Distributed photovoltaic area power quality monitoring method and device

Abstract

The invention relates to the technical field of power system analysis, and discloses a distributed photovoltaic district power quality monitoring method and device, and the method comprises the steps: periodically collecting the monitoring indexes of the power quality of a distributed photovoltaic district; comparing the monitoring index with a preset threshold value; and dynamically switching the power quality monitoring mode according to the comparison result. Two monitoring modes of lightweight sensing and deep sensing are dynamically switched according to the relationship between monitoring indexes and a preset threshold value by counting the serious degradation degree of the indexes within a period of time, the types and granularity of the monitoring indexes are dynamically controlled by means of a micro-application management and control platform, and cause analysis functions for starting / stopping different electric energy quality problems are adjusted. Dynamic perception of the electric energy quality problem is realized, the overall utilization rate of monitoring system resources is effectively improved, the network transmission burden is reduced, the data storage pressure is reduced, and lightweight perception of the electric energy quality state of the distributed photovoltaic transformer area is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power system analysis, and in particular to a method and device for monitoring the power quality of a distributed photovoltaic substation area. Background Art

[0002] In recent years, with the accelerated construction of a new power system, a large number of new types of power sources and loads such as high-penetration distributed photovoltaic power generation, high-coverage electric vehicle charging facilities, and large-scale electric heating have been connected to the substation area, exacerbating the nonlinearity and randomness of the power sources and loads in the distribution substation area, resulting in more prominent and co-existing power quality problems such as high / low voltage, three-phase imbalance, and harmonics in the distribution substation area. The power quality problems of distributed photovoltaic substation areas have attracted wide social attention.

[0003] The existing ability to monitor and analyze the power quality of distributed photovoltaic substation areas is seriously insufficient, and the restrictive factors are mainly reflected in three aspects: (1) Restricted by the high cost of power quality monitoring terminals, it is impossible to promote and deploy points in a large number of scattered distributed photovoltaics and key important / sensitive nodes, and the distribution network lacks effective monitoring means; (2) The distribution network has a large number of nodes, and at the same time, there are many power quality indicators and various granularities. The massive distribution network monitoring indicators bring huge data transmission and storage pressure to the power quality monitoring system. Therefore, the engineering promotion of unified monitoring indicators for the distribution network is poor; (3) The power supply environment of distributed photovoltaic substation areas is complex and there are many problems. It is difficult to trace the power quality problems and the timeliness is poor by simply relying on a small number of monitoring points through modeling and manual analysis means, and it is impossible to support the formulation of power quality improvement plans for distributed photovoltaic substation areas.

[0004] Restricted by the above factors, there is currently no suitable power quality monitoring technology for distributed photovoltaic substation areas. Summary of the Invention

[0005] In view of this, the present invention provides a method and device for monitoring the power quality of a distributed photovoltaic substation area to solve the problem that there is currently no suitable power quality monitoring technology for distributed photovoltaic substation areas.

[0006] In a first aspect, the present invention provides a method for monitoring the power quality of a distributed photovoltaic substation area, the method including:

[0007] Periodically collect monitoring indicators of the power quality of the distributed photovoltaic substation area;

[0008] Compare the monitoring indicators with a preset threshold;

[0009] Dynamically switch the power quality monitoring mode according to the comparison result.

[0010] Distributed photovoltaic substation power quality adaptive perception strategy for edge computing mode, covering the perception of steady-state problems such as voltage, imbalance, and harmonics, as well as transient power quality perception events, solving the problems of insufficient power quality monitoring resources and high communication pressure, and realizing panoramic perception of power quality in distributed photovoltaic substations based on existing distribution network monitoring resources.

[0011] In an alternative implementation, the dynamically switching the power quality monitoring mode according to the comparison result includes:

[0012] When the monitoring index exceeds the preset threshold, switch the power quality monitoring mode to the in-depth perception mode;

[0013] When the monitoring index does not exceed the preset threshold, switch the power quality monitoring mode to the lightweight perception mode.

[0014] Dynamically switch between the lightweight perception and in-depth perception monitoring modes according to the relationship between the monitoring index and the preset threshold, dynamically control the monitoring index type and granularity relying on the micro-application management platform, adjust the start / stop of the cause analysis function for different power quality problems, and realize dynamic perception of power quality problems.

