CN108399505B - Distributed photovoltaic power supply access capacity planning method and terminal equipment - Google Patents

Abstract

The invention relates to the technical field of photovoltaic access power grid planning, and provides a distributed photovoltaic power supply access capacity planning method and terminal equipment. The method comprises the following steps: acquiring daily load active electric quantity, daily load apparent power, photovoltaic daily power generation active electric quantity and photovoltaic daily power generation apparent power in a preset statistical period of a planning area, subtracting the photovoltaic daily power generation active electric quantity and the daily load active electric quantity to obtain a first difference sequence, and subtracting the photovoltaic daily power generation apparent power and the daily load apparent power to obtain a second difference sequence; calculating the median of the first difference sequence, and performing bilateral inspection on whether the median is reasonable; and determining the planning capacity of the planning area according to the result of the bilateral test, the first difference sequence and the second difference sequence. The method and the device can determine the planning capacity of the planning area by using the detected median of the daily net output electric quantity, and reduce the scale of transformation of the photovoltaic power supply to the power distribution network.

Description

Distributed photovoltaic power supply access capacity planning method and terminal equipment

technical field

The invention relates to the technical field of photovoltaic access grid planning, in particular to a distributed photovoltaic power supply access capacity planning method and terminal equipment.

Background technique

Photovoltaic poverty alleviation is one of the technical means to implement targeted poverty alleviation in my country. However, due to the large power supply radius of the rural power grid and the low load density, although the rural power grid has been reconstructed many times for a long time, it mainly solves the problem of power supply quality in well-urbanized areas. However, due to site requirements, photovoltaic poverty alleviation is mostly carried out in villages with relatively poor traffic conditions and economic foundations outside cities and towns in the form of poverty alleviation, and the original grid is difficult to meet the demand for photovoltaic power delivery. At present, the access capacity planning of photovoltaic power sources is based on the maximum value of power generation, which results in a higher capacity standard for capacity increase in the transformation of the distribution network, and the scale of the transformation of the distribution network is huge, which in turn leads to the need for photovoltaic poverty alleviation to connect to the rural power grid. The scale of the investment is too large to be widely implemented.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention provide a distributed photovoltaic power supply access capacity planning method and a terminal device, so as to solve the problem that the current photovoltaic power supply access capacity planning based on the maximum value of power generation results in a huge transformation of the distribution network and the implementation cost. big problem.

A first aspect of the embodiments of the present invention provides a distributed photovoltaic power supply access capacity planning method, including:

Acquire the daily load active power, daily load apparent power, photovoltaic daily power generation active power, and photovoltaic daily TV power within the preset statistical period of the planning area, and use the photovoltaic daily power generation active power and the daily load active power as a value. The first difference sequence is obtained by the difference, and the second difference sequence is obtained by making the difference between the daily photovoltaic power and the daily load apparent power;

Calculate the median of the first difference sequence, and perform a bilateral test on whether the median is reasonable;

The planned capacity of the planned area is determined according to the result of the bilateral test, the first difference sequence and the second difference sequence.

A second aspect of the embodiments of the present invention provides a distributed photovoltaic power supply access capacity planning device, including:

The obtaining module is used to obtain the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power and the photovoltaic daily TV power in the preset statistical period of the planning area, and compare the photovoltaic daily power generation active power and the photovoltaic power generation daily power. The first difference sequence is obtained by making a difference in the active power of the daily load, and the second difference sequence is obtained by making the difference between the daily photovoltaic power and the apparent power of the daily load;

a test module, configured to calculate the median of the first difference sequence, and to perform a bilateral test on whether the median is reasonable;

A processing module, configured to determine the planned capacity of the planned area according to the result of the bilateral test, the first difference sequence and the second difference sequence.

A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the first computer program when the processor executes the computer program. Distributed photovoltaic power supply access capacity planning method in one aspect.

A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, realizes the distributed photovoltaic power supply access capacity in the first aspect planning method.

