CN116304635A - Operation data analysis method, device and equipment of pumped storage equipment - Google Patents
Operation data analysis method, device and equipment of pumped storage equipment Download PDFInfo
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Abstract
The invention discloses an operation data analysis method, a device and equipment of pumped storage equipment, comprising the following steps: acquiring a plurality of characteristic quantity data generated by the pumped storage equipment in the running process, preprocessing the characteristic quantity data, determining a characteristic quantity curve corresponding to the pumped storage equipment according to the preprocessed characteristic quantity data, and determining the stability corresponding to the characteristic quantity curve according to the stability corresponding to the characteristic quantity curve if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, and determining the characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve. The technical scheme of the embodiment of the invention can improve the accuracy of the analysis result of the operation data of the pumped storage equipment.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for analyzing operation data of a pumped storage device.
Background
The pumped storage equipment is in charge of peak regulation and valley filling, frequency modulation, phase modulation, emergency standby, black start and system capacity standby in a power grid. In use, the pumped storage device may have abnormal operation, and in order to avoid damage to other devices in the power grid, it is important to analyze the operation data of the pumped storage device.
In the prior art, when the operation data of the pumped storage equipment is analyzed, only the characteristic quantity data corresponding to the pumped storage equipment is generally judged, whether the characteristic quantity data meets a preset data range or not is judged, and if yes, the current characteristic quantity data of the pumped storage equipment is considered to be free from danger.
However, in the prior art, the degree of change of the feature quantity data cannot be judged, and if some feature quantity data is too severely changed, the risk of breaking through the upper limit and the lower limit of the data exists; second, the upper and lower limits of the data range in the prior art are determined by only a single data, which results in a larger error of the data analysis result.
Disclosure of Invention
The invention provides a method, a device and equipment for analyzing operation data of pumped storage equipment, which can improve the accuracy of the analysis result of the operation data of the pumped storage equipment.
According to an aspect of the present invention, there is provided a method of analyzing operational data of a pumped-storage device, the method comprising:
acquiring a plurality of characteristic quantity data generated in the operation process of the pumped storage equipment, preprocessing the plurality of characteristic quantity data, and determining a characteristic quantity curve corresponding to the pumped storage equipment according to the preprocessed plurality of characteristic quantity data;
if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data;
and determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
According to another aspect of the present invention there is provided an operation data analysis device for a pumped-storage facility, the device comprising:
the data acquisition module is used for acquiring a plurality of characteristic quantity data generated in the operation process of the pumped storage equipment, preprocessing the plurality of characteristic quantity data, and determining a characteristic quantity curve corresponding to the pumped storage equipment according to the preprocessed plurality of characteristic quantity data;
the stability determining module is used for determining the stability corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range;
and the data analysis module is used for determining the characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of analyzing operational data of the pumped-hydro energy storage device of any of the embodiments of the present invention.
According to another aspect of the present invention there is provided a computer readable storage medium storing computer instructions for causing a processor to perform a method of analyzing operational data of a pumped-storage device according to any of the embodiments of the present invention.
According to the technical scheme provided by the embodiment of the invention, the characteristic quantity data generated in the operation process of the pumped storage equipment are obtained, the characteristic quantity data are preprocessed, and the characteristic quantity curve corresponding to the pumped storage equipment is determined according to the preprocessed characteristic quantity data; if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to a plurality of characteristic quantity data; according to the stability corresponding to the characteristic quantity curve, the technical means of determining the characteristic quantity data analysis result corresponding to the pumped storage equipment can improve the accuracy of the operation data analysis result of the pumped storage equipment.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method of analyzing operational data of a pumped-storage device according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method of analyzing operational data of a pumped-storage device provided in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of another method of analyzing operational data of a pumped-storage device provided in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of an operation data analysis device of a pumped-storage device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device implementing a method for analyzing operation data of a pumped-storage device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a flowchart of a method for analyzing operation data of a pumped-storage device according to a first embodiment of the present invention, where the method may be performed by an operation data analysis device of the pumped-storage device, and the operation data analysis device of the pumped-storage device may be implemented in hardware and/or software, and the operation data analysis device of the pumped-storage device may be configured in an electronic device (for example, a terminal or a server) having a data processing function. As shown in fig. 1, the method includes:
In this step, a plurality of feature quantity data corresponding to the pumped storage device at a plurality of different moments in the running process of the pumped storage device may be obtained, the plurality of feature quantity data may be preprocessed (for example, denoising, normalization, etc. on the data), and then a feature quantity curve corresponding to the pumped storage device may be determined according to the preprocessed plurality of feature quantity data.
