Household electricity loss calculation method and device, storage medium and product

Abstract

The invention provides a household electric quantity loss calculation method and device, a storage medium and a product, belongs to the technical field of power systems, is applied to each household distributed photovoltaic single household, and comprises the following steps: determining a single household of which the electric quantity loss is to be calculated; counting all normal household samples in a preset area to which the single household of which the power loss is to be calculated belongs in the abnormal duration; according to all normal household samples in the preset area, the theoretical generating capacity of a to-be-calculated household in the abnormal duration is calculated, and the to-be-calculated household is a single household of which the power loss is to be calculated; and according to the actual generating capacity and the theoretical generating capacity of the to-be-calculated user in the abnormal duration, obtaining the lost electric quantity of the to-be-calculated user in the abnormal duration. The benchmark generating capacity of the to-be-calculated user is calculated according to the normal user sample in the preset area to which the to-be-calculated user belongs when the to-be-calculated user is abnormal, the lost electric quantity of the to-be-calculated user when the to-be-calculated user is abnormal is obtained by combining the theoretical generating capacity, and the method is simple and high in calculation accuracy.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of power systems, and in particular to a method and device for calculating household power loss, a computer-readable storage medium, and a computer program product. Background Art

[0002] In the existing operation and maintenance process of household distributed photovoltaics, two methods are generally used to calculate the loss of electricity:

[0003] 1) Estimate losses based on PV system capacity and available time

[0004] The annual power generation of the distributed photovoltaic power station is preliminarily estimated by the system capacity and available time. For example, the total capacity of a household photovoltaic system is 40KW, the annual available time is 1800 hours, and the estimated annual power generation is 40KW×1800h=72000KWh. This estimated power generation is the power generation without loss. In actual operation, the power generation of the photovoltaic system will be affected due to the loss of factors such as the inverter. In general, the inverter loss can be calculated to be about 7%, and the loss of other factors is generally about 2%, that is, the total loss rate is 9%. In this way, the annual power generation of the photovoltaic system is: 72000×(1-9%)=65520KWh. The difference between the actual annual power generation and the calculated value is the estimated loss of electricity.

[0005] 2) Calculate the loss by the ratio of actual power generation to theoretical power generation

[0006] The theoretical power generation is calculated through household distributed monitoring data, and the percentage of photovoltaic loss is calculated from the ratio of actual power generation to theoretical power generation. This method is relatively intuitive, but it requires more than one year of actual monitoring data, and has high requirements for the communication stability of the equipment and the accuracy of the algorithm.

[0007] Disadvantages and shortcomings of existing technology:

[0008] The existing technology calculates the power loss of a single household based on the household as the analysis basis. The power loss is calculated based on the household's power station design parameters and operation data, and few other relevant factors are considered, resulting in inaccurate calculation of the power loss of a single household and the inability to classify the power loss, which affects the operation and maintenance analysis and management level, resulting in reduced overall benefits. Summary of the invention

[0009] The purpose of the embodiments of the present disclosure is to provide a method, device, computer-readable storage medium and computer program product for calculating household power loss, so as to solve the above-mentioned problems existing in the prior art.

[0010] In order to achieve the above objectives, the technical solutions adopted by the embodiments of the present disclosure are as follows:

[0011] On the one hand, the embodiments of the present disclosure provide a method for calculating household power loss, which is applied to each household with distributed photovoltaic power generation. The method includes:

[0012] Determine the single household whose power loss is to be calculated;

[0013] Counting all normal household usage samples within a preset area within the duration of the abnormality for the single household whose power loss is to be calculated;

[0014] According to all normal household samples in the preset area, the theoretical power generation of the household to be calculated during the abnormal duration is calculated, and the household to be calculated is the single household whose power loss is to be calculated;

[0015] According to the actual power generation and theoretical power generation of the household with abnormal duration to be calculated, the power loss of the household with abnormal duration to be calculated is obtained.

[0016] Exemplarily, the step of calculating the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0017] When the number of samples of all normal households in the preset area is less than the first preset threshold, the theoretical power generation of the household to be calculated during the abnormal duration is determined according to the meteorological data of the household to be calculated during the abnormal duration and the actual power generation in the historical meteorological data;

[0018] When the number of samples of all normal households in the preset area is greater than or equal to the first preset threshold, the theoretical power generation of the household to be calculated is obtained according to the equivalent utilization hours of non-abnormal operation in the N natural days closest to the abnormal duration of the household to be calculated and the benchmark utilization hours of normal household samples without abnormalities, as well as the benchmark utilization hours of normal household samples within the abnormal duration of the household to be calculated, where 0<N.

[0019] Exemplarily, the step of calculating the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0020] When the number of samples of all normal households in the preset area of ​​the abnormal duration of the household to be calculated is less than a first preset threshold, obtaining meteorological data within the abnormal duration of the household to be calculated, wherein the meteorological data includes: weather phenomena and temperature conditions on the day when the abnormal situation occurs;

[0021] Query the historical meteorological data of the household to be calculated. If there are continuous meteorological events that are the same as the abnormal duration in the historical meteorological data, the actual power generation on the same day and time corresponding to the abnormal duration is used as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated;

[0022] If there is no continuous meteorological data with the same duration as the abnormality in the historical meteorological data, the historical meteorological data of a single day shall be queried separately, and the actual power generation on different dates but at the same time corresponding to the abnormality duration shall be summed up as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated.

