A household power loss calculation method, device, storage medium and product

Abstract

The present invention proposes a method, device, storage medium and product for calculating household power loss, which belongs to the field of power system technology and is applied to each household with distributed photovoltaic power. The method includes: determining a household whose power loss is to be calculated; counting all normal household samples within a preset area to which the household whose power loss is to be calculated belongs during the abnormal duration; calculating the theoretical power generation of the household to be calculated during the abnormal duration based on all normal household samples within the preset area, where the household to be calculated is the household whose power loss is to be calculated; obtaining the power loss of the household to be calculated during the abnormal duration based on the actual power generation and theoretical power generation of the household to be calculated during the abnormal duration. The present invention calculates the benchmark power generation of the household to be calculated based on the normal household samples within the preset area to which the household to be calculated belongs when the abnormality occurs, and combines this with the theoretical power generation to obtain the power loss of the household to be calculated during the abnormal duration. The method is simple and has high calculation accuracy.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of power systems, and more particularly 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 photovoltaic systems, two methods are generally used to calculate the power loss:

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

[0004] A preliminary estimate of the annual power generation of a distributed photovoltaic power station can be made based on the system capacity and availability. For example, if a household photovoltaic system has a total capacity of 40 kW and an annual availability of 1,800 hours, the estimated annual power generation is 40 kW x 1,800 hours = 72,000 kWh. This estimated power generation assumes no losses. In actual operation, losses from factors such as the inverter will affect the power generation of the photovoltaic system. Generally, inverter losses can be calculated to be around 7%, and losses from other factors are generally around 2%, resulting in a total loss rate of 9%. Therefore, the estimated annual power generation of the photovoltaic system is: 72,000 x (1 - 9%) = 65,520 kWh. The difference between the final actual annual power generation and this calculated value is the estimated power loss.

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

[0006] Calculate theoretical power generation using household distributed monitoring data, then use the ratio of actual to theoretical power generation to calculate the percentage of PV losses. This method is relatively straightforward, but requires more than a year of actual monitoring data, high communication stability for the equipment, and high algorithm accuracy.

[0007] Disadvantages and shortcomings of existing technologies:

[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 operating data, and few other relevant factors are considered. As a result, the calculation of the power loss of a single household is inaccurate and the power loss cannot be classified, 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, thereby solving the aforementioned problems existing in the prior art.

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

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

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

[0013] Counting all normal household usage samples within a preset area within which the single household whose power loss is to be calculated belongs during the abnormal duration;

[0014] Based on all normal household samples in the preset area, calculate the theoretical power generation of the household to be calculated during the abnormal duration. 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 during the abnormal duration based on all normal household usage 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 based on 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 based on 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 during the abnormal duration based on all normal household usage 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 during 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 consecutive weather conditions 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 will be queried separately, and the actual power generation on different dates but the same time corresponding to the abnormality duration will be calculated and 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 during the abnormal duration based on all normal household usage samples in the preset area includes:

[0024] When the number of samples of all normal households within 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 obtained, and the equivalent utilization hours of the photovoltaic station without abnormality for the household to be calculated in the N natural days are obtained based on 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 on the same N natural days in the preset area, 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, and obtain the benchmark utilization hours without abnormalities on N natural days based on the average equivalent utilization hours of N natural days;

[0026] The coefficient k for converting the benchmark value of the household to be calculated into the theoretical value is obtained based on the equivalent utilization hours of the household to be calculated in N natural days without abnormal photovoltaic station power generation and the benchmark utilization hours of the photovoltaic power station power generation household;

[0027] Calculate the equivalent utilization hours of the PV stations of all normal samples of households 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 PV station power generation households, and obtain their average value, which is the benchmark utilization hours of the household to be calculated within the duration of the abnormality; combine it with the installed capacity of the household to be calculated to obtain the benchmark power generation of the household 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 during the abnormal duration based on all normal household usage samples in the preset area includes:

[0030] When the number of samples of all normal households within 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 the equivalent utilization hours of the photovoltaic power station of the household to be calculated in the N natural days without abnormality are obtained based on the installed capacity of the household to be calculated, where 0<N;

[0031] Use the box plot method to calculate the equivalent utilization hours of the PV stations with no abnormalities in the N natural days of the same household 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 PV stations with no abnormalities in the N natural days based on the average equivalent utilization hours of the N natural days.