And 120, if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data.
In this embodiment, after determining a characteristic quantity curve corresponding to the pumped storage device, a maximum value and a minimum value corresponding to the characteristic quantity curve may be obtained, the maximum value is compared with an upper limit value of a preset interval, the minimum value is compared with a lower limit value of the preset interval, and if the maximum value and the minimum value corresponding to the characteristic quantity curve satisfy the preset interval and an average value corresponding to the characteristic quantity curve is located in a preset range, stability corresponding to the characteristic quantity curve is determined according to a plurality of characteristic quantity data.
In a specific embodiment, optionally, according to a difference value between the feature quantity data, a change intensity degree corresponding to the feature quantity curve may be determined, whether the feature quantity curve has a trend of breaking through an upper limit and a lower limit of a preset interval or not is judged according to the change intensity degree, and finally, a determination result and the change intensity degree are combined to determine a stability degree corresponding to the feature quantity curve.
And 130, determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
In this embodiment, optionally, after determining the stationarity corresponding to the characteristic quantity curve, if the stationarity is higher, it may be determined that the analysis result of the characteristic quantity data is normal, that is, the running data of the pumped storage device does not have a risk of breaking through the upper and lower limits of the interval; otherwise, if the stability is lower, the characteristic quantity data analysis result can be determined to be abnormal, namely the running data of the pumped storage equipment is changed severely, and the danger of breaking through the upper limit and the lower limit of the interval exists.
According to the technical scheme provided by the embodiment of the invention, the characteristic quantity data generated in the operation process of the pumped storage equipment are obtained, the characteristic quantity data are preprocessed, and the characteristic quantity curve corresponding to the pumped storage equipment is determined according to the preprocessed characteristic quantity data; if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to a plurality of characteristic quantity data; according to the stability corresponding to the characteristic quantity curve, the technical means of determining the characteristic quantity data analysis result corresponding to the pumped storage equipment can improve the accuracy of the operation data analysis result of the pumped storage equipment.
Fig. 2 is a flowchart of a method for analyzing operation data of a pumped-storage device according to a second embodiment of the present invention, where the embodiment is further refined from the foregoing embodiment. As shown in fig. 2, the method includes:
In one implementation of the present embodiment, preprocessing the plurality of feature quantity data includes: screening abnormal characteristic quantity data from the plurality of characteristic quantity data, and eliminating the abnormal characteristic quantity data; and if the plurality of feature quantity data comprise the vacancy values, carrying out supplement processing on the vacancy values.
In this embodiment, screening the abnormal feature quantity data among the plurality of feature quantity data includes: dividing the characteristic quantity data into a plurality of data sets according to corresponding acquisition moments; and acquiring the corresponding maximum value of each data set, and screening abnormal characteristic quantity data from the plurality of characteristic quantity data according to the quantity of the maximum values in the corresponding data set and the adjacent data sets and the difference value between the maximum value and the next maximum value in the corresponding data set.
In a specific embodiment, optionally, the plurality of feature data may be divided into a plurality of data sets according to a preset duration and the collection time corresponding to each feature data, and then a maximum value and a minimum value corresponding to each data set are obtained. If the number of the maximum value (maximum value or minimum value) in a certain data group in the present data group and the adjacent data group is smaller than a preset number threshold value, and the difference between the maximum value and the next maximum value in the present data group is larger than the range of a preset multiple (i.e., the difference between the maximum value and the minimum value), the maximum value may be regarded as the abnormal feature amount data.