[0023] Exemplarily, the step of calculating the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0024] When the number of samples used by all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the first preset threshold and less than the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation when the abnormality occurs is taken, and the equivalent utilization hours of the photovoltaic station without abnormality in the N natural days of the household to be calculated are obtained according to the installed capacity of the household to be calculated, where 0<N;

[0025] Calculate the equivalent utilization hours of the photovoltaic power generation households with no abnormal samples in the same N natural days as the household to be calculated in the preset area, and sort them from high to low. Take the equivalent utilization hours of the first m photovoltaic power generation households on each day, calculate their average value, and obtain the N natural days without abnormal benchmark utilization hours based on the average equivalent utilization hours of N natural days;

[0026] According to the equivalent utilization hours of the power generation households of photovoltaic stations without abnormalities in N natural days and the benchmark utilization hours of the power generation households of photovoltaic power stations, the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value is obtained;

[0027] Calculate the equivalent utilization hours of the photovoltaic stations of all normal samples of the households to be calculated within the duration of the abnormality, sort them from high to low, take the equivalent utilization hours of the first m photovoltaic station power generation households, and get their average value, which is the benchmark utilization hours of the households to be calculated within the duration of the abnormality; combine the installed capacity of the households to be calculated to obtain the benchmark power generation of the households to be calculated;

[0028] According to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated, the theoretical power generation of the household to be calculated is obtained.

[0029] Exemplarily, the step of calculating the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0030] When the number of samples used by all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation when the household to be calculated is taken, and the equivalent utilization hours of the photovoltaic power station of the household to be calculated in the N natural days without abnormal operation are obtained according to the installed capacity of the household to be calculated, where 0<N;

[0031] The box plot method is used to calculate the equivalent utilization hours of the photovoltaic stations with no abnormal samples in the preset area for the same N natural days as the household to be calculated, remove the abnormal data in the sample, take the average of all the data, and obtain the benchmark utilization hours of the photovoltaic stations with no abnormal samples for N natural days based on the average equivalent utilization hours of N natural days;

[0032] According to the equivalent utilization hours of the photovoltaic field station without abnormality in N natural days of the household to be calculated and the benchmark utilization hours of the photovoltaic power station, the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value is obtained;

[0033] Calculate the equivalent utilization hours of the photovoltaic power station of each household in all samples within the duration of the abnormality of the household to be calculated, use the box plot method to exclude abnormal data, and calculate the average value, which is the benchmark utilization hours of the photovoltaic power station of the household to be calculated within the duration of the abnormality; combined with the installed capacity of the household to be calculated, the benchmark power generation of the household to be calculated is obtained;

[0034] According to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated, the theoretical power generation of the household to be calculated is obtained.

[0035] Exemplarily, the box method is used to calculate the equivalent utilization hours of the photovoltaic stations on each of the N natural days without abnormalities in all samples, including:

[0036] Arrange the equivalent utilization hours of the fuchang stations of all samples of N natural days without abnormalities from large to small. The data value at the 1 / 4 position is the upper quartile, the data value at the 1 / 2 position is the median, and the data value at the 3 / 4 position is the lower quartile. The upper limit value is the sum of the values ​​between the upper quartile and 1.5 times the upper quartile and the lower quartile. The lower limit value is the sum of the values ​​between the upper quartile and 1.5 times the upper quartile and the lower quartile.

[0037] Exemplarily, the method for determining the preset area includes:

[0038] The geographical area of ​​the household to which the power loss is to be calculated or the area within the management scope of the operation and maintenance point is determined as the preset area of ​​the statistical sample;

[0039] or,

[0040] The administrative area of ​​the household to be calculated for power loss - district / county, is used as the preset area for statistical samples;

[0041] or,

[0042] The household whose power loss is to be calculated is taken as the dot, and the circle with a preset length as the radius is taken as the preset area of ​​the statistical sample;

[0043] or,

[0044] The household whose power loss is to be calculated is taken as the origin, and the target sample number n, target search step length s, and search radius upper limit R are used. max As a parameter, the search radius is gradually increased according to the step size s to obtain an area that meets the target sample number n as the preset area for statistical samples.

[0045] Exemplarily, the method further includes:

[0046] When a circle with a preset length as the radius is used as the preset area of ​​the statistical sample, in terms of the division of the radius, it supports selecting the preset area according to different combinations of radii and phase angles;

[0047] When the search is gradually increased according to the step size s to obtain an area that meets the target sample number n as a preset area for statistical samples, in terms of parameter setting, it supports selecting the preset area according to the upper limit of the search radius corresponding to different phase angle settings.

[0048] Another aspect of the disclosed embodiment is to provide a household power loss calculation device, which is applied to each household using distributed photovoltaic power. The device includes:

[0049] A determination module, used to determine a single household whose power loss is to be calculated;

[0050] A statistical module, used to count all normal household samples within a preset area within the abnormal duration of the single household whose power loss is to be calculated;

[0051] Theoretical power generation calculation module, used to calculate the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area, the household to be calculated is the single household whose power loss is to be calculated;

[0052] The power loss calculation module is used to obtain the power loss of the household during the abnormal duration to be calculated based on the actual power generation and theoretical power generation of the household during the abnormal duration to be calculated.

[0053] On the other hand, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and the computer program implements the steps of the above-mentioned method when executed by a processor.

[0054] Another aspect of the embodiments of the present disclosure provides a computer program product, including a computer program, which implements the steps of the method described above when executed by a processor.

