Distributed photovoltaic connection network bearing capacity improving method

Abstract

The invention discloses a distributed photovoltaic network bearing capacity improving method, and relates to the technical field of power system planning and operation, and the method comprises the following steps: collecting source network load storage data of a target power supply area; performing current state problem analysis based on the source network load storage data to obtain a reverse heavy overload equipment list, and performing planning state demand analysis to obtain a bearing capacity margin; if the bearing capacity margin is insufficient, lifting measures including power grid construction and transformation and energy storage configuration are executed step by step according to a preset priority until the current problem is solved and the planning access requirement is met; the method comprises the following steps: aiming at two measures of power grid construction and transformation and energy storage configuration, calculating a corresponding permeability threshold value when comparison and selection indexes of the two measures are equal through a comparison and selection model, and determining a preliminary measure according to a comparison result of an actual permeability and the threshold value; and comparing the preliminary measure with a confluence boosting measure, and determining a final implementation scheme.

Description

Technical Field

[0001] This invention relates to the field of power system planning and operation technology, and more specifically, to a method for improving the grid connection capacity of distributed photovoltaic power. Background Technology

[0002] With the advancement of "dual carbon" goals and the support of new energy development policies, distributed photovoltaic (PV) power is experiencing explosive growth, with a large number of PV systems connected to the distribution network. To ensure the safe and stable operation of the power grid and fully absorb clean energy, power supply companies need to accurately assess the distribution network's capacity to support distributed PV and take effective measures to improve capacity when it is insufficient. However, current methods for improving the grid connection capacity of distributed PV still have many shortcomings. For example, traditional methods often lack comprehensive collection and analysis of multi-dimensional data on power generation, grid, load, and storage, making it difficult to accurately identify reverse overloaded equipment and assess capacity margins. When the penetration rate of distributed PV is rapidly increasing, the lack of systematic analysis of current problems and planned demand makes it difficult to identify capacity bottlenecks in a timely manner.

[0003] In existing technologies, some regions lack a scientific prioritization and hierarchical implementation mechanism for selecting capacity-enhancing measures, often directly adopting grid expansion and renovation schemes, resulting in high investment costs and long construction cycles. Furthermore, the choice between grid construction and renovation and energy storage configuration relies heavily on the experience and judgment of engineers, lacking quantitative comparison models and decision-making basis based on penetration rate thresholds. In addition, existing methods rarely include converter boosting measures in the comprehensive comparison, leading to an incomplete selection of the final implementation plan. These problems hinder the orderly integration of distributed photovoltaic power, urgently requiring a technical method that can systematically analyze the current capacity and planning needs, scientifically compare various enhancement measures, and determine the optimal implementation plan.

[0004] To address the above problems, this invention proposes a solution. Summary of the Invention

[0005] To overcome the aforementioned deficiencies in the prior art, embodiments of the present invention provide a method for enhancing the grid connection capacity of distributed photovoltaic systems, thereby addressing the problems in the prior art, such as the lack of comprehensive analysis of multi-dimensional data on source, grid, load, and storage, the lack of scientific prioritization and quantitative comparison models for selecting capacity enhancement measures, and the insufficient comprehensiveness in determining the final solution.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for improving the grid connection carrying capacity of distributed photovoltaic power includes the following steps: collecting source-grid-load-storage data of the target power supply area; analyzing the current situation based on the source-grid-load-storage data to obtain a reverse heavy overload equipment list, and conducting a planned demand analysis to obtain the carrying capacity margin; if the carrying capacity margin is insufficient, implementing improvement measures, including grid construction and renovation and energy storage configuration, in a step-by-step manner according to preset priorities until the current situation is resolved and the planned grid connection requirements are met; wherein, for the two measures of grid construction and renovation and energy storage configuration, the penetration rate threshold corresponding to the equality of the comparison indicators of the two measures is calculated through a comparison model, and the preliminary measures are determined based on the comparison results of the actual penetration rate and the threshold; the preliminary measures are compared with the converter boosting measures to determine the final implementation plan.

[0007] In a preferred embodiment, the current status problem analysis includes: calculating the reverse load rate of grid equipment; when the reverse load rate exceeds 80%, adding the equipment to the reverse overload equipment list; determining the causes of the current status problem of weak carrying capacity or reverse overload based on the regional grid structure, equipment capacity configuration, load characteristics, and distributed photovoltaic penetration and distribution; and determining that the current status problem has been resolved when the reverse load rate of all equipment in the list drops below 80%.

[0008] In a preferred embodiment, the planned demand analysis includes: obtaining the registered and planned distributed photovoltaic installed capacity within a designated area or equipment supply area; calculating the difference between the current equipment carrying capacity and the installed capacity to obtain the carrying capacity margin; and determining whether the carrying capacity margin meets the planned access requirements: if the carrying capacity margin is less than zero, it is determined that the carrying capacity margin is insufficient; otherwise, it is determined that the planned access requirements are met.

