for determining whether to correct the openable capacity of distributed photovoltaic installations based on the maximum equivalent load rate of the line specifically includes:

[0028] Compare the absolute value of the maximum equivalent load factor of the line with the reverse transmission boundary value. If the absolute value of the maximum equivalent load factor of the line is greater than the reverse transmission boundary value, the reverse transmission is determined to be overloaded, and the open capacity of distributed photovoltaic installation needs to be adjusted. The reverse transmission boundary value is determined according to the two boundary conditions of different levels.

[0029] Preferably, the specific mathematical expression for calculating the available capacity of distributed photovoltaic installations is as follows:

[0030] S m =k(η) min +δ)×S e η min >—δ;

[0031] S m=0, η min ≤—δ;

[0032] In the formula, S m This represents the planned open capacity of distributed photovoltaic installations, where k is the conversion factor and η is the open capacity. min δ represents the minimum equivalent load rate of the line, and δ represents the reverse transmission boundary value;

[0033] The formula for calculating k is:

[0034]

[0035] In the formula, P line，n P represents the electrical load under N-1 checks per circuit. line，max This indicates the maximum power supply capacity of a single line in the distribution network.

[0036] Preferably, the specific mathematical expression for calculating the margin index is as follows:

[0037]

[0038] In the formula, σ represents the margin index, and S m This indicates the planned open capacity of distributed photovoltaic installations, S PV，C This indicates the current existing photovoltaic development capacity.

[0039] Preferably, the planned distributed photovoltaic (PV) capacity development is divided into regions based on the corresponding margin index, and the development of distributed PV capacity in the distribution network is rationally set according to the divided regions. Specifically:

[0040] When σ∈(0,0.3), the area corresponding to the planned development of distributed photovoltaic capacity is classified as a Class III distributed development area. Distributed photovoltaic development will cause heavy load on the distribution network equipment, so distributed photovoltaic development should be appropriately restricted.

[0041] When σ∈(0.3,0.6), the area corresponding to the planned development of distributed photovoltaic capacity is classified as a distributed development Class II area. Distributed photovoltaic development will increase the load rate of distribution network equipment. Distributed photovoltaic development should be carried out reasonably without causing the distribution network equipment to be overloaded.

[0042] When σ∈(0.6,1.0), the area corresponding to the planned development of distributed photovoltaic capacity is designated as a Class I distributed development area. Distributed photovoltaic capacity can be increased as needed, but the newly added distributed photovoltaic capacity cannot cause the distribution network equipment to be overloaded.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] This invention presents a method for planning distributed photovoltaic (PV) grid access capacity based on margin evaluation. It establishes a calculation model for the exploitable capacity of distributed PV, and calculates the exploitable capacity of distributed PV at different voltage levels based on constraints such as no backflow of power flow, backflow of power flow not causing overload of corresponding equipment, and backflow at the same voltage level not causing overload of the upper-level grid. After calculating the exploitable capacity of distributed PV at different voltage levels, it further proposes a PV exploitable capacity margin index to evaluate distributed PV development. This method calculates the exploitable capacity of distributed PV along planned lines, considering constraints such as load factor and electricity load at the corresponding voltage level. Under the condition of meeting the constraints, it optimizes and adjusts the exploitable capacity of distributed PV along planned lines, rationally carrying out distribution network planning for planned lines, improving equipment utilization and power resource utilization, which is of great significance for grid planning and engineering practice. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating the method of an embodiment of this application;

[0046] Figure 2 This is the August line operation status according to an embodiment of this application;

[0047] Figure 3 This describes the year-round line operation status according to the embodiments of this application;

[0048] Figure 4 This is the load matching situation between the power line and the photovoltaic power station on August 14th, according to an embodiment of this application.

[0049] Figure 5 This is the load fit between the power line and the photovoltaic power station on May 1st, according to an embodiment of this application. Detailed Implementation

[0050] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0051] The present invention provides the following technical solution: a method for capacity planning of distributed photovoltaic access in distribution networks based on margin evaluation.