[0032] The coefficient k for converting the benchmark value of the household to be calculated into the theoretical value is obtained based on the equivalent utilization hours of the photovoltaic station without abnormalities in N natural days of the household to be calculated and the benchmark utilization hours of the photovoltaic power station;

[0033] Calculate the equivalent utilization hours of the photovoltaic power station for all households in the sample during 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 for the household to be calculated during 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 hot spring 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 is the sum of the values ​​between the upper quartile and 1.5 times the upper quartile and the lower quartile. The lower limit is the difference 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 (district / county) to which the household whose power loss is to be calculated belongs is used as the preset area for the statistical sample;

[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 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 the area that meets the target sample number n as the preset area of ​​the statistical sample.

[0045] Exemplarily, the method further includes:

[0046] When a circle with a preset length as the radius is used as the preset area for statistical samples, the radius division supports selecting the preset area according to different combinations of radius and phase angle;

[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 the preset area of ​​the statistical sample, in terms of parameter setting, it supports selecting the preset area according to the corresponding search radius upper limit set at different phase angles.

[0048] Another aspect of the present disclosure provides 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 statistics module, configured to collect statistics of all normal household usage samples within a preset area within which the single household whose power loss is to be calculated belongs during the abnormal duration;

[0051] Theoretical power generation calculation module 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 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] 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-described method when executed by a processor.

[0054] Another aspect 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.

[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. Based on normal household samples in the preset area, the method calculates various types of power loss of abnormal household distributed stations with high accuracy, realizes the monitoring of abnormal losses during distributed operation, provides guidance for relevant decisions of operation and maintenance management, and thus provides 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 This 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 under abnormal conditions proposed in an embodiment of the present disclosure;

[0059] Figure 3 This is a structural 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 This is a structural 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 1 is a structural diagram of a box method for calculating household power loss proposed in an embodiment of the present disclosure;

[0062] Figure 6 This 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 solutions and advantages of the embodiments of the present disclosure more clear, the embodiments of the present disclosure are further described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation methods described herein are only used to explain the embodiments of the present disclosure and are not intended to limit the embodiments of the present disclosure.

[0064] In view of the difficulty in calculating the power loss in the event of abnormal conditions at household distributed sites, the low accuracy and inability to classify the loss types, the power loss types are divided by manually selecting the types by associating them with the abnormal handling of the household distributed photovoltaic site; and the benchmark power generation reference value of the region is calculated through different regional division methods, which serves 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 the operation and maintenance of household distributed photovoltaics, including: a method for dividing the power loss types 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] Based on actual needs, photovoltaic systems are installed for multiple households within a specific area, forming a distributed photovoltaic station within that area. Each household generates electricity and uploads it to the grid. Each household also has an inverter. If an alarm signal is generated by the inverter of any household in the distributed photovoltaic station, it indicates an abnormality in the household's power generation, and the household is identified as a single household for power loss calculation. Currently, data collection for household distributed photovoltaic systems generally uses a data acquisition wand to collect data from the inverter. The group's calculation of power loss generally relies on faulty operation or abnormal downtime, and does not consider losses caused by inefficient operation without abnormalities. Therefore, when power loss occurs, in most cases, related abnormal alarms are also generated on the inverter side. For example, in the case of power loss due to power curtailment, the inverter side will generate an alarm indicating a grid failure. Combined with the handling of on-site reported issues, after comprehensive analysis, the type of power loss can be classified by manual intervention during exception handling.

[0068] The specific process for calculating and processing the power loss in abnormal household conditions 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 on-site operation and maintenance personnel or household distributed owners after discovering on-site problems. "Abnormal confirmation" refers to the further classification and confirmation of abnormalities by operation and maintenance management personnel based on 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 of the abnormality. "Theoretical power generation within the duration" refers to the theoretical power generation of the household distributed converted from the benchmark power generation within the duration of the abnormality. "Loss of electricity within the duration" refers to the calculated loss of electricity for the household within the duration 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: The power generation loss is caused by the inability of the generated electricity to be connected to the grid due to power curtailment.