Compared with the prior art, the embodiment of the present invention has the beneficial effect that the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power and the photovoltaic daily power generation TV power in the preset statistical period according to the planning area are obtained. The first difference sequence and the second difference sequence, and the planning capacity of the planning area is determined according to the bilateral test result of the median of the first difference sequence, the first difference sequence, and the second difference sequence, and the tested capacity can be used. The median of the daily net output power can determine the planned capacity of the planned area, avoid the problem of higher capacity standards in the transformation of the distribution network caused by the capacity planning based on the maximum value of power generation, and can reduce the increased capacity of the distribution network. , reduce the transformation scale of photovoltaic power supply to the distribution network, and reduce the implementation cost of photovoltaic power supply to the distribution network.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present invention. In some embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

Fig. 1 is the realization flow chart of the distributed photovoltaic power supply access capacity planning method provided by the embodiment of the present invention;

2 is a flow chart of the implementation of bilateral inspection in the method for planning the access capacity of distributed photovoltaic power sources provided by an embodiment of the present invention;

3 is a schematic diagram of a distributed photovoltaic power supply access capacity planning device provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram of a terminal device provided by an embodiment of the present invention.

Detailed ways

In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are set forth in order to provide a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

In order to illustrate the technical solutions of the present invention, the following specific embodiments are used for description.

Fig. 1 is the realization flow chart of the distributed photovoltaic power supply access capacity planning method provided by the embodiment of the present invention, and the details are as follows:

In S101 , obtain the daily load active power, daily load apparent power, photovoltaic daily power generation active power, and photovoltaic daily power generation TV power within a preset statistical period of the planning area, and combine the photovoltaic daily power generation active power and the daily power generation active power A first difference sequence is obtained by making a difference in the active power of the load, and a second difference sequence is obtained by making a difference between the daily photovoltaic power and the apparent power of the daily load.

In this embodiment, the planning area is a power grid area that needs to perform photovoltaic power supply access capacity planning. The preset statistical period is a preset time period for obtaining historical data of grid power consumption and photovoltaic power generation, which can be set according to actual needs. For example, the preset statistical period may be three years, one year, or one season.

The daily active power and apparent power of the daily load in the preset statistical period for monitoring distribution transformers in the planning area can be obtained through the power grid database, and the daily load and apparent power in the preset statistical period for the metering of the photovoltaic power connected to the grid in the planning area can be obtained. PV daily active power and PV daily TV power.

The first difference sequence is obtained by taking the difference between the daily photovoltaic active power generation and the daily load active power in each day in the preset statistical period, and the data obtained by the difference between the photovoltaic daily power generation active power and the daily load active power on the i-th day can be recorded as ΔW _i . Among them, a positive value of ΔW _i means that the power generation on the ith day is greater than the electricity consumption, and a negative value of ΔW _i means that the power generation on the ith day is less than the electricity consumption. The second difference sequence is obtained by taking the difference between the PV daily TV power and the daily load apparent power of each day in the preset statistical period, and the difference between the photovoltaic daily TV power and the daily load apparent power on the i-th day can be obtained. The data is recorded as ΔS _i .

In S102, the median of the first difference sequence is calculated, and a bilateral test is performed on whether the median is reasonable.

In this embodiment, the median of the first difference sequence may be calculated, and a bilateral test may be used to determine whether the calculated median is reasonable. Among them, bilateral test, also known as two-tailed test and two-sided test, is a method of constructing a critical region for testing by using the density curve of the test statistic and the tail area of the left and right sides of the area enclosed by the x-axis in hypothesis testing.

As an embodiment of the present invention, the step of "calculating the median of the first difference sequence" in S102 may include:

Sort the first difference value sequence; the first difference value sequence is represented as ΔW ₁ ,...,ΔW _i ,...,ΔW _N , and the sorted first difference value sequence is represented as ΔW ₍₁₎ ,..., ΔW _(j) , . . . , ΔW _(N) ; wherein N is the number of data in the first difference sequence;

If N is an odd number, the median of the first difference sequence is ΔW _((N+1)/2) ;

If N is an even number, the median of the first difference sequence is 1/2(ΔW _(N/2) +ΔW _((N+2)/2) ).