Optionally, the preset number threshold may be 3, the preset multiple may be 1/10, and the specific value may be adjusted according to the actual situation, which is not limited in this embodiment.
In another implementation manner of this embodiment, when the blank value is subjected to the supplementing process, a plurality of feature quantity data adjacent to the blank value about the blank value may be selected as the reference value, a fitting curve is generated according to the plurality of reference values, and finally the blank value is supplemented according to the fitting curve.
And 220, if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval, and the average value corresponding to the characteristic quantity curve is in a preset range, acquiring the average value corresponding to the characteristic quantity data and the trend line slope corresponding to the characteristic quantity curve.
In this step, optionally, a trend line corresponding to the characteristic quantity curve may be obtained by fitting according to a peak point in the characteristic quantity curve, and a slope of the trend line may be calculated.
In this embodiment, the preset average value may be a specific numerical range, for example [ mu ] a ，μ b ]. In this step, the difference between the average value and the maximum value and the minimum value in the numerical interval may be calculated, respectively, and the product of the difference and the slope may be calculated.
In a specific embodiment, if the product is greater than a preset threshold value within a preset time period, the characteristic curve may be considered as a dangerous curve; conversely, if the product is less than or equal to the preset threshold value within the preset time period, the characteristic amount curve may be regarded as a safety curve.
And 240, if the characteristic quantity curve is a safety curve, determining the smoothness corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data.
And 250, determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
According to the technical scheme provided by the embodiment of the invention, the characteristic quantity data corresponding to the pumped storage equipment are preprocessed by acquiring the characteristic quantity data generated in the operation process of the pumped storage equipment, the characteristic quantity curve corresponding to the pumped storage equipment is determined according to the preprocessed characteristic quantity data, if the maximum value and the minimum value corresponding to the characteristic quantity curve meet the preset interval and the average value corresponding to the characteristic quantity curve is in the preset range, the average value corresponding to the characteristic quantity data and the slope corresponding to the characteristic quantity curve are acquired, the difference between the average value and the preset average value are determined, whether the characteristic quantity curve is a safety curve or not is judged according to the product of the difference and the slope, if yes, the stability corresponding to the characteristic quantity curve is determined according to the characteristic quantity data, and the characteristic quantity data analysis result corresponding to the pumped storage equipment is determined according to the stability corresponding to the characteristic quantity curve.
Fig. 3 is a flowchart of a method for analyzing operation data of a pumped-storage device according to a third embodiment of the present invention, where the embodiment is further refined from the foregoing embodiments. As shown in fig. 3, the method includes:
In the present embodiment, a plurality of feature quantity data located above the average value in the feature quantity curve may be acquired, and the upper average value may be calculated from the plurality of feature quantity data. Similarly, a plurality of feature quantity data lying below the average value in the feature quantity curve may also be acquired, and the lower average value may be calculated from the plurality of feature quantity data.
In this step, optionally, the duty ratio of each feature quantity data in all feature quantity data may be calculated, and according to the result of calculating the duty ratio corresponding to each feature quantity data, a distribution curve corresponding to the pumped storage device is drawn, and according to the distribution curve, the dispersion corresponding to the feature quantity curve is determined. In particular, if the peak of the distribution curve is higher, the more data modes of the group are represented, the more data are concentrated, and the lower the dispersion.
In one implementation manner of the present embodiment, determining, according to the plurality of feature quantity data, a dispersion corresponding to the feature quantity curve includes: determining a difference between each of the feature quantity data and the average value; and determining the dispersion corresponding to the characteristic quantity curve according to the difference values and preset weights corresponding to the characteristic quantity data.
In a specific embodiment, it is assumed that the pumped-storage device generates n characteristic data T during operation i ，i∈[l，n]Then the average value mu corresponding to the n feature quantity data can be calculated i ：
Then dividing the characteristic data into a plurality of data groups according to a preset number (10 is assumed), and calculating the corresponding dispersion D of each data group by the following formula i ：
The specific value of the preset weight may be 1/10, and the specific value may be adjusted according to the actual situation, which is not limited in this embodiment.