[0055] The beneficial effects of the embodiments of the present disclosure are:

[0056] The disclosed embodiment has a simple method for calculating household power loss under abnormal circumstances. Combined with the actual situation of distributed operation and maintenance management, a preset area is delineated. According to normal household samples in the preset area, various types of power loss of abnormal household distributed stations are calculated with high accuracy. The abnormal loss during distributed operation can be monitored, and guidance can be provided for relevant decision-making of operation and maintenance management, thereby providing a basis for improving the level of refined management of distributed photovoltaic stations and improving overall benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flowchart of a method for calculating household power loss proposed in an embodiment of the present disclosure;

[0058] Figure 2 This is a schematic diagram of a process flow for calculating and processing household power loss in abnormal situations proposed in an embodiment of the present disclosure;

[0059] Figure 3 It is a structural schematic diagram of counting samples of a preset area according to a radius in a method for calculating household power loss proposed in an embodiment of the present disclosure;

[0060] Figure 4 It is a structural schematic diagram of searching and counting preset area samples according to a target number in a household power loss calculation method proposed in an embodiment of the present disclosure;

[0061] Figure 5 It is a structural schematic diagram of a box-type method of a household power loss calculation method proposed in an embodiment of the present disclosure;

[0062] Figure 6 It is a schematic diagram of the structure of a household power loss calculation device proposed in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiment of the present disclosure more clear, the embodiment of the present disclosure is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation methods described here are only used to explain the embodiment of the present disclosure and are not used to limit the embodiment of the present disclosure.

[0064] In view of the difficulty in calculating the power loss when household distributed sites are in abnormal conditions, the low accuracy and the inability to classify the loss types, the loss types are divided by manually selecting types through association with the abnormal processing of the household distributed photovoltaic site; and through different area division methods, the benchmark power generation reference value of the area is calculated as the basis for calculating the actual household power loss; therefore, the embodiment of the present disclosure proposes a method for calculating the power loss of a single household in household distributed photovoltaic operation and maintenance, including: a method for dividing the type of power loss of a single household and a method for calculating the loss value.

[0065] like Figure 1 As shown, the embodiment of the present disclosure proposes a method for calculating household power loss, which is applied to each household using distributed photovoltaic power. The method includes:

[0066] Step S10: Determine a single household whose power loss is to be calculated.

[0067] According to actual needs, photovoltaic equipment is installed for multiple households in a certain area to form a distributed photovoltaic station in the area. Each household generates electricity and uploads it to the grid. Each household has an inverter device. According to the alarm signal generated by the inverter of any household in the distributed photovoltaic station, it indicates that the household has an abnormal situation and abnormal power generation, and the household is determined to be a single household whose power loss is to be calculated. At present, the data collection method for household distributed photovoltaics generally uses a collection rod to collect data from the inverter, and the group's calculation of power loss is generally based on the existence of fault operation or abnormal shutdown, and the loss caused by inefficient operation without abnormality is not considered for the time being. Therefore, when there is power loss, in most cases, there will be related abnormal alarms on the inverter side, such as power limit loss, and the inverter side alarm is no grid. Combined with the processing of on-site reported problems, after comprehensive analysis, it is only necessary to manually intervene in the classification of abnormalities during abnormal processing to achieve the classification of the types of power loss.

[0068] The specific process of calculating and processing the power loss in abnormal household operation is as follows: Figure 2 As shown, "inverter alarm" refers to the alarm signal generated by the inverter of a household in the household distributed photovoltaic station. "On-site problem reporting" refers to the relevant reporting made by the on-site operation and maintenance personnel or the household distributed household owner after discovering the on-site problem. "Abnormal confirmation" refers to the operation and maintenance management personnel continuing to classify and confirm the abnormality according to the actual alarm content or report content. "Abnormal duration" refers to the duration from the occurrence to the elimination of the abnormality. "Benchmark power generation within the duration" refers to the corresponding benchmark power generation within the duration period of the abnormality. "Theoretical power generation within the duration" refers to the theoretical power generation of the household distributed converted by the benchmark power generation within the duration period of the abnormality. "Loss of electricity within the duration" refers to the loss of electricity calculated by the household within the duration period of the abnormality.

[0069] In "Abnormal Confirmation", abnormalities can be mapped to the following types of power loss:

[0070] Fault loss: The loss of power generation caused by the failure of related equipment that directly or indirectly affects power generation is classified as fault loss.

[0071] Power curtailment loss: Due to power curtailment by the power grid, the generated electricity cannot be connected to the grid, resulting in power generation loss.

[0072] Planned loss: The loss of power generation caused by the inability to generate power normally during planned maintenance.

[0073] Losses incurred: Losses incurred mainly include grid-related losses and dispute-related losses. Grid-related losses refer to the power generation losses caused by grid failure, which results in the inability of the generated electricity to be connected to the grid normally; dispute-related losses refer to the power generation losses caused by disputes with household distributed electricity users, who manually turn off the export power switch, resulting in the inability of the generated electricity to be connected to the grid.

[0074] Identifying the type of power loss helps with power plant operation and maintenance analysis, statistics, and maintenance.

[0075] Among them, under abnormal circumstances, the calculation method of the single-household benchmark power generation, theoretical power generation and lost power to be calculated are introduced in detail below. The calculation of the single-household benchmark power generation for the lost power to be calculated mainly includes two parts: calculation sample selection and benchmark value calculation.

[0076] Step S20: Count all normal household usage samples within the preset area within the abnormal duration of the single household whose power loss is to be calculated.

[0077] The distributed power system of a single household whose power loss is to be calculated is referred to as the household to be calculated as the base point. Sample statistics are performed according to different methods. All samples must exclude abnormal households. That is, during the abnormal period of the household to be calculated, there are also abnormal household distributed power systems, such as inverter alarms, equipment offline, etc. The statistical methods for normal household samples include:

[0078] Counting all normal household samples within a preset area to which a single household whose power loss is to be calculated belongs during the abnormal duration, the method for determining the preset area includes:

[0079] a. Manually divide the sample area, select the household distributed power to be calculated, and according to actual needs, such as by geographical area, operation and maintenance point management scope, or manual division; the household distributed power is grouped into a sample calculation area. In other words, the distributed power of the household in the geographical area or the operation and maintenance point management scope of the household whose power loss is to be calculated is grouped into a sample calculation area. The geographical area or operation and maintenance point management area to which the household to be calculated belongs is the preset area.