[0052] Example 1

[0053] This embodiment calculates the capacity and access method of distributed photovoltaic (PV) grid access based on the carrying capacity of distribution network equipment and the selection of access methods, combined with the development and upgrading trend of distribution networks. Specifically, it determines the access capacity and method for distributed PV grid access. In this embodiment, the method follows the principles of distributed PV access, specifically:

[0054] A. Safety and Stability Principle. The calculation of the equipment's connectable capacity is based on the fundamental principle of "ensuring the safe and stable operation of the existing power grid and avoiding backfeeding to the 220kV and above power grids," and is calculated sequentially from five levels: "220kV substations and 10kV busbars of main transformers, 110kV main transformers, 35kV main transformers, 10kV lines, and distribution transformers."

[0055] B. Layered and zoned principle. The open capacity of distributed photovoltaic power grid is the capacity of distributed power sources that can be newly connected to the traditional power grid. When calculating the layers and dimensions, the "grid" planning concept with relatively mature regional development can be considered to establish a layered and zoned principle for the open capacity.

[0056] C. Load Capacity Assessment Principles. The calculation of the regional power grid's connectable capacity is based on the calculation results of the equipment's connectable capacity, and the minimum value is taken as the calculation result, according to the principle that all levels must meet the requirements.

[0057] Based on the above principles, this embodiment specifically includes the following steps:

[0058] S1. Establish a calculation model for the openable capacity of distributed photovoltaic installations with the target as the objective, obtain relevant parameters of the planned lines, and calculate the openable capacity of distributed photovoltaic installations of the planned lines based on the relevant parameters of the planned lines.

[0059] S11. The relevant parameters of the planned route include the area of ​​the land plots supplied by the planned route, the building density, the power load under N-1 verification for each circuit, the maximum power supply capacity of a single line of the distribution network, and the rated capacity and conversion rate of the photovoltaic equipment in the distribution network.

[0060] In this embodiment, the planned line is a 10kV line, and the plots supplied by CFⅠ are X06-B02, X06-B03, X06-B04 and X06-B05. According to the MLS Cultural and Creative Park "Control Detailed Planning", the above-mentioned plots are classified as Class II residential land.

[0061] The CFⅠ circuit connection mode is a single-ring network. According to the "CS City Distribution Network Planning and Design Technical Guidelines", the maximum power supply capacity of a single line in a single-ring network is 7.4MW. At the same time, considering that each line can pass the "N-1" check, the power load of each line should be less than 3.7MW.

[0062] Based on the obtained land area of ​​the planned power supply line and the selected appropriate photovoltaic installation coefficient, the net land area is obtained. The installable area for distributed photovoltaics is then obtained by combining the net land area with the building density. Based on the installable area for distributed photovoltaics and the power generation efficiency of different photovoltaic panels on the market, a relatively conventional photovoltaic panel with a conversion rate of 1kW / 6m2 is selected to calculate the open capacity for distributed photovoltaic installation.

[0063] The specific mathematical expression for calculating the openable capacity of the distributed photovoltaic installation is as follows:

[0064] S PV =S·α·β;

[0065] In the formula, S PV The area to be installed for distributed photovoltaic power generation is represented by S, the area of ​​the planned route plot is represented by α, the building density index of the plot is represented by β, and the overall recommended value is 50% to 80%.

[0066] P PV =S PV ·γ;

[0067] In the formula, P PV This indicates the openable capacity of distributed photovoltaic installations, and γ represents the conversion efficiency of photovoltaic equipment. The recommended overall value is 10% to 17%.

[0068] The specific calculation results are shown in the table below:

[0069]

[0070] The planned line, through calculation, yields the following openable distributed photovoltaic (PV) installation capacities for plots X06-B02, X06-B03, X06-B04, and X06-B05: 4424.05kW, 1311.71kW, 286.77kW, and 644.16kW, respectively. These plots are connected to two ring main units of the 10kV CFⅠ line, and the total openable distributed PV installation capacity of the entire line is approximately 6687kW.