[0009] In a preferred embodiment, the step of executing improvement measures, including power grid construction and upgrading, and energy storage configuration, in a predetermined priority manner until the current problems are resolved and the planned access requirements are met includes: optimizing the power grid operation mode to determine whether the current problems can be resolved and the planned access requirements can be met. If the requirements cannot be met, source-load side guidance measures will be adopted for further evaluation; if the requirements still cannot be met, grid construction and renovation or energy storage configuration will be adopted; wherein, the optimized grid operation mode includes adjusting the parallel operation of transformers to the split operation mode and optimizing the transfer of distributed photovoltaic or load through line operation mode; the source-load side guidance measures include energy storage configuration for distributed photovoltaic, transformation of the observable, measurable, adjustable and controllable capabilities of distributed photovoltaic, energy storage configuration on the user side and construction of flexible and adjustable resource pools.

[0010] In a preferred embodiment, the step of calculating the penetration rate threshold corresponding to the equality of the comparison indicators of the two measures through the comparison model includes: plotting the pre-balance load curve based on the equipment load function, and plotting the post-balance load curve based on the net load function; calculating the reverse load rate of the equipment, and determining the reverse heavy overload period. to And calculate the distributed photovoltaic power feedback during that period. Calculate the power grid construction and renovation comparison index and the energy storage configuration comparison index respectively; solve for the distributed photovoltaic installed capacity corresponding to the power grid construction and renovation comparison index and the energy storage configuration comparison index being equal, and then calculate the penetration rate threshold; wherein, the equipment load function is... ,in, For the rated capacity of the equipment, The maximum utilization factor of the equipment. This is the load characteristic function. For time; the output function of distributed photovoltaic power is ,in, For distributed photovoltaic installed capacity, Output characteristic function; Net load function: Maximum equipment load: Penetration threshold: ,in, The distributed photovoltaic installed capacity is the same as the grid construction and renovation comparison index and the energy storage configuration comparison index.

[0011] In a preferred embodiment, the reverse load rate is calculated using the following formula:

[0012] in, For distributed photovoltaic power output function, For equipment load function, The rated capacity of the equipment; The determination of the reverse heavy overload period includes: when When the maximum value exceeds 80%, determine the reverse overload decomposition line. , The point of intersection with the balanced load curve corresponds to the boundary of the reverse heavy overload period. The formula for calculating the reverse power transmission is as follows:

[0013] in, and This represents the boundary of the reverse heavy overload period.

[0014] In a preferred embodiment, the calculation formula for the power grid construction and renovation selection index is as follows:

[0015] in, The moment when the maximum reverse load rate occurs. For the rated capacity of the equipment, To ensure a reasonable load rate for the equipment, The comprehensive cost per unit capacity of the equipment, For the entire life cycle of the equipment, For line length factor, L is the floor function; for distribution transformer substation scenarios and 110 kV main transformer scenarios, L = 1; for 10 kV feeder scenarios, L is the feeder power supply radius. The calculation formula for the energy storage selection index is as follows:

[0016] in, For the overall cost of energy storage, This refers to the entire lifecycle of energy storage.

[0017] In a preferred embodiment, the determination of preliminary measures based on the comparison between the actual penetration rate and the threshold is based on the following criteria: When the actual penetration rate < , At that time, the initial measure was to configure energy storage; When the actual penetration rate > , At that time, the initial measures were power grid construction and renovation; When the actual penetration rate = , Initial measures at that time included configuring energy storage or upgrading the power grid.

[0018] In a preferred embodiment, the insufficient carrying capacity margin further includes the following judgment method: based on the predicted data of natural load growth in the power supply area, it is determined whether the future load growth can offset the distributed photovoltaic reverse power; if it can offset, the carrying capacity margin is sufficient; otherwise, the carrying capacity margin is insufficient.

[0019] In a preferred embodiment, comparing the preliminary measures with the boost converter measures includes: assessing whether the implementation conditions of the preliminary measures are met; if not, selecting the boost converter measures; assessing the adaptability of the preliminary measures to future distributed photovoltaic installation growth; if the adaptability is insufficient, selecting the boost converter measures; and if the implementation conditions of the preliminary measures are met and the adaptability is sufficient, selecting the preliminary measures as the final implementation plan.