[0015] In an alternative implementation, the data granularity in the in-depth perception mode is minute-level / recording wave, the monitoring index is a multi-dimensional index, and the cause analysis function for power quality problems is enabled.

[0016] In an alternative implementation, the data granularity in the lightweight perception mode is daily statistical value, the monitoring index is a basic index, and the cause analysis function for power quality problems is stopped.

[0017] Evaluating the severity level of power quality based on coarse-grained macro statistical indicators, dynamically adjusting the monitoring rules according to the perception strategy state machine, effectively improving the overall utilization rate of monitoring system resources, reducing the network transmission burden, reducing the data storage pressure, and realizing lightweight perception of the power quality status in distributed photovoltaic substations.

[0018] In an alternative implementation, when the power quality of the distributed photovoltaic substation is steady-state power quality, the monitoring indexes include: voltage over-limit rate, equivalent power factor over-limit rate, harmonic pollution coefficient, and imbalance coefficient;

[0019] When the power quality of the distributed photovoltaic substation is transient power quality, the monitoring index includes: voltage sag energy.

[0020] In an alternative implementation, the preset threshold is dynamically changed by statistically analyzing the historical data within a preset time.

[0021] The voltage quality adaptive perception process based on statistical process control dynamically and rolling updates the judgment threshold for monitoring mode change through statistical learning of recent historical data, achieving precise perception of voltage problems.

[0022] In a second aspect, the present invention provides a power quality monitoring device for a distributed photovoltaic substation area, the device includes:

[0023] An acquisition module for periodically acquiring monitoring indicators of the power quality of the distributed photovoltaic substation area;

[0024] A comparison module for comparing the monitoring indicators with a preset threshold;

[0025] A switching module for dynamically switching the power quality monitoring mode according to the comparison result.

[0026] The adaptive perception strategy for the power quality of the distributed photovoltaic substation area in the edge computing mode covers the perception of steady-state problems such as voltage, imbalance, and harmonics, as well as transient power quality perception events, solves the problems of insufficient power quality monitoring resources and high communication pressure, and realizes the panoramic perception of the power quality of the distributed photovoltaic substation area based on the existing distribution network monitoring resources.

[0027] In an optional embodiment, the switching module includes a first switching unit and a second switching unit, wherein,

[0028] The first switching unit is used to switch the power quality monitoring mode to the deep perception mode when the monitoring indicator exceeds the preset threshold;

[0029] The second switching unit is used to switch the power quality monitoring mode to the lightweight perception mode when the monitoring indicator does not exceed the preset threshold.

[0030] In a third aspect, the present invention provides a computer device, including: a memory and a processor, which are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the power quality monitoring method for the distributed photovoltaic substation area in the first aspect or any corresponding embodiment thereof.

[0031] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the power quality monitoring method for the distributed photovoltaic substation area in the first aspect or any corresponding embodiment thereof. Description of the Drawings

[0032] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the accompanying drawings required for the description of the specific embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0033] Figure 1 It is a schematic flowchart of a distributed photovoltaic substation area power quality monitoring method according to an embodiment of the present invention;

[0034] Figure 2 It is a schematic flowchart of an adaptive perception strategy for power quality steady-state problems according to an embodiment of the present invention;

[0035] Figure 3 It is a schematic flowchart of an adaptive perception strategy for power quality transient events according to an embodiment of the present invention;

[0036] Figure 4 It is a structural block diagram of a distributed photovoltaic substation area power quality monitoring device according to an embodiment of the present invention;

[0037] Figure 5 It is a schematic hardware structure diagram of a computer device according to an embodiment of the present invention. Specific Embodiments

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0039] With the substantial improvement in the digital level, intelligent construction, and application level of modern distribution networks, power grid companies are accelerating the transformation to the energy Internet. In the top-level design of the distribution Internet of Things, it is mentioned that taking the intelligent fusion terminal of the substation area as the core, adopting the technical architecture of "unified hardware platform + edge operating system + APP business application software", and realizing the flexible deployment of business functions and the real-time reliability of business processing through software-defined terminals and edge computing. Currently, the intelligent fusion terminal of the distribution substation area is continuously and steadily promoted, which lays a hardware foundation for the digitalization of the power quality business in the distributed photovoltaic substation area.