[0080] If the household to be calculated has been manually divided into a sample calculation area, the sample area will be calculated using the sample area as the benchmark value for the household to be calculated.

[0081] b. Statistical samples are collected by district / county, with the administrative area - district / county to which the single household whose power loss is to be calculated belongs as the preset area for statistical samples; that is, the administrative area - district / county is used as the sample selection area, and other households in the same county as the household to be calculated are used as a sample.

[0082] c. Statistical samples are collected by area radius, with the household whose power loss is to be calculated as the dot and the circle with the preset length as the radius as the preset area for statistical samples; Figure 3 As shown in (a), the household to be calculated is used as the regional point, and the household distribution within the circle of the preset radius is selected as the calculation sample. In order to reduce the impact of PV power generation caused by meteorological differences and ensure the accuracy of sample calculation, it is recommended that the preset radius be selected not more than 50km. The preset radius can be 20km, 40km, etc. At the same time, for some areas with special terrain, the radius division supports the selection of sample areas according to different combinations of radius and phase angle. Figure 3 As shown in (b), in the north direction, the clockwise phase angle is 90° and the radius is 20km; in the west direction, the counterclockwise phase angle is 45° and the radius is 50km.

[0083] d. Search for statistical samples according to the target number, take the household to be calculated as the regional origin, set the target sample number n, target search step s, and search radius upper limit R max That is to say, the single household whose power loss is to be calculated is taken as the origin, the target sample number n, the target search step length s, and the search radius upper limit R max As a parameter, the search radius is gradually increased according to the step size s to obtain an area that meets the target sample number n as the preset area for statistical samples.

[0084] For example, set the target sample number n = 500, the target search step s = 2, and the search radius upper limit R max =50. Search results such as Figure 4 As shown in the figure, when the search radius r reaches 18km, the number of samples n is 480, which does not reach the target number. After the search radius is increased to r=20 by step s, the number of samples n is 511. It is considered that when r=20, the number of samples reaches the set requirement, and n=511 at this time.

[0085] If the search radius has reached the set radius upper limit R max , and the number of samples searched does not reach the target number of samples n, the actual number of samples searched is used as the number of samples.

[0086] Similar to the statistical method based on regional radius, this method also supports setting the upper limit of the search radius corresponding to different phase angles.

[0087] That is to say, when a circle with a preset length as a radius is used as a preset area for statistical samples, in terms of the division of the radius, it is supported to select the preset area according to different combinations of radii and phase angles.

[0088] or,

[0089] When the search is gradually increased according to the step size s to obtain an area that meets the target sample number n as a preset area for statistical samples, in terms of parameter setting, it supports selecting the preset area according to the upper limit of the search radius corresponding to different phase angle settings.

[0090] Here, the area with a relatively close and concentrated distance within the preset area can be divided into a sub-area. A sub-area can have the same number or different numbers of households, and each sub-area can be set according to actual conditions. Each household in the sub-area may have similar equivalent utilization hours. The sub-area is, for example, a village, town, etc. The sub-area has similar equivalent utilization hours, that is, there can be multiple sub-areas in the preset area. Based on the selection of the preset areas a to d above, the regional average equivalent utilization hours of the sub-area where the household to be calculated is located in the preset time period, that is, the first value, and the regional average equivalent utilization hours of the preset time period of the remaining sub-areas in the preset area, that is, the second value, are calculated. The average equivalent utilization hours can be obtained by summarizing the equivalent utilization hours of each household in each sub-area during the preset time and taking the average value; the difference between the first value of the sub-area where the household to be calculated is located and the second value of the remaining sub-areas is calculated respectively, and the sub-area with a difference less than the threshold is used as a candidate area, and the normal households in each candidate area are used as the final samples in the preset area. According to the difference and the threshold, the candidate area is determined from the remaining sub-areas in the preset area, that is, the sub-areas whose difference or the absolute value of the difference is less than the threshold are used as candidate areas. The preset time period can be set according to actual conditions.

[0091] Furthermore, the threshold can be adjusted according to the distance between the current sub-region where the household to be calculated is located and the remaining target sub-regions. As the distance between the current sub-region of the household to be calculated and the target sub-region increases, the threshold can be reduced. That is, for target sub-regions close to the current sub-region of the household to be calculated, a large threshold is used when selecting candidate regions, and for target sub-regions far from the current sub-region of the household to be calculated, a small threshold is used when selecting candidate regions.

[0092] The historical data of power loss can be obtained by the method of the embodiment of the present disclosure or by other methods. The purpose of sample selection is to eliminate the influence of some external factors on power generation, such as local meteorological and topographical conditions. For example, some are in mountainous areas and some are in plains, and the sunshine duration and radiation will be quite different, and the corresponding power generation will also be quite different. The purpose of the search is to ensure that the selected samples are similar to the external conditions of the outdoor to be calculated as much as possible.

[0093] Step S30, calculating the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area, where the household to be calculated is the single household whose power loss is to be calculated.