[0020] The technical effects and advantages of the method for improving the grid connection capacity of distributed photovoltaic power in this invention are as follows: This invention collects source-grid-load-storage data for the target power supply area, analyzes the current situation based on this data to obtain a list of reverse overloaded equipment, and performs planned demand analysis to determine the carrying capacity margin. When the carrying capacity margin is insufficient, different improvement measures are implemented step-by-step according to preset priorities until the current situation is resolved and the planned access requirements are met. A comparison model is used to calculate the penetration rate threshold corresponding to the equal comparison indicators of grid construction and energy storage configuration. Preliminary measures are determined based on the comparison results of the actual penetration rate and the threshold, thus achieving a systematic analysis and scientific improvement of the grid connection carrying capacity of distributed photovoltaic power generation. Furthermore, the preliminary measures are compared with the current boosting measures to determine the final implementation plan, ensuring the comprehensiveness and optimization of the selected plan. By constructing a quantitative comparison model based on the penetration rate threshold, it helps to make reasonable decisions between grid construction and energy storage configuration, effectively solving the problems of lack of comprehensive analysis of multi-dimensional source-grid-load-storage data in existing technologies, lack of scientific priority ranking and quantitative comparison basis for carrying capacity improvement measures, and insufficient comprehensiveness in the final implementation plan determination. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the process for improving the grid connection carrying capacity of distributed photovoltaic power generation based on investment economics comparison, provided in an embodiment of the present invention. Figure 2 These are the load characteristic curve and the photovoltaic output characteristic curve. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1, Figure 1 The present invention provides a method for improving the grid connection capacity of distributed photovoltaic power, comprising the following steps: S1, collect source-grid-load-storage data for the target power supply area; S2, based on the source-grid-load-storage data, perform current status problem analysis to obtain a reverse heavy overload equipment list, and perform planned demand analysis to obtain the bearing capacity margin; S3. If the carrying capacity margin is insufficient, then according to the preset priority, the improvement measures, including power grid construction and renovation and energy storage configuration, will be implemented step by step until the current problems are resolved and the planned access requirements are met. S4. For the two measures of power grid construction and renovation and energy storage configuration, the penetration rate threshold corresponding to the comparison index of the two measures is calculated by the comparison model, and the preliminary measures are determined based on the comparison result of the actual penetration rate and the threshold. S5. Compare the preliminary measures with the busbar boosting measures to determine the final implementation plan.

[0024] This embodiment provides a method for improving the grid connection carrying capacity of distributed photovoltaic power generation. This method achieves systematic selection and quantitative evaluation of measures to improve the grid connection carrying capacity of distributed photovoltaic power generation through a standardized improvement process and an economic comparison model.

[0025] S1 collects source-grid-load-storage data for the target power supply area.

[0026] In this embodiment, the source-grid-load-storage data includes power source data, grid data, load data, and energy storage data; The power data is obtained through the distributed photovoltaic monitoring system, the power grid dispatching system, and the power registration management system. It includes data on the installed capacity, output characteristics, spatial distribution, and penetration rate of distributed photovoltaic systems that have been connected to the grid in the designated power supply area or power grid equipment supply area, as well as the installed capacity data of various types of power sources that have been registered or planned. The output characteristics are described by the output characteristic function, and the penetration rate is the ratio of the installed capacity of distributed photovoltaic systems to the rated capacity of distribution transformers. The power grid data is obtained through the distribution automation system, power grid GIS system, equipment ledger management system and distribution network planning system, including equipment capacity, operation mode and grid structure information. The equipment capacity includes parameters such as the rated capacity of distribution transformers, the rated power supply capacity of feeders and the capacity of main transformers. The load data is obtained through the electricity information collection system, SCADA system, marketing management system and load forecasting system. It includes data such as the current load scale and electricity characteristics in the designated power supply area or power grid equipment supply area, as well as the predicted load type, load scale and load natural growth data. The electricity characteristics are described by the load characteristic function. The energy storage data is obtained through the energy storage monitoring system and the energy storage registration management system. It includes the types, spatial distribution and installed capacity, charging and discharging power and capacity ratio data of the energy storage that has been built and put into operation and the energy storage that is planned to be built. The spatial distribution includes three categories: source side, grid side and load side.

[0027] S2. Based on the source-grid-load-storage data, perform current status problem analysis to obtain a reverse heavy overload equipment list, and perform planned demand analysis to obtain the bearing capacity margin.

[0028] In this embodiment, the current state problem analysis and planned state demand analysis are applicable to three scenarios: distribution transformer substations, 10kV feeders, and 110kV main transformers. Analysis and evaluation are performed on various types of equipment within the target power supply area, using the following specific methods: The analysis of the current situation includes: The reverse load rate of power grid equipment is calculated using the following formula: , in, For distributed photovoltaic power output function, For equipment load function, The rated capacity of the equipment; Specifically, the equipment load function is ,in, This refers to the maximum utilization factor of the equipment. The load characteristic function can be obtained in the following way: Based on the historical load data recorded by the electricity information collection system, select the 24-hour load curve of a typical day (such as the annual maximum load day or a typical working day), divide the load value at each moment by the maximum load value of the day, and obtain the normalized load characteristic function, with a value range of 0 to 1; Specifically, the distributed photovoltaic output function ,in, For distributed photovoltaic installed capacity; The output characteristic function can be obtained in the following ways: based on the historical output data recorded by the distributed photovoltaic monitoring system, or based on the local solar resource data and photovoltaic module parameters, calculate the 24-hour output curve of a typical day, divide the output value at each moment by the installed capacity, and obtain the normalized output characteristic function, with a value range of 0 to 1. Furthermore, the net load function is calculated using the following formula: This represents the difference between the load and the output of distributed photovoltaic (PV) power. A negative net load indicates that the output of distributed PV power exceeds the load, resulting in reverse power flow. Figure 2 As shown in the figure, the load characteristic curve and photovoltaic output characteristic curve of a typical 24-hour day are displayed. The blue solid line in the figure is the normalized load characteristic function, which shows a typical double-peak characteristic in the morning and evening, with the peak occurring around 19:00. The red solid line is the normalized photovoltaic output characteristic function, which shows a bell-shaped distribution characteristic with high at noon and low at both ends, with the peak occurring around 12:00. It can be seen from the figure that the peak photovoltaic output period (10:00-14:00) overlaps with the relatively low load period. This time mismatch is one of the main reasons for the reverse power flow after distributed photovoltaic access. Furthermore, the maximum load of the equipment is calculated using the following formula: ; When the reverse load rate exceeds 80%, add the device to the reverse overload device list; Based on the regional power grid structure, equipment capacity configuration, load characteristics, and the penetration and distribution of distributed photovoltaic power, the causes of the current problems of weak load-bearing capacity or reverse overload are determined. Specifically, these include: Regarding the grid structure, analyzing whether line connections are sufficient, whether power flow transfer channels are limited, and whether the wiring method is reasonable; regarding equipment capacity, analyzing whether the rated capacity of the equipment is too small, whether the equipment utilization rate is too high, and whether the space for capacity expansion and modification is limited; regarding load characteristics, analyzing whether the off-peak load period overlaps with the peak photovoltaic output period, and whether the load regulation capacity is insufficient; and regarding distributed photovoltaic power, analyzing whether the penetration rate is too high, whether the spatial distribution is too concentrated, and whether the output characteristics match the load characteristics. It should be noted that the above causal analysis results can be used as a reference for selecting subsequent improvement measures and should be kept for future reference. When the reverse load rate of all devices in the list drops below 80%, the current problem is considered resolved.