[0040] On this basis, the present invention provides a method for monitoring the power quality of a distributed photovoltaic substation area. Relying on the edge computing ability of the intelligent fusion terminal platform in the substation area, a power quality dynamic monitoring strategy adaptive to the scenario is proposed. Based on a finite state machine, dynamic decoupling is used to achieve adaptive perception of steady-state power quality. The severity level of power quality is evaluated based on coarse-grained macroscopic statistical indicators. The monitoring rules are dynamically adjusted according to the state machine of the perception strategy, and specific perception rules such as the acquisition range, monitoring indicators, data granularity, processing methods, upload frequency, waveform recording, etc. are clarified, realizing the automation of power quality perception in the distributed photovoltaic substation area. The active perception strategy effectively improves the overall utilization rate of the monitoring system resources, reduces the network transmission burden, eases the data storage pressure, realizes lightweight perception of the power quality status in the distributed photovoltaic substation area, and lays a foundation for the in-depth exploration of business values such as modeling the characteristics of distributed photovoltaic clusters and warning and tracing power quality disturbances.

[0041] According to an embodiment of the present invention, an embodiment of a method for monitoring the power quality of a distributed photovoltaic substation area is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0042] In this embodiment, a method for monitoring the power quality of a distributed photovoltaic substation area is provided, which can be used for the above-mentioned mobile terminals, such as smart meters, mobile phones, tablet computers, etc. Figure 1 is a flowchart of a method for monitoring the power quality of a distributed photovoltaic substation area according to an embodiment of the present invention, as Figure 1 shown, and this process includes the following steps:

[0043] Step S1, periodically collect the monitoring indicators of the power quality of the distributed photovoltaic substation area.

[0044] In a specific embodiment, the power quality of the distributed photovoltaic substation area is divided into steady-state power quality and transient power quality. When the power quality of the distributed photovoltaic substation area is steady-state power quality, the adaptive perception of the power quality of the distributed photovoltaic substation area monitors around three types of power quality indicators: voltage, three-phase unbalance, and harmonics. Based on a finite state machine, dynamic decoupling of the three types of indicator monitoring modes is used to achieve adaptive perception of steady-state power quality. When the power quality of the distributed photovoltaic substation area is transient power quality, the adaptive perception of the power quality of the distributed photovoltaic substation area is based on the collected recorded data of the substation area's gateway voltage and current waveforms, and the voltage sag energy index is used to achieve adaptive perception of transient power quality.

[0045] In the embodiments of the present invention, when the power quality of the distributed photovoltaic substation area is steady-state power quality, the monitoring indicators include: voltage over-limit rate, equivalent power factor over-limit rate, harmonic pollution coefficient, and unbalance coefficient. When the power quality of the distributed photovoltaic substation area is transient power quality, the monitoring indicator includes: voltage sag energy.

[0046] Step S2: Compare the monitoring indicators with the preset thresholds.

[0047] In a specific embodiment, considering the change trend of the power quality level and the diversity of the problem causes, the preset thresholds are divided into two types, type I and type II. For voltage, three-phase unbalance, and harmonic indicators, exceeding one of the thresholds is regarded as a serious power quality problem. The definitions of the two types of thresholds are as follows:

[0048] (a) The type I threshold is calculated based on the average value (μ) and the range (Υ) of the severity of this indicator on all the over-limit days of this indicator at this monitoring point in recent years. The calculation formula is μ + ɑ * Υ. The influence factor ɑ can be obtained by looking up the statistical control chart or by learning from the measured data.

[0049] (b) The type II threshold is calculated based on the average value (μ) and the range (Υ) of the over-limit severity of this indicator on all the over-limit days of this indicator at this monitoring point in recent several weeks. The calculation formula is μ + ɑ * Υ. The influence factor ɑ can be obtained by looking up the statistical control chart or by learning from the measured data.

[0050] The judgment time window needs to be obtained by combining the time-effect analysis requirements of different photovoltaic penetration level substations, taking into account the detection sensitivity of power quality problems and the computing resources of the intelligent fusion terminal, and verifying with a large amount of measured and simulation data.

[0051] Step S3: Dynamically switch the power quality monitoring mode according to the comparison result.

[0052] In a specific embodiment, the monitoring modes include two types: lightweight sensing mode and in-depth sensing mode. Among them, the data granularity in the in-depth sensing mode is minute-level / recording wave, the monitoring indicators are multi-dimensional indicators, and the function of analyzing the causes of power quality problems is enabled. The data granularity in the lightweight sensing mode is daily statistical value, the monitoring indicators are basic indicators, and the function of analyzing the causes of power quality problems is stopped.