[0071] S2. Use a simulation platform to simulate the planned route throughout the year to obtain the simulation operation results of the planned route. Perform chart analysis on the simulation operation results of the planned route to obtain relevant operation data of the route. Calculate the maximum and minimum values ​​of the equivalent load rate of the route based on the relevant data of the route operation.

[0072] In this embodiment, the simulation platform is the Cloudpss Integrated Energy Digital Twin Platform. It simulates the planned 10kV CFⅠ circuit throughout the year. Since this platform can only select a maximum of three months for simulation, a full-year simulation would require... Figure 2The simulation data is exported and organized month by month as shown. The simulation results are as follows: Figure 3 The diagram shows the line operation status throughout the year, including the main / distribution transformers, line power load, actual line operating load, and photovoltaic output load for each month.

[0073] Preferably, the step of obtaining relevant operational data on the route conditions through graphical analysis of the simulation results of the planned route includes:

[0074] The simulation results are compiled into charts to obtain the overall feeder load situation and the overall feeder load feedback situation;

[0075] Among them, such as Figure 1 As shown, the feeder load exhibits a bi-peak pattern, with January and August being peak periods and February and October being low-peak periods. Analysis of the day with the highest load throughout the year, based on the overall feeder load situation, reveals the following: the highest load occurred on August 14th at 10:00 AM, with a load value of 3543.17 kW; the lowest load occurred on January 25th at 0:00 AM, with a minimum load value of 425.40 kW; and the maximum peak-to-valley difference for residential loads was 3117.77 kW.

[0076] like Figure 4 As shown, the analysis focuses on the day with the highest annual load (August 14th). The maximum electrical load is 3543.17kW, while the maximum output load of the photovoltaic system is 3000.71kW. The photovoltaic output can reduce the circuit's electrical load to 163.80kW. This means that the residential load feeder can fully absorb the electricity generated by the photovoltaic system on the day with the highest load. With the continued development of photovoltaic systems, the peak load of residential areas will shift accordingly.

[0077] Based on the overall feeder load feedback situation, April to June is the peak period for feedback, while January and August are the low periods for feedback; the total feedback time throughout the year is 2,600 hours, accounting for 29.68%, with the maximum feedback time being 12:00 on May 1st;

[0078] like Figure 5 As shown, the analysis focuses on the day with the maximum reverse load of the line throughout the year (May 1st). The line's power load is 831.09kW, the maximum photovoltaic output load is 6726.27kW, the maximum reverse load occurs at 12:00, and the maximum power load is 5895.18kW. Considering that the maximum load that each line can withstand is 7400kW, i.e., the rated capacity of the photovoltaic equipment in the distribution network is 7400kW, the maximum equivalent load rate of the line is calculated by combining the maximum reverse load and the maximum photovoltaic output load of the day with the rated capacity of the photovoltaic equipment in the distribution network. The corresponding mathematical expression is:

[0079]

[0080] Thus, the maximum equivalent load factor of the 10kV CFⅠ reverse transmission is 79.67%.

[0081] The minimum equivalent load factor should be calculated at the time of maximum output of the distributed power source, which typically occurs between 12:00 and 13:00. The electricity load is taken as the minimum value within the corresponding evaluation period. The minimum equivalent load factor is generally calculated separately for summer and winter, and the smaller of the two values ​​is taken as the minimum (including negative minimums). The maximum output of the distributed power source in summer and winter is selected differently based on the power source type and operating characteristics. In this embodiment, the electricity load at the time of maximum backfeed is used for calculation, i.e., P. L，max =831.09kW, S e The value is taken as 7.4MW, and substituted into the calculation formula:

[0082]

[0083] We can obtain η min Approximately 11%.