[0029] The planned demand analysis includes: Obtain the registered and planned distributed photovoltaic installation capacity within a designated area or equipment supply area. The data comes from information such as distributed photovoltaic resource survey and development planning. The difference between the current equipment's carrying capacity and the installed capacity is calculated to obtain the carrying capacity margin, which reflects the degree of surplus or deficit of the current equipment for the planned distributed photovoltaic grid connection. The formula for calculating the current equipment's load-bearing capacity is as follows: ; in, The moment when the maximum reverse load rate occurs. The rated capacity of the equipment; The criteria for determining whether the carrying capacity margin meets the planned access requirements are as follows: if the carrying capacity margin is not less than zero, the planned access requirements are met; if the carrying capacity margin is less than zero, the carrying capacity margin is insufficient. Insufficient load capacity margin can also be determined by the following methods: Based on the predicted data of natural load growth in the power supply area, determine whether the future load growth can offset the distributed photovoltaic reverse power; if it can offset, the load capacity margin is sufficient; otherwise, the load capacity margin is insufficient. It should be noted that the specific method for determining whether future load growth can offset the reverse power fed back by distributed photovoltaic power is as follows: The current distributed photovoltaic power feedback is calculated based on the net load function; the calculation formula is as follows: ; Obtain the projected average annual load growth rate data for the power supply area over the next 3-5 years, and calculate the load growth at the end of the forecast period. The calculation formula is as follows: ; in, The moment when the maximum reverse power occurs. The load value of the equipment load function at the moment when the maximum reverse power occurs. This represents the average annual growth rate of the load. For predicting the number of years; If the load increase is greater than or equal to the reverse power, it is determined that the future load increase can offset the reverse power of distributed photovoltaic power, and the carrying capacity margin is sufficient; otherwise, it is determined that the carrying capacity margin is insufficient.

[0030] It should be noted that distributed photovoltaic grid connection capacity refers to the maximum installed capacity of distributed photovoltaic power that can be connected to the grid under the conditions of meeting grid operation safety and power quality requirements, taking into account factors such as load level, renewable energy utilization rate, and flexible resource adjustment. Reverse load rate refers to the ratio of reverse transmission power flowing through the transformer to its rated capacity, where transmission power flows from a low voltage level to a high voltage level. Reverse overload refers to the operating state where the maximum reverse load rate of grid equipment is not less than 80%, where the maximum reverse load rate of equipment reaches or exceeds 80% but does not reach 100% and is judged as reverse heavy load, and the maximum reverse load rate of equipment reaches or exceeds 100% and is judged as reverse overload.

[0031] S3. If the carrying capacity margin is insufficient, then according to the preset priority, improvement measures including power grid construction and renovation and energy storage configuration will be implemented step by step until the current problems are resolved and the planned access requirements are met.

[0032] In this embodiment, the step of executing different enhancement measures in order of preset priority includes: S301, using optimized power grid operation mode, determines whether the current problems can be resolved and the planned grid connection requirements can be met: The optimized power grid operation modes include two categories: First, adjusting the parallel operation of transformers to separate operation, which is applicable to 35 to 220 kV substations with two or more transformers operating in parallel mode. Under the premise of ensuring safety and reliability, the parallel operation mode is adjusted to separate operation mode. Second, optimizing the transfer of distributed photovoltaic or load through line operation mode. When the distributed photovoltaic output of a certain feeder is too large, resulting in reverse overload, the distributed photovoltaic on that feeder can be transferred to other lines in part or all through the tie switch, or a part of the load of other lines can be transferred to it, thereby changing the power flow direction and achieving the purpose of eliminating reverse overload. It should be noted that after optimizing the power grid operation mode, the reverse load rate and carrying capacity margin of the relevant equipment are recalculated. If the reverse heavy overload equipment list is empty and the carrying capacity margin is not less than zero, it is determined that the current problem has been resolved and the planned access requirements are met; otherwise, S302 is executed.