In this embodiment, the sorting may be in ascending order or in descending order, which is not limited here. ΔW ₀ can be used to represent the median of the first difference sequence, if N is an odd number, then ΔW ₀ =ΔW _((N+1)/2) , if N is an even number, then ΔW ₀ =1/2(ΔW _{(N/ 2)} +ΔW _((N+2)/2) ).

For example, if the first difference sequence is -4, 8, 3, 10, 12, the first difference sequence in ascending order is -4, 3, 8, 10, 12. At this time, N=5 is an odd number, Therefore ΔW ₀ =ΔW _((N+1)/2) =ΔW ₍₃₎ =8, that is, the median is 8; if the first difference sequence is -4, 8, 3, 10, 12, 2, according to The first difference sequence after ascending order is -4, 2, 3, 8, 10, 12. At this time, N=6 is an even number, so ΔW ₀ =1/2(ΔW _(N/2) +ΔW _{((N +2)/2)} )=1/2(ΔW ₍₃₎ +ΔW ₍₄₎ )=1/2(3+8), which means the median is 5.5.

In this embodiment, by sorting the first difference sequence, and then determining the median of the first difference sequence according to the sorted sequence, the calculation speed of the median of the first difference sequence can be improved, thereby reducing distributed photovoltaic power generation Time required for access capacity planning and improve planning efficiency.

As an embodiment of the present invention, as shown in FIG. 2 , the step of “performing a bilateral test on whether the median is reasonable” in S102 may include:

In S201, each data in the first difference sequence is compared with the median, and then an absolute value is obtained to obtain an absolute value sequence; each data in the first difference sequence and the absolute value are obtained Each data in the sequence corresponds one-to-one.

In this embodiment, if the i-th data in the first difference sequence is represented by ΔW _i and the median is represented by ΔW ₀ , the i-th data in the absolute value sequence can be represented as |ΔW _i -ΔW ₀ | .

In S202, a rank corresponding to each data in the absolute value sequence is calculated.

In this embodiment, the rank corresponding to each data in a sequence is the position of each data after the sequence is arranged in ascending order. R _i can be used to represent the rank corresponding to the i-th data. For example, if the absolute value sequence is 14, 18, 13, 20, 22, 12, and the absolute value sequence in ascending order is 12, 13, 14, 18, 20, 22, then the rank corresponding to each data in the absolute value sequence is in order 3, 4, 2, 5, 6, 1.

In S203, the hypothesis H ₀ of the bilateral test is determined: M=ΔW ₀ .<=>H ₁ : M≠ΔW ₀ , and the test statistic T=min(T+, T-) is calculated, where M represents the first The actual median of a difference sequence, ΔW ₀ . represents the calculated median of the first difference sequence, and T+ represents the sum of the ranks corresponding to each first data, and the first data is the first data. The data in a difference sequence is greater than the median; T- represents the sum of ranks corresponding to each second data, and the second data is the data in the first difference sequence that is smaller than the median.

In this embodiment, it is assumed that H ₀ indicates that the calculated median is reasonable, and that H ₁ is assumed to indicate that the calculated median is unreasonable. The test statistics are described below in conjunction with the example data in Table 1. The first row in Table 1 is the first difference sequence; the second row is the result of the difference between each data in the first difference sequence and the median. In this example, the median of the first difference sequence is 8; The row is the absolute value sequence; the fourth row is the rank corresponding to each data in the absolute value sequence.

The first data is data greater than the median in the first difference sequence, that is, the first data is ΔW _i with ΔW _i -ΔW ₀ >0, such as data 10 and 12 in the first row of Table 1. T+ represents the sum of the ranks corresponding to each first data, such as the sum of 2 (rank corresponding to data 10) and 3 (rank corresponding to data 12) in the fourth row in Table 1, that is, obtained from the example data in Table 1 T+ is 5.

The second data is data less than the median in the first difference sequence, that is, the first data is ΔW _i with ΔW _i -ΔW ₀ <0, such as data -4 and 3 in the first row of Table 1. T- represents the sum of the ranks corresponding to each second data, such as the sum of 5 (rank corresponding to data-4) and 4 (rank corresponding to data 3) in the fourth row in Table 1, that is, according to the example data in Table 1 The T- out is 9.