[0094] Specifically, according to the different number ranges of samples of all normal households in the preset area of ​​abnormal duration of the household to be calculated, the benchmark power generation is calculated using the corresponding pre-set methods. The specific calculation method of the benchmark value and theoretical power generation is as follows:

[0095] In the embodiment of the present disclosure, two methods are mainly listed to calculate the theoretical power generation of the household to be calculated during the abnormal duration according to the number of samples. The method calculates the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area, including:

[0096] When the number of samples of all normal households in the preset area is less than the first preset threshold, the theoretical power generation of the household to be calculated during the abnormal duration is determined according to the meteorological data of the household to be calculated during the abnormal duration and the actual power generation in the historical meteorological data.

[0097] At this time, the number of samples used for normal households is small and they are not used as benchmark samples for calculating the households to be calculated.

[0098] When the number of samples of all normal households in the preset area is greater than or equal to the first preset threshold, the theoretical power generation of the household to be calculated is obtained according to the equivalent utilization hours of non-abnormal operation in the N natural days closest to the abnormal duration of the household to be calculated and the normal household sample non-abnormal benchmark utilization hours, and the benchmark utilization hours of the normal household sample within the abnormal duration of the household to be calculated, where N is set according to the actual situation, 15<N<35. The first preset threshold can be set according to the actual situation, and the range of the first preset threshold can be 15~30.

[0099] The calculation of the benchmark value mainly depends on the actual number of samples and different calculation methods are selected.

[0100] As an example, the calculation of the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0101] Step S311: when the number of samples of all normal households in the preset area for the abnormal duration of the household to be calculated reaches the first preset threshold, obtain the meteorological data within the abnormal duration of the single household whose power loss is to be calculated.

[0102] Among them, the first preset threshold value can be 20, that is, when the number of samples used by normal households is greater than or equal to 0 and less than 20, the meteorological data within the abnormal duration of the single household whose power loss is to be calculated is obtained. The meteorological data includes: weather phenomena and temperature conditions. Specifically, weather phenomena include: sunny, haze, cloudy, light rain, moderate rain, heavy rain, light snow, moderate snow, heavy snow, sleet, etc. The temperature condition is the minimum temperature and maximum temperature of the abnormal situation of the household to be calculated on the day.

[0103] Step S312, query the historical meteorological data of the household to be calculated. If there are continuous meteorological events with the same duration as the abnormality in the historical meteorological data, the normal actual power generation on the same day and time with the same meteorological event corresponding to the abnormality duration will be used as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated.

[0104] The same weather phenomenon and temperature conditions within the corresponding preset range are regarded as the same meteorological data; that is, they meet the following conditions at the same time: the weather conditions are the same, such as sunny, cloudy, light rain, etc., and the absolute value of the minimum temperature difference and the absolute value of the maximum temperature difference of the same weather phenomenon on the day of the abnormal duration do not exceed the preset threshold value and are regarded as the same temperature conditions. Specifically, the minimum temperature difference does not exceed ±5, and the maximum temperature difference does not exceed ±5.

[0105] Step S313: If there is no continuous meteorological data with the same duration as the abnormality in the historical meteorological data, query the historical meteorological data of a single day respectively, and calculate the sum of the normal actual power generation on different dates but the same time corresponding to the abnormality duration as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated.

[0106] The details are as follows: when the number of samples of all normal households in the preset area of ​​the abnormal duration of the household to be calculated is small, and the sample number range is 0≤n<20, at this time, there is no other reference power station in the preset area, and the historical operation data of the household to be calculated is used for evaluation to obtain the meteorological data within the duration of the abnormality (in days). For example: the abnormal duration of the household to be calculated is from 10:10:24 on October 5 to 19:01:35 on October 6, then the meteorological data of October 5 and October 6 are taken, and similar meteorological conditions are queried from the historical data based on the principle of proximity.

[0107] When similar weather conditions that meet the requirements appear and there is no abnormality in the corresponding household, the actual power generation from 10:10:24 on the first day to 19:01:35 on the second day will be used as the benchmark power generation.

[0108] If no continuous meteorological data is found, the meteorological data for each day will be queried separately, and then the power generation on consecutive dates with no similar meteorological conditions will be calculated separately, such as the power generation from 10:10:20 to 23:59:59 on the fifth day and from 00:00:00 to 19:01:35 on the seventh day, and then the two will be added together as the benchmark power generation.

[0109] The benchmark value calculated by this method can be used as the theoretical power generation of the household to be calculated.

[0110] As an example, the calculation of the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0111] Step S321: When the number of samples of all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the first preset threshold and less than the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation is taken, and the equivalent utilization hours of the household to be calculated in the N natural days without abnormal operation are obtained according to the installed capacity of the household to be calculated, where 15<N<35. The first preset threshold and the second preset threshold can be set according to actual conditions, and can be 20 and 100 respectively.

[0112] Step S322, respectively calculate the equivalent utilization hours of the distributed photovoltaic station power generation households with no abnormal samples in the same N natural days as the household to be calculated in the preset area, and sort them from high to low, take the equivalent utilization hours of the first m photovoltaic station power generation households each day, calculate their average value, and obtain the benchmark utilization hours of photovoltaic power stations without abnormalities in N natural days based on the average equivalent utilization hours of N natural days.

[0113] At this time, the abnormal samples that appear every day in N natural days can be excluded, and the remaining samples are normal samples no matter which day they are.

[0114] Step S323, obtain the coefficient k for converting the benchmark value of the household to be calculated into the theoretical value based on the equivalent utilization hours of the household to be calculated and the sample N natural days without abnormal photovoltaic field station power generation households and the benchmark utilization hours of photovoltaic power station power generation households.