[0033] S302 If the conditions cannot be met, take source load-side guidance measures and then make a judgment; The source-load side guidance measures include energy storage configuration for distributed photovoltaic systems, capacity upgrades for distributed photovoltaic systems, energy storage configuration on the user side, and the construction of flexible and adjustable resource pools.

[0034] Specifically, the capacity upgrade of distributed photovoltaic (PV) systems refers to enabling distributed PV systems to possess observable, measurable, adjustable, and controllable capabilities. For new distributed PV projects, the goal is to guide distributed PV owners to install smart terminals to achieve these four capabilities. For existing distributed PV systems, the goal is to guide distributed PV owners to cooperate with the capacity upgrade, with 10 kV and above distributed PV systems being gradually upgraded to possess the corresponding capabilities, and low-voltage distributed PV projects gradually achieving adjustable and controllable capabilities based on observable and measurable capabilities. Specifically, distributed photovoltaic (PV) with energy storage refers to leveraging the advantage of a large peak-valley electricity price difference to guide distributed PV to the grid, promoting a PV plus energy storage plus peak-valley electricity price difference model. This involves storing excess electricity during peak PV output periods and releasing it during peak load or electricity price periods, thus achieving local consumption of distributed PV. Specifically, user-side energy storage configuration refers to conducting surveys on user energy storage needs, screening potential users based on electricity consumption, load characteristics, and reliability requirements, with a focus on large-scale enterprises and industrial and commercial users. This involves promoting energy storage configuration among potential users through policy promotion, peak-valley arbitrage guidance, and explanations of green electricity and carbon reduction, thereby leveraging its role in peak shaving and valley filling. For users or industrial parks that simultaneously possess distributed photovoltaic and charging facilities, the focus is on guiding the development of integrated photovoltaic, energy storage, and charging projects to promote the local consumption of distributed photovoltaic power. Specifically, building a flexible and adjustable resource pool refers to fully exploring the flexible and adjustable loads of air conditioning, charging, and other production and living activities on the user side, and updating and improving the list of demand response users; relying on digital system platforms and big data analysis methods, systematically analyzing the electricity consumption characteristics of various users, evaluating their demand response potential according to multi-dimensional indicators such as adjustable load scale, adjustable duration, and response rate, and finely screening and classifying potential demand response users; promoting the development of virtual power plant aggregation mode, relying on the virtual power plant platform to realize the wide-area aggregation, high-frequency sensing, and real-time response of fragmented flexible resources, and enhancing the absorption capacity of distributed photovoltaics during off-peak hours; It should be noted that after implementing source load-side guidance measures, the reverse load rate and bearing capacity margin of the relevant equipment are recalculated. If the reverse heavy overload equipment list is empty and the bearing capacity margin is not less than zero, it is determined that the current problem has been resolved and the planning access requirements are met; otherwise, S303 is executed.

[0035] S303 If the source-load side guidance measures still cannot meet the demand, then grid construction and renovation or energy storage should be adopted. The power grid construction and renovation includes three categories: line relocation, equipment capacity expansion, and grid structure renovation. Line relocation refers to examining the reverse load rate of another transformer in the same station or a nearby substation for transformer equipment with low current carrying capacity. If the reverse load rate of the other transformer in the same station or a nearby substation is still low, then a portion of the lines that are connected to distributed photovoltaic systems at the lower level of this transformer will be relocated to the other transformer or a nearby substation to achieve a redistribution of load and power. If the reverse load rate of the other transformer in the same station or a nearby substation is also high, then other solutions will be considered.

[0036] Equipment capacity expansion refers to taking into account factors such as the current operating status of equipment, the development of distributed photovoltaic power and load in the power supply area, and equipment selection standards, and adopting strategies such as capacity expansion, renovation, and new construction as needed. For transformer equipment, if the current capacity is too small, it can be upgraded to a larger capacity in a timely manner based on the current reverse load rate and source load forecasts. If there is no room for capacity expansion or renovation measures, or if implementation still cannot solve the problem, then new transmission and transformation projects in the surrounding area should be selected from the power grid planning project database, and the construction and commissioning time should be properly arranged in conjunction with the economic and social development of the power supply area, power generation forecasts, and distributed photovoltaic installation forecasts.

[0037] The main targets of the grid upgrade are 10 kV or 20 kV lines. Specific upgrade schemes include converting overhead lines from multi-segment single radial connection to multi-segment single tie connection, circuit breaker connection schemes within cable double ring network groups, connection schemes between connection groups, and flexible DC interconnection schemes. By increasing line connections, the power flow transfer capacity and distributed photovoltaic absorption capacity can be improved.