Table 1 Example data

In S204, the corresponding p value is searched in the normal distribution table according to the calculated test statistic, and whether the median is reasonable is judged according to the p value.

In this embodiment, whether the median is reasonable can be judged according to the corresponding p value of the calculated test statistic in the normal distribution table.

Optionally, according to the calculated test statistic, check the normal distribution table at the confidence level α to obtain the p value, if T>p, accept H ₀ , and consider the obtained median to be reasonable; otherwise, consider the median unreasonable.

Optionally, a rank test distribution table corresponding to the test statistic and the p value can be established, the corresponding p value is searched in the rank test distribution table according to the calculated test statistic, and then the p value is compared with the preset threshold. If the p value is less than the preset threshold, then accept H ₀ , and consider the obtained median to be reasonable; otherwise, consider the median to be unreasonable.

In S103, the planned capacity of the planned area is determined according to the result of the bilateral test, the first difference sequence and the second difference sequence.

In this embodiment, the planning capacity of the planning area may be selectively determined according to the first difference sequence or the second difference sequence according to the result of the bilateral test.

In the embodiment of the present invention, the first difference sequence and the second difference sequence are obtained by obtaining the first difference sequence and the second difference sequence according to the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power, and the photovoltaic daily power generation TV power in the preset statistical period of the planning area, The planned capacity of the planned area can be determined according to the bilateral test results of the median of the first difference sequence, the first difference sequence and the second difference sequence, and the tested median of the daily net output power can be used to determine the planned capacity of the planned area. Planning capacity, avoiding the problem of higher capacity standards in distribution network transformation caused by capacity planning based on the maximum value of power generation, which can reduce the capacity of distribution network to increase capacity and reduce the transformation of photovoltaic power into distribution network Scale and reduce the implementation cost of connecting photovoltaic power to the distribution network.

As an embodiment of the present invention, S103 may include:

If the result of the bilateral test is that the median is reasonable, the planned capacity of the planning area is determined according to the first difference sequence; if the result of the bilateral test is that the median is unreasonable, the The maximum value in the second difference sequence is used as the planned capacity of the planned area.

Optionally, if the result of the bilateral test is that the median is reasonable, it indicates that the first difference series data is normal, and ΔW _i /24 can be determined as the planning capacity of the planning area; if the result of the bilateral test is that the median is unreasonable , it indicates that the first difference sequence data is abnormal, and the maximum value in the second difference sequence can be used as the planning capacity of the planning area. If ΔS _i is used to represent the i-th data in the second difference value sequence, the maximum value in the second difference value sequence can be represented as ΔS _{i_max} .

Optionally, if the result of the bilateral test is that the median is reasonable, it indicates that the data of the first difference series is normal, and the maximum value in the first difference series (which can be expressed as ΔW _i-max ) can be divided by 24 hours as Planning capacity, that is, ΔW _i-max /24 can be determined as the planning capacity of the planning area; if the result of the bilateral test is that the median is unreasonable, it indicates that the first difference sequence data is abnormal, and the second difference sequence The maximum value in is used as the planned capacity of the planned area.

As an embodiment of the present invention, the preset statistical period includes at least one season, the first difference sequence includes a first difference sequence corresponding to each season, and the second difference sequence includes a first difference sequence corresponding to each season two-difference sequence;

S102 may include:

Calculate the median of the first difference series corresponding to each season, and conduct a bilateral test to see if the median corresponding to each season is reasonable;

S103 may include:

Determine the planning capacity corresponding to each season according to the results of the bilateral test corresponding to each season, the first difference sequence corresponding to each season, and the second difference sequence corresponding to each season;

The maximum value among the planned capacities corresponding to each season is determined as the planned capacity of the planned area.

In this embodiment, the preset statistical period may include at least one season, first determine the planned capacity corresponding to each season, and then determine the maximum value of the planned capacity corresponding to each season as the planned capacity of the planned area.