[0115] Step S324: Calculate the equivalent utilization hours of the photovoltaic stations of all normal samples within the duration of the abnormality of the household to be calculated, sort them from high to low, take the equivalent utilization hours of the first m photovoltaic stations, and obtain their average value, which is the benchmark utilization hours of the household to be calculated within the duration of the abnormality; combine the installed capacity of the household to be calculated to obtain the benchmark power generation of the household to be calculated. m is greater than 0, and m can be set according to actual conditions.

[0116] Step S325, obtaining the theoretical power generation of the household to be calculated according to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated.

[0117] The details are as follows: when the sample size is medium, the sample size range is 20≤n<100; the value range of N can be 15~35, specifically 30.

[0118] Step 1: Get the power generation of the household to be calculated in the past 30 natural days without abnormal operation. The dates can be discontinuous, and record the corresponding date data. 1－30 , after summing, divide it by the installed capacity of the household to be calculated, and calculate the equivalent utilization hours of the photovoltaic station without abnormalities in the past 30 days for the household to be calculated;

[0119] The equivalent utilization hours of the household to be calculated without abnormal photovoltaic power generation in the past 30 days = (Σ(data 1－30 Daily normal power generation)) / installed capacity of the household.

[0120] Step 2: Calculate data separately 1－30 The equivalent utilization hours of distributed photovoltaic stations in the non-abnormal sample of each day are taken, and the equivalent utilization hours of the power generation households in the first m photovoltaic stations of each day are averaged, and then the average value of 30 days is added to obtain the non-abnormal benchmark utilization hours, which is used as the non-abnormal benchmark utilization hours of the households to be calculated: 1－30 The samples without abnormalities every day serve as the non-abnormal samples in the second step.

[0121] The number of hours of use without abnormal benchmark in the past 30 days = Σ(data 1－30 The average value of equivalent utilization hours of power generation households in the first m photovoltaic stations per day).

[0122] Step 3: Calculate the coefficient k of the theoretical value of the benchmark value of the household to be calculated;

[0123] Conversion factor k = equivalent utilization hours of power generation users at photovoltaic stations without abnormalities in the past 30 days / benchmark utilization hours without abnormalities in the past 30 days.

[0124] Step 4: Calculate the equivalent utilization hours of the photovoltaic power generation households in the sample within the duration of the abnormality of the household to be calculated. For example, if the duration of the abnormality is from 10:10:24 on October 5 to 19:01:35 on October 6, then for each household in the sample, take the power generation in this period, and then divide it by the installed capacity of the household. The calculated value is the equivalent utilization hours of the photovoltaic power generation households in the duration of the abnormality of the household to be calculated, and then take the average of the equivalent utilization hours of the photovoltaic power generation households before m. This value is the benchmark utilization hours of the household to be calculated within the duration of the abnormality. The value range of M can be 8 to 12, and specifically 10.

[0125] Benchmark power generation of the household to be calculated = benchmark utilization hours × installed capacity of the household to be calculated (single household);

[0126] Step 5: Calculate the theoretical power generation of the household to be calculated;

[0127] Theoretical power generation of the household to be calculated = conversion factor k × benchmark power generation of the household to be calculated.

[0128] As an example, the calculation of the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area includes:

[0129] Step S331, when the number of samples used by all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation when the abnormality occurs is obtained, and according to the installed capacity of the household to be calculated, the equivalent utilization hours of the photovoltaic power station of the household to be calculated in the N natural days without abnormality is obtained, wherein N can be set according to the actual situation, 15<N<35.

[0130] Step S332: Use the box plot method to calculate the equivalent utilization hours of the photovoltaic station for the same N natural days as the household to be calculated in the preset area, remove the abnormal data in the sample, take the average of all the data, and obtain the benchmark utilization hours of the photovoltaic station without abnormalities in N natural days based on the average equivalent utilization hours of N natural days.

[0131] Step S333, obtaining a coefficient k for converting the benchmark value of the household to be calculated into a theoretical value based on the equivalent utilization hours of the photovoltaic field station without abnormalities in N natural days of the household to be calculated and the benchmark utilization hours of the photovoltaic power station.

[0132] Step S334, calculate the equivalent utilization hours of the photovoltaic power station of each household in all samples within the duration of the abnormality of the household to be calculated, use the box plot method to exclude abnormal data, and calculate the average value, which is the benchmark utilization hours of the photovoltaic power station of the household to be calculated within the duration of the abnormality; combined with the installed capacity of the household to be calculated, the benchmark power generation of the household to be calculated is obtained;

[0133] Step S335, obtaining the theoretical power generation of the household to be calculated according to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated.

[0134] The details are as follows: when the sample size is sufficient, the sample size range is n ≥ 100;

[0135] Step 1: Get the power generation of the household to be calculated in the past 30 natural days without abnormal operation. The dates can be discontinuous, and record the corresponding date data. 1－30 , and then divide it by the installed capacity of the household to be calculated to calculate the equivalent utilization hours of the photovoltaic station without abnormalities in the past 30 days for the household to be calculated:

[0136] The equivalent utilization hours of the household to be calculated without abnormal photovoltaic power generation in the past 30 days = (Σ(data 1－30 Daily normal power generation)) / installed capacity;

[0137] Step 2: Calculate data separately 1－30 The equivalent utilization hours of distributed photovoltaic power generation users in the sample for each day are calculated using the box plot method.

[0138] like Figure 5 As shown, the upper quartile Q75%: the data is arranged from large to small, and the data value is located at the 1 / 4 position. The median: the data is arranged from large to small, and the data value is located at the 1 / 2 position. The lower quartile Q25%: the data is arranged from large to small, and the data value is located at the 3 / 4 position. IQR: Q75%-Q25% value. Upper limit value = Q75% + 1.5xIQR. Lower limit value = Q25%-1.5xIQR. The value greater than the upper limit and less than the lower limit is a discrete point and needs to be removed.