[0038] Configuring energy storage refers to installing energy storage devices on the grid side. Typical scenarios include areas with severe photovoltaic backfeeding, feeders, and even substations. Energy storage can also be configured as needed to optimize power quality and improve power supply reliability after distributed photovoltaic grid connection. Energy storage devices absorb excess electricity during peak output periods of distributed photovoltaic systems and release electricity during peak load periods, effectively smoothing power fluctuations and reducing the reverse load rate of the equipment. It should be noted that the specific selection method for the two measures of power grid construction and renovation and energy storage configuration is detailed in S4. The penetration rate threshold is calculated by comparing the actual penetration rate and then determined.

[0039] S4. For the two measures of power grid construction and renovation and energy storage configuration, the penetration rate threshold corresponding to the comparison index of the two measures is calculated by the comparison model. The preliminary measures are determined based on the comparison result of the actual penetration rate and the threshold.

[0040] In this embodiment, for the two measures of power grid construction and renovation and energy storage configuration, a comparison model is used to calculate the penetration rate threshold corresponding to the equality of the comparison indicators of the two measures. The preliminary measures are determined based on the comparison result of the actual penetration rate and the threshold. To ensure the economic comparability of the two measures, the same problem scenario and solution objective are set. That is, the above two measures are only considered when the power grid equipment experiences power backflow and causes equipment overload. Furthermore, the two measures face the same scenario, and the objective is to precisely solve the reverse overload problem of the equipment. The comparison model is established for three scenarios: distribution transformer area, 10 kV feeder, and 110 kV main transformer. The specific steps are as follows: S401, draw the pre-balance load curve based on the equipment load function, and draw the post-balance load curve based on the net load function; Specifically, the load functions are defined as follows for the three scenarios: In the scenario of distribution transformer area: The equipment load function is: ,in, For the rated capacity of the distribution transformer, This is the maximum utilization factor of the distribution transformer. This is the load characteristic function; Net load function: ; Maximum load of distribution transformer: ; In the case of a 10 kV feeder: The equipment load function is: ,in, For the rated capacity of the feeder, This is the maximum utilization factor of the feeder. This is the load characteristic function; Net load function: ; Maximum load on feeder: ; In the scenario of a 110 kV main transformer: The equipment load function is: ,in, Main transformer rated capacity, The maximum utilization factor of the main variable This is the load characteristic function; Net load function: ; Maximum load of main transformer: ; The universal distributed photovoltaic output function for the three scenarios is as follows: ,in, For distributed photovoltaic installed capacity, This is the output characteristic function; It should be noted that, in this embodiment, to simplify calculations, the same distributed photovoltaic output function is used for all three scenarios. This function is obtained by normalizing a typical sunny-day photovoltaic output curve. In practical applications, a simultaneous output coefficient can be introduced to correct the output based on the geographical distribution range and photovoltaic aggregation characteristics of each scenario. The range of simultaneous output coefficients for different scenarios is shown in Table 1. Table 1

[0041] Therefore, the formula for calculating the penetration threshold is: ,in, The rated capacity of equipment in the corresponding scenario when the power grid construction and renovation selection indicators are equal to the energy storage configuration selection indicators.

[0042] S402, determine the reverse heavy overload period based on the reverse load rate, including: when When the maximum value exceeds 80%, determine the reverse overload decomposition line. , The point of intersection with the balanced load curve corresponds to the boundary of the reverse heavy overload period. Therefore, the calculation formula for the reverse power transmission from distributed photovoltaic power during the reverse overload period is as follows:

[0043] in, , This represents the boundary of the reverse heavy overload period.

[0044] S403, after determining the reverse overload period and the reverse power transmission, the calculation formula for the power grid construction and renovation comparison index is as follows:

[0045] in, The moment when the maximum reverse load rate occurs. For the rated capacity of the equipment, To ensure a reasonable load rate for the equipment, The comprehensive cost per unit capacity of the equipment, For the entire life cycle of the equipment, For line length factor, L is the floor function; for distribution transformer substation scenarios and 110 kV main transformer scenarios, L = 1; for 10 kV feeder scenarios, L is the feeder power supply radius. It should be noted that the relevant parameter values ​​are shown in Table 2 for the three scenarios; Table 2

[0046] The calculation formula for the energy storage selection index is as follows: , in, , This is the boundary of the reverse heavy overload period. For the overall cost of energy storage, For the entire life cycle of energy storage; It should be noted that the values ​​of energy storage-related parameters for the three scenarios are shown in Table 3: Table 3

[0047] It should be noted that the overall cost of energy storage includes the cost of the energy storage unit, converter, installation, commissioning and operation and maintenance; the overall cost of energy storage varies in different scenarios, mainly affected by factors such as installation scale, access method and operation and maintenance costs.