For example, the preset statistical period can be one year. Since spring and autumn have similar electricity consumption, spring and autumn can be treated as one season, so the preset statistical period includes three seasons: spring and autumn, summer and winter. For example, summer can be from May 1st to September 15th, and winter can be from October 20th to March 31st.

The first difference sequence corresponding to each season can be obtained by taking the difference between the active power of photovoltaic daily generation and the active power of daily load corresponding to each season, and the difference between the daily photovoltaic power and apparent power of daily load corresponding to each season can be obtained. The second difference series corresponding to the season.

Optionally, after determining the maximum value of the planned capacity corresponding to each season as the planned capacity of the planned area, the maximum load can be flexibly adjusted according to the user's proposed agricultural situation, and then the determined planned capacity can be adjusted according to the maximum load. Make further cuts to get the final planned capacity.

This embodiment proposes an access limit capacity planning method that considers the interaction between photovoltaic distributed power generation and flexibly adjustable loads. Considering the electric heating load in winter, the air conditioning load in summer and other agricultural flexibly adjustable loads, the electricity generated by photovoltaic poverty alleviation is considered. Under the influence factors of local consumption, the difference between the verified daily net output power median and the user's expected new flexible adjustment power is used to determine the final exchange power, so as to avoid the photovoltaic poverty alleviation based on the maximum value of power generation being connected to the rural power grid The waste of funds brought by the planning will reduce the investment scale of photovoltaic poverty alleviation in rural power grids, and improve the efficiency of distribution network investment and utilization.

In the embodiment of the present invention, the first difference sequence and the second difference sequence are obtained by obtaining the first difference sequence and the second difference sequence according to the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power, and the photovoltaic daily power generation TV power in the preset statistical period of the planning area, The planned capacity of the planned area can be determined according to the bilateral test results of the median of the first difference sequence, the first difference sequence and the second difference sequence, and the tested median of the daily net output power can be used to determine the planned capacity of the planned area. Planning capacity, avoiding the problem of higher capacity standards in distribution network transformation caused by capacity planning based on the maximum value of power generation, which can reduce the capacity of distribution network to increase capacity and reduce the transformation of photovoltaic power into distribution network Scale and reduce the implementation cost of connecting photovoltaic power to the distribution network.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Corresponding to the distributed photovoltaic power supply access capacity planning method described in the above embodiment, FIG. 3 shows a schematic diagram of a distributed photovoltaic power supply access capacity planning apparatus provided by an embodiment of the present invention. For convenience of explanation, only the parts related to this embodiment are shown.

Referring to FIG. 3 , the apparatus includes an acquisition module 31 , a verification module 32 and a processing module 33 .

The acquisition module 31 is used to acquire the daily load active power, daily load apparent power, photovoltaic daily power generation active power, and photovoltaic daily TV power in the preset statistical period of the planning area, and calculate the daily photovoltaic power generation active power and all the power. A first difference sequence is obtained by making a difference in the active power of the daily load, and a second difference sequence is obtained by making a difference between the daily photovoltaic power and the apparent power of the daily load.

The testing module 32 is configured to calculate the median of the first difference sequence, and perform a bilateral test on whether the median is reasonable.

The processing module 33 is configured to determine the planned capacity of the planned area according to the result of the bilateral test, the first difference sequence and the second difference sequence.

Optionally, the preset statistical period includes at least one season, the first difference sequence includes a first difference sequence corresponding to each season, and the second difference sequence includes a second difference sequence corresponding to each season. ;

The inspection module 32 is used for:

Calculate the median of the first difference series corresponding to each season, and conduct a bilateral test to see if the median corresponding to each season is reasonable;

The processing module 33 is used for:

Determine the planning capacity corresponding to each season according to the results of the bilateral test corresponding to each season, the first difference sequence corresponding to each season, and the second difference sequence corresponding to each season;

The maximum value among the planned capacities corresponding to each season is determined as the planned capacity of the planned area.