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

[0073] Accumulated losses: Accumulated losses mainly include grid-accumulated losses and dispute-accumulated losses. Grid-accumulated 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-accumulated losses refer to the power generation losses caused by disputes with household distributed 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 field 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] Taking the distributed solar panels of a single household whose power loss is to be calculated (hereinafter referred to as the household to be calculated) as the base point, sample statistics are performed using different methods. All samples must exclude abnormal households. That is, during the period of abnormality of the household to be calculated, there may also be abnormal distributed solar panels, such as inverter alarms and equipment offline. The statistical methods for normal household samples include:

[0078] Counting all normal household usage samples within a preset area within the duration of the abnormality for a single household whose power loss is to be calculated, wherein the method for determining the preset area includes:

[0079] a. Manually divide the sample area. Select the distributed energy consumption of a single household to be calculated and, based on actual needs, such as by geographic region, O&M point management area, or manual division, group the distributed energy consumption of each household into a sample calculation area. In other words, group the distributed energy consumption of each household within the geographic region or O&M point management area of ​​the household whose power loss is to be calculated into a sample calculation area. The geographic region or O&M point management area of ​​the household to be calculated 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 calculated by district / county, with the administrative region - district / county to which the household whose power loss is to be calculated belongs as the preset area for the statistical sample; that is, the administrative region - 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 photovoltaic power generation caused by weather differences and ensure the accuracy of sample calculation, it is recommended that the preset radius be selected no 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 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, take the household whose power loss is to be calculated 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 the area that meets the target sample number n as the preset area of ​​the statistical sample.

[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 18 km, the number of samples n is 480, which does not reach the target number. After increasing the search radius to r = 20 by step s, the number of samples n is 511. It is considered that when r = 20, the number of samples meets the set requirement, and at this time n = 511.

[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 sample number n, the actual number of samples searched is used as the sample number.

[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, when a circle with a preset length as a radius is used as a preset area for statistical samples, in terms of radius division, 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 the preset area of ​​the statistical sample, in terms of parameter setting, it supports selecting the preset area according to the corresponding search radius upper limit set at different phase angles.

[0090] Here, the relatively close and concentrated areas within the preset area can be divided into sub-areas. A sub-area can have the same or different numbers of households, and each sub-area can be set according to actual conditions. Each household in a sub-area may have similar equivalent utilization hours. For example, a sub-area can be a village or town, and each sub-area has similar equivalent utilization hours. In other words, there can be multiple sub-areas within the preset area. Based on the above selection of preset areas a to d, the regional average equivalent utilization hours for the preset time period of the sub-area where the household to be calculated is located, i.e., the first value, and the regional average equivalent utilization hours for the preset time period of the remaining sub-areas within the preset area, i.e., 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 period 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. The sub-areas with a difference less than the threshold are selected as candidate areas, and the normal households in each candidate area are used as the final samples within the preset area. Based on the difference and the threshold, candidate regions are determined from the remaining sub-regions in the preset region, that is, sub-regions whose difference, or whose absolute value of the difference is less than the threshold, are selected as candidate regions. The preset time period can be set according to actual conditions.

[0091] Furthermore, the threshold value 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 value can be reduced. That is, when selecting candidate regions, the target sub-regions close to the current sub-region of the household to be calculated have a large threshold value, and when selecting candidate regions, the target sub-regions far from the current sub-region of the household to be calculated have a small threshold value.

[0092] The historical data on power loss can be obtained using the method of the embodiment of the present disclosure or other methods. The purpose of sample selection is to eliminate the influence of some external factors on power generation, such as local weather and topographic conditions. For example, some locations are in mountainous areas, while others are in plains. The sunshine duration and radiation amount will vary greatly, and the corresponding power generation will also vary greatly. The purpose of the search is also to ensure that the selected samples are as similar as possible to the external conditions of the field to be calculated.