[0048] S404, solve for the distributed photovoltaic installed capacity when the power grid construction and renovation comparison index is equal to the energy storage configuration comparison index, and then calculate the penetration rate threshold; It should be noted that since both the grid construction and renovation selection index and the energy storage configuration selection index are functions of the distributed photovoltaic installed capacity, setting the grid construction and renovation selection index equal to the energy storage configuration selection index allows for the corresponding solutions to be obtained through numerical iteration or analytical methods. For three scenarios—distribution transformer area, 10kV feeder, and 110kV main transformer—solutions are performed separately, with the specific steps as follows: (1) Determine the rated capacity of the equipment and the initial search range of the distributed photovoltaic installed capacity based on the scenario type. , ]; (2) Take several discrete points within the search range and calculate the power grid construction and renovation comparison index and the energy storage configuration comparison index respectively; (3) Locate the interval where the sign of the difference between the power grid construction and renovation selection indicators and the energy storage configuration selection indicators changes; (4) Within this interval, when the grid construction and renovation selection index equals the energy storage selection index, the corresponding distributed photovoltaic installed capacity value is obtained by using the bisection method or Newton's iteration method. ; The formula for calculating the penetration threshold is as follows: , in, The distributed photovoltaic installed capacity is the same as the grid construction and renovation comparison index and the energy storage configuration comparison index.

[0049] S405, the preliminary measures are determined based on the comparison between the actual penetration rate and the threshold, and the criteria are as follows: When the actual penetration rate < , At that time, the initial measure was to configure energy storage; When the actual penetration rate > , At that time, the initial measures were power grid construction and renovation; When the actual penetration rate = , Initial measures at that time included configuring energy storage or upgrading the power grid.

[0050] S5, compare the preliminary measures with the busbar boosting measures to determine the final implementation plan, specifically as follows: First, assess whether the conditions for implementing the preliminary measures are met; if not, select the confluence boosting measure. The implementation condition assessment specifically includes: (1) Site condition assessment: Assess whether the site required for equipment installation meets the requirements for area, load-bearing capacity, ventilation and heat dissipation, etc. (2) Power grid access condition assessment: assess whether the voltage level, short-circuit capacity, relay protection configuration, etc. of the access point meet the access requirements; (3) Policy and planning conditions assessment: Assess whether there are any policy and planning restrictions such as planning red lines, environmental protection restrictions, and power facility protection zones; If any of the above conditions are not met, the implementation conditions are deemed not met, and the merging booster measure is selected.

[0051] Furthermore, assess the adaptability of the initial measures to future distributed photovoltaic installation growth; if the adaptability is insufficient, select the converter boosting measure. Adaptability assessment specifically includes: (1) Obtain regional distributed photovoltaic development planning data and determine the expected installed capacity growth of distributed photovoltaic in the next 3-5 years; (2) Assess the carrying capacity improvement after the implementation of the preliminary measures, wherein the carrying capacity improvement of power grid construction and renovation is equal to the new equipment capacity multiplied by the reasonable load rate, and the carrying capacity improvement of energy storage configuration is equal to the rated power of energy storage; (3) If the increase is greater than or equal to the growth, the adaptability is deemed sufficient and the preliminary measures are selected as the final implementation plan; if the increase is less than the growth, the adaptability is deemed insufficient and the merging and boosting measures are selected. The aforementioned busbar boosting measures are divided into two categories based on the access voltage level: one is busbar boosting to 10 kV, which collects distributed photovoltaic power to the low-voltage collection network via AC or DC, and then connects to the 10 kV line via a step-up transformer; the other is busbar boosting to 35 kV or 110 kV, which collects distributed photovoltaic power and then connects to the 35 kV or 110 kV busbar via a step-up transformer. If the conditions for implementing the preliminary measures are met and the adaptability is sufficient, then the preliminary measures shall be selected as the final implementation plan.

[0052] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0053] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0054] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0055] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0056] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0057] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for improving the grid connection carrying capacity of distributed photovoltaic systems, characterized in that, Includes the following steps: Collect source, grid, load, and storage data for the target power supply area; Based on the source-grid-load-storage data, a current status problem analysis is performed to obtain a reverse heavy overload equipment list, and a planned demand analysis is conducted to obtain the carrying capacity margin. If the carrying capacity margin is insufficient, then upgrade measures, including grid construction and renovation and energy storage configuration, will be implemented step by step according to the preset priority until the current problems are resolved and the planned access requirements are met. Among them, for the two measures of power grid construction and renovation and energy storage configuration, the penetration rate threshold corresponding to the comparison index of the two measures is calculated by the comparison model, and the preliminary measures are determined based on the comparison result of the actual penetration rate and the threshold. The preliminary measures were compared with the busbar boosting measures to determine the final implementation plan.

2. The method for improving the grid connection carrying capacity of distributed photovoltaic power according to claim 1, characterized in that, The analysis of the current situation includes: Calculate the reverse load rate of the power grid equipment. When the reverse load rate exceeds 80%, add the equipment to the reverse overload equipment list. Based on the regional power grid structure, equipment capacity configuration, load characteristics, and the penetration and distribution of distributed photovoltaic power, the causes of the current problems of weak load-bearing capacity or reverse overload are determined. When the reverse load rate of all devices in the list drops below 80%, the current problem is considered resolved.