Optionally, the inspection module 32 is used for:

Sort the first difference value sequence; the first difference value sequence is represented as ΔW ₁ ,...,ΔW _i ,...,ΔW _N , and the sorted first difference value sequence is represented as ΔW ₍₁₎ ,..., ΔW _(j) , . . . , ΔW _(N) ; wherein N is the number of data in the first difference sequence;

If N is an odd number, the median of the first difference sequence is ΔW _((N+1)/2) ;

If N is an even number, the median of the first difference sequence is 1/2(ΔW _(N/2) +ΔW _((N+2)/2) ).

Optionally, the inspection module 32 is used for:

Each data in the first difference sequence is compared with the median to obtain an absolute value to obtain an absolute value sequence; each data in the first difference sequence is different from each data in the absolute value sequence. data one-to-one correspondence;

calculating the rank corresponding to each data in the absolute value sequence;

Determine the hypothesis H ₀ of the bilateral test: M=ΔW _0. <=> H ₁ : M≠ΔW ₀ , and calculate the test statistic T=min(T+, T-), where M represents the first difference sequence The actual median of , ΔW _0. represents the calculated median of the first difference sequence, T+ represents the sum of the ranks corresponding to each first data, and the first data is the first difference sequence T-represents the sum of the ranks corresponding to each second data, and the second data is the data in the first difference sequence that is smaller than the median;

The corresponding p value is searched in the normal distribution table according to the calculated test statistic, and whether the median is reasonable is judged according to the p value.

Optionally, the processing module 33 is used for:

If the result of the bilateral test is that the median is reasonable, the planned capacity of the planning area is determined according to the first difference sequence; if the result of the bilateral test is that the median is unreasonable, the The maximum value in the second difference sequence is used as the planned capacity of the planned area.

In the embodiment of the present invention, the first difference sequence and the second difference sequence are obtained by obtaining the first difference sequence and the second difference sequence according to the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power, and the photovoltaic daily power generation TV power in the preset statistical period of the planning area, The planned capacity of the planned area can be determined according to the bilateral test results of the median of the first difference sequence, the first difference sequence and the second difference sequence, and the tested median of the daily net output power can be used to determine the planned capacity of the planned area. Planning capacity, avoiding the problem of higher capacity standards in distribution network transformation caused by capacity planning based on the maximum value of power generation, which can reduce the capacity of distribution network to increase capacity and reduce the transformation of photovoltaic power into distribution network Scale and reduce the implementation cost of connecting photovoltaic power to the distribution network.

FIG. 4 is a schematic diagram of a terminal device provided by an embodiment of the present invention. As shown in FIG. 4 , the terminal device 4 in this embodiment includes: a processor 40 , a memory 41 , and a computer program 42 , such as a program, stored in the memory 41 and executable on the processor 40 . When the processor 40 executes the computer program 42, the steps in each of the foregoing method embodiments are implemented, for example, steps 101 to 103 shown in FIG. 1 . Alternatively, when the processor 40 executes the computer program 42, the functions of the modules/units in each of the foregoing apparatus embodiments, such as the functions of the modules 31 to 33 shown in FIG. 3, are implemented.

Exemplarily, the computer program 42 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 41 and executed by the processor 40 to complete the this invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 42 in the terminal device 4 . For example, the computer program 42 can be divided into an acquisition module, an inspection module and a processing module, and the specific functions of each module are as follows:

The obtaining module is used to obtain the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power and the photovoltaic daily TV power in the preset statistical period of the planning area, and compare the photovoltaic daily power generation active power and the photovoltaic power generation daily power. The first difference sequence is obtained by making a difference in the active power of the daily load, and the second difference sequence is obtained by making the difference between the daily photovoltaic power and the apparent power of the daily load;

a test module, configured to calculate the median of the first difference sequence, and to perform a bilateral test on whether the median is reasonable;

A processing module, configured to determine the planned capacity of the planned area according to the result of the bilateral test, the first difference sequence and the second difference sequence.