[0139] Remove abnormal data (discrete points) in the sample, that is, remove daily abnormal data, then take the average of all data to obtain the average equivalent utilization hours of the daily sample PV station in the natural day, and then take the average value of 30 days respectively and add them up to obtain the sample normal benchmark utilization hours.

[0140] The number of hours of use without abnormal benchmarks in the past 30 days = Σ (data1-30, the average number of hours of use for each household after removing abnormal data points every day)

[0141] Step 3: Calculate the coefficient k of the theoretical value of the benchmark value of the household to be calculated:

[0142] Conversion coefficient k = equivalent utilization hours of the photovoltaic station without abnormality in the past 30 days for the household to be calculated / benchmark utilization hours without abnormality in the past 30 days for the sample

[0143] Step 4: Calculate the equivalent utilization hours of the photovoltaic power generation households in the sample within the duration of the abnormality of the household to be calculated. For example, if the duration of the abnormality is from 10:10:24 on October 5 to 19:01:35 on October 6, then for each household in the sample, take the power generation in this period, and then divide it by the installed capacity of the household. The calculated value is the equivalent utilization hours of the photovoltaic power generation households in the duration of the abnormality of the household to be calculated. Then, the average value is taken after excluding abnormal data (discrete points) through the box plot method. This value is the benchmark utilization hours of the household to be calculated within the duration of the abnormality.

[0144] Benchmark power generation of the household to be calculated = benchmark utilization hours × installed capacity of the household to be calculated

[0145] Step 5: Calculate the theoretical power generation of the household to be calculated

[0146] Theoretical power generation of the household to be calculated = conversion factor k × benchmark power generation of the household to be calculated

[0147] Step S40, obtaining the power loss of the household during the abnormal duration to be calculated according to the actual power generation of the household during the abnormal duration to be calculated and the theoretical power generation.

[0148] The power loss of the household to be calculated during the duration of the abnormality is the theoretical power generation of the household to be calculated during this period minus the actual power generation of the household to be calculated during this period, as follows:

[0149] The lost power generation of the household to be calculated = the theoretical power generation of the household to be calculated - the actual power generation of the household to be calculated.

[0150] In the embodiment of the present disclosure, for each household distributed photovoltaic power supply, when dividing the sample area, you can choose to manually configure the area, automatically divide by the district / county, divide by the search radius, and search and divide by the sample target number to configure the reference sample area when calculating the loss of electricity. Searching by search radius and by sample target number supports batch operations for multiple household distributed systems. Then, when an abnormality occurs in a household in the household distributed system, the system will automatically calculate the relevant loss of electricity based on the actual number of sample areas to which it belongs.

[0151] like Figure 6 As shown, another aspect of the embodiment of the present disclosure provides a household power loss calculation device, which is applied to each household using distributed photovoltaic power, and the device includes:

[0152] The determination module 10 is used to determine a single household whose power loss is to be calculated.

[0153] The statistical module 20 is used to count all normal household usage samples in a preset area within the abnormal duration of the single household whose power loss is to be calculated.

[0154] The theoretical power generation calculation module 30 is used to calculate the theoretical power generation of the household to be calculated during the abnormal duration based on all normal household samples in the preset area. The household to be calculated is a single household whose power loss is to be calculated.

[0155] The power loss calculation module 40 is used to obtain the power loss of the household during the abnormal duration to be calculated based on the actual power generation and theoretical power generation of the household during the abnormal duration to be calculated.

[0156] Compared with the prior art, the household electricity loss calculation method of the disclosed embodiment is based on the actual situation of distributed operation and maintenance management, and designs an algorithm by itself. Through multiple methods, it calculates various types of electricity loss of abnormal household distributed stations, realizes the monitoring of abnormal losses during distributed operation, and provides guidance for relevant decisions of operation and maintenance management, thereby improving the level of refined management of distributed photovoltaic stations and improving overall benefits.

[0157] Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-mentioned method when executed by a processor.

[0158] Another aspect of the embodiments of the present disclosure provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0159] The above is only a preferred implementation of the embodiment of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the embodiment of the present disclosure. These improvements and modifications should also be considered as the protection scope of the embodiment of the present disclosure.

Claims

1. A method for calculating household power loss, applied to each household with distributed photovoltaic power generation, characterized in that: The method comprises: Determine the single household whose power loss is to be calculated; Counting all normal household usage samples within a preset area within the duration of the abnormality for the single household whose power loss is to be calculated; According to all normal household samples in the preset area, the theoretical power generation of the household to be calculated during the abnormal duration is calculated, and the household to be calculated is the single household whose power loss is to be calculated; According to the actual power generation and theoretical power generation of the household with abnormal duration to be calculated, the power loss of the household with abnormal duration to be calculated is obtained.

2. The method according to claim 1, characterized in that The calculation of the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area includes: When the number of samples of all normal households in the preset area is less than the first preset threshold, the theoretical power generation of the household to be calculated during the abnormal duration is determined according to the meteorological data of the household to be calculated during the abnormal duration and the actual power generation in the historical meteorological data; When the number of samples of all normal households in the preset area is greater than or equal to the first preset threshold, the theoretical power generation of the household to be calculated is obtained according to the equivalent utilization hours of non-abnormal operation in the N natural days closest to the abnormal duration of the household to be calculated and the benchmark utilization hours of normal household samples without abnormalities, as well as the benchmark utilization hours of normal household samples within the abnormal duration of the household to be calculated, where 0<N.