3. The method for improving the grid connection capacity of distributed photovoltaic power generation according to claim 1, characterized in that, The planned demand analysis includes: Obtain the registered and planned distributed photovoltaic installation capacity within the designated area or equipment supply area; The difference between the current equipment's carrying capacity and the installed capacity is calculated to obtain the carrying capacity margin; Determine whether the carrying capacity margin meets the planned access requirements: If the carrying capacity margin is less than zero, it is determined that the carrying capacity margin is insufficient; otherwise, it is determined that the planned access requirements are met.

4. The method for improving the grid connection carrying capacity of distributed photovoltaic power according to claim 1, characterized in that, The implementation of improvement measures, including power grid construction and upgrading, and energy storage configuration, in a step-by-step manner according to preset priorities until the current problems are resolved and the planned grid connection requirements are met includes: By optimizing the power grid operation mode, it can be determined whether the current problems can be resolved and the planned grid connection requirements can be met: If the requirements cannot be met, source load-side guidance measures should be implemented before making a final judgment. If this still cannot be achieved, then grid construction and renovation or energy storage should be implemented. The optimized power grid operation mode includes adjusting the parallel operation of transformers to separate operation and optimizing the transfer of distributed photovoltaic or loads through line operation mode; The source-load side guidance measures include distributed photovoltaic configuration with energy storage, distributed photovoltaic capacity upgrade, user-side configuration with energy storage, and construction of flexible and adjustable resource pools.

5. The method for improving the grid connection capacity of distributed photovoltaic power generation according to claim 1, characterized in that, The calculation of the penetration rate threshold corresponding to the equality of the comparison indicators of the two measures through the comparison model includes: Plot the pre-balance load curve based on the equipment load function, and plot the post-balance load curve based on the net load function. Calculate the reverse load rate of the equipment and determine the reverse heavy overload period. to And calculate the distributed photovoltaic power feedback during that period. ; Calculate the selection criteria for power grid construction and renovation and the selection criteria for energy storage configuration separately; Solve for the distributed photovoltaic installed capacity when the power grid construction and renovation selection index is equal to the energy storage configuration selection index, and then calculate the penetration rate threshold; Wherein, the equipment load function is ,in, For the rated capacity of the equipment, The maximum utilization factor of the equipment. This is the load characteristic function. For time; The output function of distributed photovoltaic power is ,in, For distributed photovoltaic installed capacity, This is the output characteristic function; Net load function: ; Maximum load of equipment: ; Penetration threshold: ,in, The distributed photovoltaic installed capacity is the same as the grid construction and renovation comparison index and the energy storage configuration comparison index.

6. The method for improving the grid connection carrying capacity of distributed photovoltaic power according to claim 5, characterized in that, The formula for calculating the reverse load rate is as follows: in, For distributed photovoltaic power output function, For equipment load function, The rated capacity of the equipment; The determination of the reverse heavy overload period includes: when When the maximum value exceeds 80%, determine the reverse overload decomposition line. , The point of intersection with the balanced load curve corresponds to the boundary of the reverse heavy overload period. The formula for calculating the reverse power transmission is as follows: in, and This represents the boundary of the reverse heavy overload period.

7. The method for improving the grid connection capacity of distributed photovoltaic power generation according to claim 5, characterized in that, The calculation formula for the power grid construction and renovation selection indicators is as follows: in, The moment when the maximum reverse load rate occurs. For the rated capacity of the equipment, To ensure a reasonable load rate for the equipment, The comprehensive cost per unit capacity of the equipment. For the entire life cycle of the equipment, For line length factor, L is the floor function; for distribution transformer substation scenarios and 110 kV main transformer scenarios, L = 1; for 10 kV feeder scenarios, L is the feeder power supply radius. The calculation formula for the energy storage selection index is as follows: in, For the overall cost of energy storage, This refers to the entire lifecycle of energy storage.

8. The method for improving the grid connection capacity of distributed photovoltaic power generation according to claim 5, characterized in that, The preliminary measures are determined based on the comparison between the actual penetration rate and the threshold, and the criteria are as follows: When the actual penetration rate < , At that time, the initial measure was to configure energy storage; When the actual penetration rate > , At that time, the initial measures were power grid construction and renovation; When the actual penetration rate = , Initial measures at that time included configuring energy storage or upgrading the power grid.

9. The method for improving the grid connection carrying capacity of distributed photovoltaic power according to claim 3, characterized in that, The insufficient bearing capacity margin also includes the following judgment methods: Based on the predicted data of natural load growth in the power supply area, it is determined whether future load growth can offset the power fed back by distributed photovoltaic power. If the load can be offset, the bearing capacity margin is sufficient; otherwise, the bearing capacity margin is insufficient.

10. The method for improving the grid connection carrying capacity of distributed photovoltaic power according to claim 1, characterized in that, The comparison of the preliminary measures with the bus boosting measures includes: Assess whether the conditions for implementing the preliminary measures are met; if not, select the confluence boosting measure. Assess the adaptability of the initial measures to the future growth of distributed photovoltaic installations; if the adaptability is insufficient, select the converter boosting measures. If the conditions for implementing the preliminary measures are met and the adaptability is sufficient, then the preliminary measures shall be selected as the final implementation plan.

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