The terminal device 4 may be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server. The terminal device may include, but is not limited to, the processor 40 and the memory 41 . Those skilled in the art can understand that FIG. 4 is only an example of the terminal device 4, and does not constitute a limitation on the terminal device 4, and may include more or less components than the one shown, or combine some components, or different components For example, the terminal device may further include an input and output device, a network access device, a bus, a display, and the like.

The so-called processor 40 may be a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 41 may be an internal storage unit of the terminal device 4 , such as a hard disk or a memory of the terminal device 4 . The memory 41 may also be an external storage device of the terminal device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) equipped on the terminal device 4. card, flash card (Flash Card) and so on. Further, the memory 41 may also include both an internal storage unit of the terminal device 4 and an external storage device. The memory 41 is used for storing the computer program and other programs and data required by the terminal device. The memory 41 can also be used to temporarily store data that has been output or will be output.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the present invention.

In the embodiments provided by the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units. Or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, and can also be completed by instructing relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, removable hard disk, magnetic disk, optical disk, computer memory, Read-Only Memory (ROM) , Random Access Memory (Random Access Memory, RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable media may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable media Excluded are electrical carrier signals and telecommunication signals.

The above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it is still possible to implement the foregoing implementations. The technical solutions described in the examples are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the within the protection scope of the present invention.

Claims (8)