[0084] In the two formulas above for calculating the maximum and minimum equivalent load factor, η max η represents the maximum equivalent load factor of the line. min P represents the minimum equivalent load factor of the line. L，max P represents the maximum reverse power load. SS，max S represents the maximum photovoltaic output load for that day. e This indicates the rated capacity of photovoltaic equipment in the power distribution network.

[0085] S3. Determine whether to adjust the openable capacity of distributed photovoltaic installations based on the maximum equivalent load factor. If adjustment is required, consider the two-level boundary conditions at each level to calculate the openable capacity of the planned distributed photovoltaic installations, and calculate the corresponding margin index based on the openable capacity of the planned distributed photovoltaic installations. If no adjustment is required, calculate the corresponding margin index based on the openable capacity of the distributed photovoltaic installations.

[0086] Preferably, the step of determining whether to correct the openable capacity of distributed photovoltaic installations based on the analysis results specifically involves comparing the absolute value of the maximum equivalent load factor of the line with the reverse transmission boundary value. If the absolute value of the maximum equivalent load factor of the line is greater than the reverse transmission boundary value, then the reverse transmission is determined to be overloaded, and the openable capacity of distributed photovoltaic installations needs to be corrected. The reverse transmission boundary value is determined based on the dual boundary conditions at different levels, for example:

[0087] The calculation of the openable capacity of distributed photovoltaic installations at the 0.22 / 0.38kV level should consider two boundary conditions. First, under the constraint of only the local grid, the openable capacity should meet the requirement of non-overloading of reverse transmission. Second, under the constraint of the upper-level grid, in addition to the local grid meeting the requirement of non-overloading of reverse transmission, it should also be considered that the reverse transmission of the local grid will not cause overloading of the 10kV level grid. In this embodiment, the planned line is a 10kV line. The calculation of the openable capacity at the 10kV level should consider two boundary conditions. First, under the constraint of only the local grid, the openable capacity should meet the requirement of non-overloading of reverse transmission. Second, under the constraint of the upper-level grid, in addition to the local grid meeting the requirement of non-overloading of reverse transmission, it should also be considered that the reverse transmission of the local grid will not cause overloading of the upper-level grid. The calculation personnel need to determine the value of k based on the main transformer load level, the already connected distributed power sources, and other conditions, and meet the constraints of the upper-level grid. Typically, the value of k is chosen to account for the power supply situation with two circuits, and to satisfy the ratio of the line transmission capacity during the N-1 check of each circuit to the maximum power supply capacity of a single line in a single ring network. Here, k is a conversion factor, ranging from 0 to 1. The specific calculation formula is as follows:

[0088]

[0089] In the formula, P line，n P represents the electrical load under N-1 checks per circuit. line，max Indicates the maximum power supply capacity of a single line in the distribution network;

[0090] In this embodiment, since the reverse transmission boundary value of the 10kV line is 70%, and the maximum equivalent load rate calculated in S3 is 79.67% > 70%, the reverse transmission reaches the heavy load standard, and the open capacity of distributed photovoltaic installation needs to be corrected.

[0091] Preferably, the specific mathematical expression for calculating the available capacity of distributed photovoltaic installations is as follows:

[0092] S m =k(η) min +δ)×S e η min >—δ;

[0093] S m =0, η min ≤—δ;

[0094] In the formula, S m This represents the planned open capacity of distributed photovoltaic installations, where k is a conversion factor. In this embodiment, two ring main units are connected, the power load is 3.7MW, and the maximum power supply capacity is 7.4MW; therefore, k is set to 1. η min The minimum equivalent load factor of the line is 11%, and δ represents the reverse transmission boundary value of 70%. S can be calculated from this. m =6.01MW, where Sm =0 indicates that the backfeed exceeds the boundary, and it is not recommended to connect to distributed renewable energy.

[0095] S4. Divide the planned distributed photovoltaic capacity development into regions based on the corresponding margin indicators, and rationally carry out the distributed photovoltaic access of the planned distribution network according to the divided regions.