[0093] Step S30: 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 the single household whose power loss is to be calculated.

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

[0095] The embodiment of the present disclosure mainly lists two methods for calculating the theoretical power generation of the household to be calculated during the abnormal duration based on the number of samples. The two methods for calculating the theoretical power generation of the household to be calculated during the abnormal duration based on the samples of all normal households in a preset area include:

[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 based on 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 by normal households is small and they are not used as benchmark samples for calculating 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 based on the equivalent utilization hours of normal operation without abnormalities in the N natural days closest to the abnormal duration of the household to be calculated, the benchmark utilization hours of normal household samples without abnormalities, and the benchmark utilization hours of normal household samples during the abnormal duration of the household to be calculated, where N can be set according to actual conditions, and 15<N<35. The first preset threshold can be set according to actual conditions and can range from 15 to 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 during the abnormal duration based on 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 meteorological data within the abnormal duration of the single household whose power loss is to be calculated.

[0102] The first preset threshold can be 20. That is, when the number of samples of normal household usage is greater than or equal to 0 and less than 20, meteorological data for the duration of the abnormality of the 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 and maximum temperature on the day of the abnormality of the household to be calculated.

[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, the historical meteorological data of a single day is queried separately, and the normal actual power generation on different dates but the same time corresponding to the abnormality duration is calculated and summed 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: October 5th 10:10:24 to October 6th 19:01:35, then the meteorological data of October 5th and October 6th 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 the corresponding household has no abnormalities, 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 is queried separately, and then the power generation on consecutive days without similar meteorological conditions is calculated separately, such as the power generation from 10:10:20 to 23:59:59 on the fifth day and the power generation from 00:00:00 to 19:01:35 on the seventh day, and then the sum is added 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 during the abnormal duration based on all normal household samples in the preset area includes:

[0111] Step S321: When the number of samples of all normal households within the preset area of ​​the abnormal duration of the household to be calculated is greater than or equal to a first preset threshold and less than a second preset threshold, the daily power generation of the household to be calculated during the N natural days preceding the abnormal operation is calculated, and based on the installed capacity of the household to be calculated, the equivalent utilization hours of the household to be calculated during the N natural days preceding the abnormal operation are calculated, where 15 < N < 35. The first and second preset thresholds can be set according to actual conditions and can be 20 and 100, respectively.

[0112] Step S322: Calculate the equivalent utilization hours of the distributed 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 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 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 household to be calculated and the N natural days of sample normal photovoltaic station power generation households and the benchmark utilization hours of the photovoltaic power station power generation households.

[0115] Step S324: Calculate the equivalent utilization hours of the PV station for each household in the normal sample during the duration of the abnormality for the household to be calculated. Sort the equivalent utilization hours of the first m PV station-generating households from highest to lowest, and calculate their average, which is the benchmark utilization hours for the household to be calculated during 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 calculated. m is greater than 0 and can be set according to actual conditions.

[0116] Step S325: Obtain the theoretical power generation of the household to be calculated based on 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 for the household to be calculated in the past 30 days;

[0119] 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 no-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 no-abnormal benchmark utilization hours, which is used as the no-abnormal benchmark utilization hours of the household to be calculated: data can be used to calculate the equivalent utilization hours of the distributed photovoltaic stations in the no-abnormal sample of each day. 1－30 The samples without abnormalities on each day serve as the non-abnormal samples in the second step.

[0121] The number of hours of normal benchmark utilization in the past 30 days = Σ(data 1－30 The average value of equivalent utilization hours of power generation households at photovoltaic stations before m per day).

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

[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 each household in the sample during the duration of the abnormality. For example, if the abnormality lasted from 10:10:24 on October 5th to 19:01:35 on October 6th, for each household in the sample, take the power generation during this period and divide it by the household's installed capacity. This calculated value is the equivalent utilization hours of the household's PV station during the duration of the abnormality. Then, average the first m equivalent utilization hours of the PV station. This value is the benchmark utilization hours for the household during the abnormality. M can range from 8 to 12, and is typically 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 coefficient 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 during the abnormal duration based on all normal household samples in the preset area includes:

[0129] Step S331: 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 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 based on the installed capacity of the household to be calculated, the equivalent utilization hours of the photovoltaic power station for the household to be calculated in the N natural days without abnormality are obtained, where N can be set according to actual conditions, and 15<N<35.