[0053] In an alternative embodiment, step S3 includes the following steps:

[0054] Step S31: When the monitoring indicator exceeds the preset threshold, switch the power quality monitoring mode to the in-depth sensing mode.

[0055] Step S32: When the monitoring indicator does not exceed the preset threshold, switch the power quality monitoring mode to the lightweight sensing mode.

[0056] In a specific embodiment, as Figure 2 shown, when the power quality of the distributed photovoltaic substation area is steady-state power quality, the types of monitoring indicators include two categories: voltage and equivalent power factor. The specific indicators include the upper voltage limit rate, the lower voltage limit rate, the equivalent power limit rate, the harmonic pollution coefficient, and the unbalance coefficient.

[0057] Among them, in the adaptive perception strategy for voltage problems: the voltage monitoring mode for the next period is determined by regularly evaluating the severity of the voltage-related indicators in this week. The types of statistical values used for evaluation are statistical characteristic values such as the mean, extreme value, and variance of the relevant indicators within this period. An abnormal threshold is constructed based on the statistical control chart theory. When the statistical characteristic value of the online voltage-related indicator exceeds the abnormal threshold, the in-depth perception mode is entered, and the aggregated statistics of the minute-level data of indicators such as phase current, phase voltage, load rate, unbalance degree, and power factor are increased, and at the same time, the function of analyzing the cause of voltage limit violation is started; when the statistical characteristic value of the online voltage-related statistical indicator does not exceed the abnormal threshold, it is switched to the lightweight perception mode. In the lightweight perception mode, only the upper voltage limit rate and the lower voltage limit rate need to be statistically counted, and the function of analyzing the cause of voltage limit violation is stopped.

[0058] In the adaptive perception strategy for three-phase unbalance and harmonic problems: there is a correlation between the three-phase unbalance and harmonic problems, and the system should be dynamically decoupled or linked according to the specific scenario. To further reduce the perception cost, in the lightweight perception mode, only the equivalent power factor limit rate needs to be statistically counted. When it exceeds the threshold, two indicators, the harmonic pollution coefficient and the unbalance coefficient, are added for monitoring. Whether to switch to the in-depth perception mode for unbalance and the in-depth perception mode for harmonics is determined by judging the severity of the harmonic pollution coefficient and the unbalance coefficient. For in-depth unbalance perception, indicators such as analysis current, distributed penetration rate, load rate, unbalance degree, and active power volatility are added, and the function of analyzing the cause of three-phase unbalance is started. For in-depth harmonic perception, branch power, branch harmonic currents of each frequency, and bus harmonic voltages of each frequency are added, and the function of analyzing the cause of harmonics is started.

[0059] In the process of adaptive perception of steady-state power quality, a hierarchical and graded adaptive perception process for harmonics and three-phase unbalance is proposed. By introducing non-sinusoidal power theory indicators such as equivalent power factor, harmonic pollution coefficient, and unbalance coefficient, and through the dynamic decoupling and linking of harmonic and three-phase unbalance indicators, the monitoring of power quality problems in distributed photovoltaic substation areas at different levels is realized.

[0060] When the power quality of the distributed photovoltaic substation area is transient power quality, the severity of the sag environment is studied through the sag energy, and the voltage sag time-domain and frequency-domain characteristics are actively triggered for extraction to achieve the adaptive perception of voltage sag. Specifically, the overall active perception process of voltage sag analysis is as Figure 3As shown in the figure, based on the collected voltage and current oscillogram data of the substation gateway, the voltage sag energy index is adopted, and the severity threshold is obtained based on the statistical control chart. The severity is judged periodically through the statistical value of the sag energy, and then the sensing mode is switched. For the substation with severe voltage sag, the deep sensing mode is switched, more voltage sag characteristic indexes are added, and the voltage sag cause analysis function is started.

[0061] First, the sag energy index within a specified time window is statistically aggregated, a statistical control chart is constructed based on the aggregated data within a period of time, and the sag severity assessment is realized based on the outlier criterion of the statistical control chart. By comparing with the threshold hs, the sensing mode to enter is determined.

[0062] Secondly, different strategies are adopted for different sensing modes.

[0063] For mild sensing, the daily cumulative voltage sag energy data is mainly calculated, and the monitoring granularity is the daily statistical value. The voltage sag cause analysis function is turned off in this mode.