[0096] Preferably, the specific mathematical expression for calculating the margin index is as follows:

[0097]

[0098] In the formula, σ represents the margin index, and S m This indicates the planned open capacity of distributed photovoltaic installations, S PV，C This represents the current existing photovoltaic development capacity; in this embodiment, S m =6.01MW, S PV，C The maximum power load on August 14 was approximately 3.5MW, and the calculated value was σ = 0.418.

[0099] Preferably, the planned distributed photovoltaic (PV) capacity development is divided into regions based on the corresponding margin index, and the development of distributed PV capacity in the distribution network is rationally set according to the divided regions. Specifically:

[0100] When σ∈(0,0.3), the area corresponding to the planned development of distributed photovoltaic capacity is classified as a Class III distributed development area. Distributed photovoltaic development will cause heavy load on the distribution network equipment, so distributed photovoltaic development should be appropriately restricted.

[0101] When σ∈(0.3,0.6), the area corresponding to the line in this embodiment is classified as a distributed development Class II area. Distributed photovoltaic development will increase the load rate of the distribution network equipment. Distributed photovoltaic development should be carried out reasonably without causing the distribution network equipment to be overloaded.

[0102] When σ∈(0.6,1.0), the area corresponding to the planned development of distributed photovoltaic capacity is designated as a Class I distributed development area. Distributed photovoltaic capacity can be increased as needed, but the newly added distributed photovoltaic capacity cannot cause the distribution network equipment to be overloaded.

[0103] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for capacity planning of distributed photovoltaic (PV) grid access in a distribution network based on margin evaluation, characterized in that, The specific steps include: A calculation model for the available capacity of distributed photovoltaic installations is established with the target being the available capacity of distributed photovoltaic installations. Relevant parameters of the planned lines are obtained, and the available capacity of distributed photovoltaic installations of the planned lines is calculated based on the relevant parameters of the planned lines. The simulation platform is used to simulate the planned route throughout the year to obtain the simulation operation results of the planned route. The simulation operation results of the planned route are analyzed by charts to obtain relevant data on the operation of the route. Based on the relevant data on the operation of the route, the maximum and minimum values ​​of the equivalent load rate of the route are calculated. The decision on whether to revise the planned capacity for distributed photovoltaic installations on the line should be based on the maximum equivalent load factor of the line. Specifically: Compare the absolute value of the maximum equivalent load factor of the line with the reverse transmission boundary value. If the absolute value of the maximum equivalent load factor of the line is greater than the reverse transmission boundary value, the reverse transmission is determined to be overloaded, and the open capacity of distributed photovoltaic installation needs to be adjusted. The reverse transmission boundary value is determined according to the two boundary conditions of different levels. If adjustments are needed, the calculation of the openable capacity of distributed photovoltaic installations should consider the two-tiered boundary conditions at different levels. The specific mathematical expression is as follows: ， ＞— ； ， ≤— ； In the formula, This represents the planned open capacity of distributed photovoltaic installations, where k is the conversion factor. This represents the minimum equivalent load factor of the line. Indicates the backfeed boundary value. Indicates the rated capacity of photovoltaic equipment in the power distribution network; The formula for calculating k is: ，0≤k≤1； In the formula, This represents the electrical load under N-1 checks per circuit. Indicates the maximum power supply capacity of a single line in the distribution network; The corresponding margin index is calculated based on the planned open capacity of distributed photovoltaic installations. If no correction is needed, the corresponding margin index is calculated based on the open capacity of distributed photovoltaic installations. Based on the corresponding margin indicators, the development of distributed photovoltaic capacity is divided into regions, and the distribution network planning for distributed photovoltaic access is carried out according to the divided regions.