[0130] Step S332: Use the box plot method to calculate the equivalent utilization hours of the photovoltaic station for each of the N natural days with no abnormal samples in the preset area, remove the abnormal data in the samples, take the average of all the data, and obtain the benchmark utilization hours of the photovoltaic station without abnormalities in the N natural days based on the average equivalent utilization hours of the N natural days.

[0131] Step S333: Obtain 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 station without abnormalities in N natural days and the benchmark utilization hours of the photovoltaic power station for the household to be calculated.

[0132] Step S334: Calculate the equivalent utilization hours of the photovoltaic power station for each household in all samples during 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 for the household to be calculated during the duration of the abnormality; combine it with the installed capacity of the household to be calculated to obtain the benchmark power generation of the household to be calculated;

[0133] Step S335: Obtain the theoretical power generation of the household to be calculated based on 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 number of samples 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 for the household to be calculated in the past 30 days:

[0136] 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 within the sample on each day are calculated using the box plot method.

[0138] like Figure 5 As shown in the figure, the upper quartile (Q75%) is the value at the 1 / 4 position when the data is arranged from large to small. The median is the value at the 1 / 2 position when the data is arranged from large to small. The lower quartile (Q25%) is the value at the 3 / 4 position when the data is arranged from large to small. The IQR is calculated as Q75% minus Q25%. The upper limit is Q75% plus 1.5 times the IQR. The lower limit is Q25% minus 1.5 times the IQR. Values ​​above the upper limit and below the lower limit are considered discrete points and should 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 photovoltaic station in the natural day, and then take the average value of 30 days and add them up to obtain the sample normal utilization hours.

[0140] The number of hours of use without abnormal benchmarks in the past 30 days = Σ(data1-30, the average of the number of hours of use of 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 factor k = equivalent utilization hours of the photovoltaic station without abnormalities in the past 30 days for the household to be calculated / benchmark utilization hours without abnormalities in the past 30 days for the sample

[0143] Step 4: Calculate the equivalent utilization hours of each household in the sample during the duration of the abnormality. For example, if the abnormality lasted from 10:10:24 on October 5th to 19:01:35 on October 6th, for each household in the sample, take the power generation during this period and divide it by the household's installed capacity. The calculated value is the equivalent utilization hours of the household's PV station during the duration of the abnormality. Then, use the box plot method to eliminate abnormal data (discrete points) and take the average. This value is the benchmark utilization hours for the household during 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 coefficient k × benchmark power generation of the household to be calculated

[0147] Step S40: Obtain the power loss of the household during the abnormality duration to be calculated based on the actual power generation and the theoretical power generation of the household during the abnormality duration to be calculated.

[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 that period minus the actual power generation of the household to be calculated during that 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 this disclosed embodiment, for each household's distributed photovoltaic power supply, the system can configure the reference sample area for calculating power loss by manually configuring the area, automatically dividing by district / county, dividing by search radius, or searching by target sample number. Searching by search radius and by target sample number supports batch operations for multiple household distributed systems. If an abnormality occurs in a household within the distributed system, the system will automatically calculate the associated power loss based on the actual number of units in the sample area.

[0151] like Figure 6 As shown, another aspect of the present disclosure provides a household power loss calculation device, which is applied to each household using distributed photovoltaic power. 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 usage samples in the preset area. The household to be calculated is the 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 power loss calculation method of the disclosed embodiment is based on the actual situation of distributed operation and maintenance management, and independently designs an algorithm. Through multiple methods, it calculates various types of power losses of household distributed stations with abnormalities, 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 present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-described method when executed by a processor.