[0064] For deep sensing, 8 disturbance characteristic quantities are added to be extracted from the voltage effective value data recorded during the sag process, and the voltage sag cause analysis function is turned on to realize voltage sag analysis. The disturbance characteristic quantities are defined as follows:

[0065] 1) Sag minimum value U min

[0066] U min is the global per-unit minimum value of the voltage effective value during the sag process, and is calculated as follows:

[0067] U min =min(U min_a ,U min_b ,U min_c ) / U n (1)

[0068] where U n is the nominal voltage, and min() is the minimum value function. The corresponding moment of U min is t min .

[0069] 2) Sag average value U ave

[0070] U ave is the average value of the voltage effective value during the sag process, and is calculated as follows:

[0071]

[0072] where U(i)=(U a (i)+U b (i)+U c(i)) / 3, that is, the average value of the three-phase voltage of this cycle.

[0073] 3) Sag duration t sd

[0074] t sd is the duration from the occurrence to the end of the transient event, in cycles, called the sag duration, and is calculated as follows:

[0075] t sd = t e - t s (3)

[0076] where, t s is the occurrence time of the transient event, and t e is the end time of the transient event.

[0077] 4) Minimum value position p x

[0078] At time t min at t sd relative position:

[0079] p x = (t min - t s ) / t sd (4)

[0080] 5) Drop slope r down and rise slope r up

[0081] First, define the voltage value when dropping to 75% of the maximum amplitude during the sag as the threshold voltage value U 25％ , and the calculation formula is as follows:

[0082] U 25％ = (0.9 - U min ) / 4 + U min (5)

[0083] Record the time when first reaching U 25％ during the sag as t 25％,1 , and record the time when last reaching U 25％ during the sag as t 25％,-1 .

[0084] Then the sag drop slope r down , is the slope from the data point at the sag start time t s to the data point at the time t 25％,1 when first reaching 75% of the maximum amplitude, and the calculation formula is as follows:

[0085] r down = (0.9 - U25％ ) / (t 25％,1 -t s ) (6)

[0086] Then the sag rising slope r up, , which is the time t when the last time reaches 75% of the maximum amplitude 25％,-1 The slope from the data point to the data point at the end of the sag.

[0087]

[0088] 7) The dispersion characteristic U of the minimum value of each phase sag ε

[0089] U ε is the dispersion characteristic U of the minimum value of each phase sag during the sag process ε , and is defined as follows:

[0090]

[0091] In the formula, max() is the maximum value function, min() is the minimum value function, and ave() is the average value function.

[0092] 8) The number of phases of sag N 1

[0093] The number of phases where voltage sag occurs. When U min_a , U min_b , U min_c are all less than the sag threshold of 0.9, N 1 = 3; when there are exactly two values less than the sag threshold of 0.9, N 1 = 2; when there is exactly one value less than the sag threshold of 0.9, N 1 = 1.

[0094] The present invention provides a method for monitoring the power quality of a distributed photovoltaic substation area, including: periodically collecting the monitoring indicators of the power quality of the distributed photovoltaic substation area; comparing the monitoring indicators with a preset threshold; dynamically switching the power quality monitoring mode according to the comparison result. By statistically analyzing the degree of severe deterioration of the indicators over a period of time, dynamically switching between two monitoring modes of lightweight perception and in-depth perception according to the relationship between the monitoring indicators and the preset threshold, relying on the micro-application control platform to dynamically control the type and granularity of the monitoring indicators, and adjusting the start / stop of the cause analysis function for different power quality problems, the dynamic perception of power quality problems is realized. The active perception strategy effectively improves the overall utilization rate of the monitoring system resources, reduces the network transmission burden, reduces the data storage pressure, realizes the lightweight perception of the power quality status of the distributed photovoltaic substation area, and lays a foundation for the in-depth business value mining such as the modeling of the distributed photovoltaic cluster characteristics and the early warning and traceability of power quality disturbances.

[0095] In an alternative embodiment, the preset threshold is dynamically changed by statistically analyzing historical data within a preset time period.

[0096] In a specific embodiment, based on the voltage quality adaptive perception process of statistical process control, the threshold for judging the change of the monitoring mode is dynamically and continuously updated through statistical learning of recent historical data, so as to accurately perceive voltage problems.