2. The method for capacity planning of distributed photovoltaic (PV) grid access based on margin evaluation according to claim 1, characterized in that, The relevant parameters of the planned route include the area of ​​the land plots supplied by the planned route, the building density of the land plots supplied by the planned route, the power load under N-1 verification for each circuit, the maximum power supply capacity of a single line of the distribution network, the rated capacity of photovoltaic equipment in the distribution network, and the conversion rate of photovoltaic equipment.

3. The method for capacity planning of distributed photovoltaic (PV) grid access based on margin evaluation according to claim 2, characterized in that, The specific mathematical expression for calculating the openable capacity of the distributed photovoltaic installation is as follows: ； In the formula, The area to be installed for distributed photovoltaic power generation is represented by S, the area of ​​the land plot supplied by the planned power line is represented by α, the building density index of the land plot supplied by the planned power line is represented by β, and the photovoltaic installation coefficient is represented by β. ； In the formula, γ represents the open capacity of distributed photovoltaic installations, and γ represents the conversion efficiency of photovoltaic equipment.

4. The method for capacity planning of distributed photovoltaic (PV) grid access based on margin evaluation according to claim 1, characterized in that, The simulation results represent the line's operation throughout the year, specifically including the main / distribution transformers, line power load, actual line operating load, and photovoltaic output load for each month.

5. The method for capacity planning of distributed photovoltaic power grid access based on margin evaluation according to claim 4, characterized in that, The method of obtaining relevant data on line operation by performing graphical analysis of simulation results includes: The simulation results are compiled into charts to obtain the overall feeder load situation and the overall feeder load feedback situation; Based on the overall feeder load situation, the day with the highest load throughout the year is selected for analysis to obtain the value of the maximum power load, the corresponding time node, and the maximum photovoltaic output load on that day; Based on the overall feeder load feedback situation, the day with the largest feedback load throughout the year is selected for analysis to obtain the value of the largest feedback load, the corresponding time node, and the maximum photovoltaic output load on that day.

6. The method for capacity planning of distributed photovoltaic (PV) grid access based on margin evaluation according to claim 5, characterized in that, The calculation of the maximum and minimum values ​​of the line's equivalent load rate based on relevant data on line operation is as follows: The maximum and minimum equivalent load rates of the line are calculated by combining the maximum reverse power load and the maximum photovoltaic output load of the day with the rated capacity of the photovoltaic equipment in the distribution network. The corresponding mathematical expressions are as follows: ； ； In the formula, This represents the maximum equivalent load factor of the line. This represents the minimum equivalent load factor of the line. Indicates the maximum power load being fed back. This indicates the maximum output load of photovoltaic power on that day.

7. The method for capacity planning of distributed photovoltaic (PV) grid access based on margin evaluation according to claim 6, characterized in that, The specific mathematical expression for calculating the margin index is as follows: ； In the formula, Indicates the margin index, This indicates the planned open capacity for distributed photovoltaic installations. This indicates the current existing photovoltaic development capacity.

8. The method for capacity planning of distributed photovoltaic power grid based on margin evaluation according to claim 7, characterized in that, Based on the corresponding margin indicators, the planned distributed photovoltaic (PV) capacity development is divided into regions, and the specific details of the planned distribution network distributed PV capacity development are as follows: when When ∈ (0, 0.3), the area corresponding to the planned development of distributed photovoltaic capacity is classified as a distributed development Class III area. Distributed photovoltaic development will cause heavy load on the distribution network equipment, and distributed photovoltaic development should be appropriately restricted. when When ∈ (0.3, 0.6), the area corresponding to the planned distributed photovoltaic capacity development is classified as a distributed development Class II area. Distributed photovoltaic development will increase the load rate of distribution network equipment. Distributed photovoltaic development should be carried out reasonably without causing the distribution network equipment to be overloaded. when When ∈ (0.6, 1.0), the area corresponding to the planned development of distributed photovoltaic capacity is designated as a Class I distributed development area. Distributed photovoltaic capacity can be increased as needed, but the newly added distributed photovoltaic capacity cannot cause the distribution network equipment to be overloaded.

Images