3. The method according to claim 1 or 2, characterized in that: The calculation of the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area includes: When the number of samples of all normal households in the preset area of ​​the abnormal duration of the household to be calculated is less than a first preset threshold, obtaining meteorological data within the abnormal duration of the household to be calculated, wherein the meteorological data includes: weather phenomena and temperature conditions on the day when the abnormal situation occurs; Query the historical meteorological data of the household to be calculated. If there are continuous meteorological events that are the same as the abnormal duration in the historical meteorological data, the actual power generation on the same day and time corresponding to the abnormal duration is used as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated; If there is no continuous meteorological data with the same duration as the abnormality in the historical meteorological data, the historical meteorological data of a single day shall be queried separately, and the actual power generation on different dates but at the same time corresponding to the abnormality duration shall be summed up as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated.

4. The method according to claim 1 or 2, characterized in that: The calculation of the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area includes: When the number of samples used by all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the first preset threshold and less than the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation when the abnormality occurs is taken, and the equivalent utilization hours of the photovoltaic station without abnormality in the N natural days of the household to be calculated are obtained according to the installed capacity of the household to be calculated, where 0<N; Calculate the equivalent utilization hours of the photovoltaic power generation households with no abnormal samples in the same N natural days as the household to be calculated in the preset area, and sort them from high to low. Take the equivalent utilization hours of the first m photovoltaic power generation households on each day, calculate their average value, and obtain the N natural days without abnormal benchmark utilization hours based on the average equivalent utilization hours of N natural days; According to the equivalent utilization hours of the power generation households of photovoltaic stations without abnormalities in N natural days and the benchmark utilization hours of the power generation households of photovoltaic power stations, the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value is obtained; Calculate the equivalent utilization hours of the photovoltaic stations of all normal samples of the households to be calculated within the duration of the abnormality, sort them from high to low, take the equivalent utilization hours of the first m photovoltaic station power generation households, and get their average value, which is the benchmark utilization hours of the households to be calculated within the duration of the abnormality; combine the installed capacity of the households to be calculated to obtain the benchmark power generation of the households to be calculated; According to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated, the theoretical power generation of the household to be calculated is obtained.

5. The method according to claim 1 or 2, characterized in that: The calculation of the theoretical power generation of the household to be calculated during the abnormal duration according to all normal household samples in the preset area includes: When the number of samples used by all normal households in the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to the second preset threshold, the daily power generation of the household to be calculated in the N natural days without abnormal operation when the household to be calculated is taken, and the equivalent utilization hours of the photovoltaic power station of the household to be calculated in the N natural days without abnormal operation are obtained according to the installed capacity of the household to be calculated, where 0<N; The box plot method is used to calculate the equivalent utilization hours of the photovoltaic stations with no abnormal samples in the preset area for the same N natural days as the household to be calculated, remove the abnormal data in the sample, take the average of all the data, and obtain the benchmark utilization hours of the photovoltaic stations with no abnormal samples for N natural days based on the average equivalent utilization hours of N natural days; According to the equivalent utilization hours of the photovoltaic field station without abnormality in N natural days of the household to be calculated and the benchmark utilization hours of the photovoltaic power station, the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value is obtained; Calculate the equivalent utilization hours of the photovoltaic power station of each household in all samples within the duration of the abnormality of the household to be calculated, use the box plot method to exclude abnormal data, and calculate the average value, which is the benchmark utilization hours of the photovoltaic power station of the household to be calculated within the duration of the abnormality; combined with the installed capacity of the household to be calculated, the benchmark power generation of the household to be calculated is obtained; According to the coefficient k of converting the benchmark value of the household to be calculated into the theoretical value and the benchmark power generation of the household to be calculated, the theoretical power generation of the household to be calculated is obtained.

6. The method according to any one of claims 1 to 5, characterized in that: The method for determining the preset area includes: The geographical area of ​​the household to which the power loss is to be calculated or the area within the management scope of the operation and maintenance point is determined as the preset area of ​​the statistical sample; or, The administrative area of ​​the household to be calculated for power loss - district / county, is used as the preset area for statistical samples; or, The household whose power loss is to be calculated is taken as the dot, and the circle with a preset length as the radius is taken as the preset area of ​​the statistical sample; or, The household whose power loss is to be calculated is taken as the origin, and the target sample number n, target search step length s, and search radius upper limit R are used. max As a parameter, the search radius is gradually increased according to the step size s to obtain an area that meets the target sample number n as the preset area for statistical samples.

7. The method according to claim 6, characterized in that The method further comprises: When a circle with a preset length as the radius is used as the preset area of ​​the statistical sample, in terms of the division of the radius, it supports selecting the preset area according to different combinations of radii and phase angles; When the search is gradually increased according to the step size s to obtain an area that meets the target sample number n as a preset area for statistical samples, in terms of parameter setting, it supports selecting the preset area according to the upper limit of the search radius corresponding to different phase angle settings.

8. A household power loss calculation device, applied to each household using distributed photovoltaic power, characterized in that: The device comprises: A determination module, used to determine a single household whose power loss is to be calculated; A statistical module, used to count all normal household samples within a preset area within the abnormal duration of the single household whose power loss is to be calculated; Theoretical power generation calculation module, used to calculate the theoretical power generation of the household to be calculated within the abnormal duration according to all normal household samples in the preset area, the household to be calculated is the single household whose power loss is to be calculated; The power loss calculation module is used to obtain the power loss of the household during the abnormal duration to be calculated based on the actual power generation and theoretical power generation of the household during the abnormal duration to be calculated.

9. A computer-readable storage medium having a computer program stored thereon, 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 7 are implemented.

10. A computer program product, comprising 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 7 are implemented.

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