[0097] In this embodiment, a distributed photovoltaic substation power quality monitoring device is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated here. As used hereinafter, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0098] This embodiment provides a distributed photovoltaic substation power quality monitoring device, as Figure 4 shown, including:

[0099] An acquisition module 41, configured to periodically acquire monitoring indicators of the power quality of a distributed photovoltaic substation;

[0100] A comparison module 42, configured to compare the monitoring indicators with a preset threshold;

[0101] A switching module 43, configured to dynamically switch the power quality monitoring mode according to the comparison result.

[0102] In some alternative embodiments, the switching module 43 includes:

[0103] A first switching unit 431, configured to switch the power quality monitoring mode to the in-depth perception mode when the monitoring indicator exceeds the preset threshold;

[0104] A second switching unit 432, configured to switch the power quality monitoring mode to the lightweight perception mode when the monitoring indicator does not exceed the preset threshold.

[0105] The further function descriptions of the above-mentioned modules and units are the same as those in the corresponding embodiments above, and will not be repeated here.

[0106] The distributed photovoltaic substation power quality monitoring device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0107] This embodiment of the present invention further provides a computer device having the aboveFigure 5 The distributed photovoltaic substation power quality monitoring device shown in the figure.

[0108] Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of a computer device provided by an optional embodiment of the present invention. As Figure 5 shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 5 In

[0109]

[0110]

[0111]

[0112] Here, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0112] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, a hard disk, or a solid state drive; the memory 20 may further include a combination of the above types of memory.

[0113] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0114] An embodiment of the present invention further provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented by downloading through a network the original computer code stored in a remote storage medium or a non-transitory machine-readable storage medium and to be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state drive, etc.; further, the storage medium can also include a combination of the above types of memory. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiment is implemented.

[0115] Although the embodiments of the present invention are described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for monitoring the power quality of a distributed photovoltaic substation area, characterized in that, the method includes: periodically collecting monitoring indicators of the power quality of the distributed photovoltaic substation area; comparing the monitoring indicators with a preset threshold; dynamically switching the power quality monitoring mode according to the comparison result.

2. The method for monitoring the power quality of the distributed photovoltaic substation area according to claim 1, characterized in that, the dynamically switching the power quality monitoring mode according to the comparison result includes: when the monitoring indicator exceeds the preset threshold, switching the power quality monitoring mode to the deep perception mode; when the monitoring indicator does not exceed the preset threshold, switching the power quality monitoring mode to the lightweight perception mode.

3. The method for monitoring the power quality of the distributed photovoltaic substation area according to claim 2, characterized in that, the data granularity in the deep perception mode is minute-level / recording wave, the monitoring indicators are multi-dimensional indicators, and the cause analysis function of power quality problems is enabled.

4. The method for monitoring the power quality of the distributed photovoltaic substation area according to claim 2, characterized in that, the data granularity in the lightweight perception mode is daily statistical value, the monitoring indicators are basic indicators, and the cause analysis function of power quality problems is stopped.

5. The method for monitoring the power quality of the distributed photovoltaic substation area according to claim 1, characterized in that, when the power quality of the distributed photovoltaic substation area is steady-state power quality, the monitoring indicators include: voltage over-limit rate, equivalent power factor over-limit rate, harmonic pollution coefficient and unbalance coefficient; when the power quality of the distributed photovoltaic substation area is transient power quality, the monitoring indicator includes: voltage sag energy.

6. The method for monitoring the power quality of the distributed photovoltaic substation area according to claim 1, characterized in that, dynamically changing the preset threshold by statistically analyzing historical data within a preset time.

7. A device for monitoring the power quality of a distributed photovoltaic substation area, characterized in that, the device includes: a collection module for periodically collecting monitoring indicators of the power quality of the distributed photovoltaic substation area; a comparison module for comparing the monitoring indicators with a preset threshold; a switching module for dynamically switching the power quality monitoring mode according to the comparison result.

8. The device for monitoring the power quality of the distributed photovoltaic substation area according to claim 7, characterized in that, the switching module includes a first switching unit and a second switching unit, wherein, the first switching unit is used to switch the power quality monitoring mode to the deep perception mode when the monitoring indicator exceeds the preset threshold; the second switching unit is used to switch the power quality monitoring mode to the lightweight perception mode when the monitoring indicator does not exceed the preset threshold.

9. A computer device, characterized in that, including: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the method for monitoring the power quality of the distributed photovoltaic substation area according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the distributed photovoltaic substation power quality monitoring method according to any one of claims 1 to 6.

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