1. A distributed photovoltaic power supply access capacity planning method, characterized in that, comprising: Acquire the daily load active power, daily load apparent power, photovoltaic daily power generation active power, and photovoltaic daily TV power within the preset statistical period of the planning area, and use the photovoltaic daily power generation active power and the daily load active power as a value. The first difference sequence is obtained by the difference, and the second difference sequence is obtained by making the difference between the daily photovoltaic power and the daily load apparent power; Calculate the median of the first difference sequence, and perform a bilateral test on whether the median is reasonable; Determine the planned capacity of the planned area according to the result of the bilateral test, the first difference sequence and the second difference sequence; Wherein, the bilateral test on whether the median is reasonable includes: Each data in the first difference sequence is compared with the median to obtain an absolute value to obtain an absolute value sequence; each data in the first difference sequence is different from each data in the absolute value sequence. data one-to-one correspondence; calculating the rank corresponding to each data in the absolute value sequence; Determine the hypothesis H ₀ of the bilateral test: M=ΔW _0. <=> H ₁ : M≠ΔW ₀ , and calculate the test statistic T=min(T+, T-), where M represents the first difference sequence The actual median of , ΔW _0. represents the calculated median of the first difference sequence, T+ represents the sum of the ranks corresponding to each first data, and the first data is the first difference sequence T-represents the sum of the ranks corresponding to each second data, and the second data is the data in the first difference sequence that is smaller than the median; Find the corresponding p value in the normal distribution table according to the calculated test statistic, and judge whether the median is reasonable according to the p value; Wherein, the H ₀ indicates that the calculated median is reasonable, and the H ₁ indicates that the calculated median is unreasonable; Wherein, determining the planning capacity of the planning area according to the result of the bilateral test, the first difference sequence and the second difference sequence includes: If the result of the bilateral test is that the median is reasonable, the planned capacity of the planning area is determined according to the first difference sequence; if the result of the bilateral test is that the median is unreasonable, the The maximum value in the second difference sequence is used as the planned capacity of the planned area. 2 . The method for planning distributed photovoltaic power supply access capacity according to claim 1 , wherein the preset statistical period includes at least one season, and the first difference sequence includes the first difference corresponding to each season. 3 . sequence, the second difference sequence includes the second difference sequence corresponding to each season; The calculating the median of the first difference sequence and performing a bilateral test on whether the median is reasonable includes: Calculate the median of the first difference series corresponding to each season, and conduct a bilateral test to see if the median corresponding to each season is reasonable; The determining the planning capacity of the planning area according to the result of the bilateral test, the first difference sequence and the second difference sequence includes: Determine the planning capacity corresponding to each season according to the results of the bilateral test corresponding to each season, the first difference sequence corresponding to each season, and the second difference sequence corresponding to each season; The maximum value among the planned capacities corresponding to each season is determined as the planned capacity of the planned area. 3 . The method for planning distributed photovoltaic power supply access capacity according to claim 1 , wherein the calculating the median of the first difference sequence comprises: 3 . Sort the first difference value sequence; the first difference value sequence is represented as ΔW ₁ ,...,ΔW _i ,...,ΔW _N , and the sorted first difference value sequence is represented as ΔW ₍₁₎ ,..., ΔW _(j) , . . . , ΔW _(N) ; wherein N is the number of data in the first difference sequence; If N is an odd number, the median of the first difference sequence is ΔW _((N+1)/2) ; If N is an even number, the median of the first difference sequence is 1/2(ΔW _(N/2) +ΔW _((N+2)/2) ). 4. A distributed photovoltaic power supply access capacity planning device, characterized in that, comprising: The obtaining module is used to obtain the daily load active power, the daily load apparent power, the photovoltaic daily power generation active power and the photovoltaic daily TV power in the preset statistical period of the planning area, and compare the photovoltaic daily power generation active power and the photovoltaic power generation daily power. The first difference sequence is obtained by making a difference in the active power of the daily load, and the second difference sequence is obtained by making the difference between the daily photovoltaic power and the apparent power of the daily load; a test module, configured to calculate the median of the first difference sequence, and to perform a bilateral test on whether the median is reasonable; a processing module, configured to determine the planned capacity of the planned area according to the result of the bilateral test, the first difference sequence and the second difference sequence; Wherein, the inspection module is also used for: Each data in the first difference sequence is compared with the median to obtain an absolute value to obtain an absolute value sequence; each data in the first difference sequence is different from each data in the absolute value sequence. data one-to-one correspondence; calculating the rank corresponding to each data in the absolute value sequence; Determine the hypothesis H ₀ of the bilateral test: M=ΔW _0. <=> H ₁ : M≠ΔW ₀ , and calculate the test statistic T=min(T+, T-), where M represents the first difference sequence The actual median of , ΔW _0. represents the calculated median of the first difference sequence, T+ represents the sum of the ranks corresponding to each first data, and the first data is the first difference sequence T-represents the sum of the ranks corresponding to each second data, and the second data is the data in the first difference sequence that is smaller than the median; Find the corresponding p value in the normal distribution table according to the calculated test statistic, and judge whether the median is reasonable according to the p value; Wherein, the H ₀ indicates that the calculated median is reasonable, and the H ₁ indicates that the calculated median is unreasonable; Wherein, the processing module is also used for: If the result of the bilateral test is that the median is reasonable, the planned capacity of the planning area is determined according to the first difference sequence; if the result of the bilateral test is that the median is unreasonable, the The maximum value in the second difference sequence is used as the planned capacity of the planned area. 5 . The distributed photovoltaic power supply access capacity planning device according to claim 4 , wherein the preset statistical period includes at least one season, and the first difference sequence includes the first difference corresponding to each season. 6 . sequence, the second difference sequence includes the second difference sequence corresponding to each season; The inspection module is used for: Calculate the median of the first difference series corresponding to each season, and conduct a bilateral test to see if the median corresponding to each season is reasonable; The processing module is used for: Determine the planning capacity corresponding to each season according to the results of the bilateral test corresponding to each season, the first difference sequence corresponding to each season, and the second difference sequence corresponding to each season; The maximum value among the planned capacities corresponding to each season is determined as the planned capacity of the planned area. 6. The distributed photovoltaic power supply access capacity planning device according to claim 4, wherein the inspection module is used for: Sort the first difference value sequence; the first difference value sequence is represented as ΔW ₁ ,...,ΔW _i ,...,ΔW _N , and the sorted first difference value sequence is represented as ΔW ₍₁₎ ,..., ΔW _(j) , . . . , ΔW _(N) ; wherein N is the number of data in the first difference sequence; If N is an odd number, the median of the first difference sequence is ΔW _((N+1)/2) ; If N is an even number, the median of the first difference sequence is 1/2(ΔW _(N/2) +ΔW _((N+2)/2) ). 7. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the computer program as claimed in the claims when executing the computer program Steps of any one of 1 to 3 of the method. 8. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented .

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