[0158] Another aspect 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 within the scope of protection 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 household whose power loss is to be calculated; Count all normal household samples within the preset area within the abnormal duration of the single household whose power loss is to be calculated; the method for determining the preset area includes: taking the single household whose power loss is to be calculated as the origin, and using the target sample number n, target search step size s, and search radius upper limit R max As a parameter, the search radius is gradually increased according to the step size s to obtain the area that meets the target sample number n as the preset area of ​​the statistical sample; Based on the equivalent utilization hours of all normal household samples in the preset area and the installed capacity of the household to be calculated, the theoretical power generation of the household to be calculated during the abnormal duration is calculated. The household to be calculated is the single household whose power loss is to be calculated; According to the difference between the actual power generation of the household with abnormal duration to be calculated and the theoretical power generation, the power loss of the household with abnormal duration to be calculated is obtained; The calculation of the theoretical power generation of the household to be calculated during the abnormal duration based on the equivalent utilization hours of all normal household samples in the preset area and the installed capacity of the household to be calculated includes: When the number of samples of all normal households in the preset area is less than a first preset threshold, the theoretical power generation of the household to be calculated during the abnormal duration is determined based on the meteorological data of the household to be calculated during the abnormal duration and the actual power generation in the historical meteorological data; including: when the number of samples of all normal households in the preset area during the abnormal duration of the household to be calculated is less than the first preset threshold, obtaining the meteorological data of the household to be calculated during the abnormal duration, 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 consecutive weather conditions 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 is queried separately, and the actual power generation on different days but at the same time corresponding to the abnormality duration is calculated and summed as the benchmark power generation of the household to be calculated, that is, the theoretical power generation of the household to be calculated; 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 based on 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.

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 based on all normal household samples in the preset area includes: When the number of samples of all normal households within 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 obtained, and the equivalent utilization hours of the photovoltaic station without abnormality for the household to be calculated in the N natural days are obtained based on 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 on the same N natural days in the preset area, 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, and obtain the benchmark utilization hours without abnormalities on N natural days based on the average equivalent utilization hours of N natural days; The coefficient k for converting the benchmark value of the household to be calculated into the theoretical value is obtained based on the equivalent utilization hours of the household to be calculated in N natural days without abnormal photovoltaic station power generation and the benchmark utilization hours of the photovoltaic power station power generation household; Calculate the equivalent utilization hours of the PV stations of all normal samples of households 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 PV station power generation households, and obtain their average value, which is the benchmark utilization hours of the household to be calculated within the duration of the abnormality; combine it with the installed capacity of the household to be calculated to obtain the benchmark 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, the theoretical power generation of the household to be calculated is obtained.

3. 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 based on all normal household samples in the preset area includes: When the number of samples of all normal households within 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 the equivalent utilization hours of the photovoltaic power station of the household to be calculated in the N natural days without abnormality are obtained based on the installed capacity of the household to be calculated, where 0<N; Use the box plot method to calculate the equivalent utilization hours of the PV stations with no abnormalities in the N natural days of the same household 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 PV stations with no abnormalities in the N natural days based on the average equivalent utilization hours of the N natural days. The coefficient k for converting the benchmark value of the household to be calculated into the theoretical value is obtained based on the equivalent utilization hours of the photovoltaic station without abnormalities in N natural days of the household to be calculated and the benchmark utilization hours of the photovoltaic power station; Calculate the equivalent utilization hours of the photovoltaic power station for all households in the sample during 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 for the household to be calculated during 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.

4. The method according to any one of claims 1 to 3, 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 (district / county) to which the household whose power loss is to be calculated belongs is used as the preset area for the statistical sample; 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.

5. The method according to claim 4, characterized in that The method further comprises: When a circle with a preset length as the radius is used as the preset area for statistical samples, the radius division supports selecting the preset area according to different combinations of radius and phase angle; When the step size s is gradually increased, the area that meets the target sample number n is obtained as the statistical sample. When presetting an area, the parameter settings support selecting the preset area by setting the upper limit of the search radius corresponding to different phase angles.

6. 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 statistics module, configured to collect statistics of all normal household usage samples within a preset area within which the single household whose power loss is to be calculated belongs during the abnormal duration; Theoretical power generation calculation module 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 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.

7. 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 5 are implemented.

8. 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 5 are implemented.

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