In the present embodiment, the respective dispersions (D 1 、D 2 、D 3 ……D n ) After that, the plurality of dispersions may be weighted and summed according to the corresponding weights to obtain a dispersion D corresponding to the characteristic curve, as shown in the following formula:
D＝D 1 *w 1 +D 2 *w 2 +D 3 *w 3 +…+D n *w n
the influence of the data at the later stage of the pumped storage equipment on the current change of the curve is relatively small, so that the preset weight corresponding to each characteristic quantity data in the characteristic quantity curve is gradually increased.
In a specific embodiment, the preset weights w corresponding to the data sets i May be equidifferent or equi-proportionally varied. For example: w (w) n ＝w n-1 +d, or w n ＝αw n-1 . Wherein d and a are constants, w 1 +w 2 +…+w n ＝1。
In this embodiment, the dispersion may be used to represent the degree of dispersion of the pumped-storage device characteristic data relative to the average of the characteristic data.
And 330, determining a distance threshold corresponding to the characteristic quantity curve according to the distances between the average value corresponding to the characteristic quantity data and the upper average value and the lower average value respectively.
In this embodiment, the distance threshold may be used to reflect the degree of variation of the characteristic amount curve.
In a specific embodiment, a plurality of feature quantity numbers are assumedAccording to the corresponding average value u i The upper mean value corresponding to the characteristic quantity curve is u + Lower mean value u - The distance threshold delta corresponding to the characteristic quantity curve can be calculated by the following formula:
and 340, determining the smoothness corresponding to the characteristic quantity curve according to the dispersion and the distance threshold corresponding to the characteristic quantity curve.
In this step, optionally, linear or nonlinear processing may be performed on the dispersion and the distance threshold corresponding to the characteristic quantity curve, to obtain the smoothness corresponding to the characteristic quantity curve.
In one implementation manner of this embodiment, determining the smoothness corresponding to the feature quantity curve according to the dispersion and the distance threshold corresponding to the feature quantity curve includes: and weighting and summing the dispersion corresponding to the characteristic quantity curve and the distance threshold according to the target weights respectively corresponding to the dispersion and the distance threshold to obtain the stationarity corresponding to the characteristic quantity curve.
In a specific embodiment, assuming that the target weight corresponding to the dispersion D is α and the target weight corresponding to the distance threshold Δ is b, the stationarity Σ corresponding to the characteristic curve may be calculated by the following formula j ：
∑ j ＝αD+bΔ
Wherein α+b=1, alternatively, a and b may be both 0.5, and specific values may be preset according to practical situations, which is not limited in this embodiment.
And 350, comparing the smoothness corresponding to the characteristic quantity curve with a preset smoothness threshold.
And 360, determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the comparison result.
In this embodiment, optionally, if the smoothness corresponding to the feature quantity curve is greater than or equal to a preset smoothness threshold, it may be determined that the feature quantity data analysis result is normal; otherwise, if the smoothness corresponding to the characteristic quantity curve is smaller than the preset smoothness threshold, the characteristic quantity data analysis result can be determined to be abnormal.
The advantage of this arrangement is that the feature quantity data analysis result can be intuitively determined from the data comparison result. Specifically, the stability threshold may be determined based on the material of the pumped-storage device and the environment in which it is located.
On the basis of the above embodiment, after determining the stationarity A corresponding to the characteristic curve, the stationarity A and the average value mu corresponding to the characteristic curve may be also determined i Preset mean [ mu ] a ，μ b ]Calculating the safety value corresponding to the characteristic quantity curve by the following formula
According to the technical scheme provided by the embodiment of the invention, the characteristic quantity data corresponding to the pumped storage equipment are preprocessed by acquiring the characteristic quantity data generated in the operation process of the pumped storage equipment, the characteristic quantity curves corresponding to the pumped storage equipment are determined according to the preprocessed characteristic quantity data, and if the maximum value and the minimum value corresponding to the characteristic quantity curves meet a preset interval and the average value is in a preset range, the dispersion degree, the upper average value and the lower average value corresponding to the characteristic quantity curves are determined according to the characteristic quantity data, the distance threshold corresponding to the characteristic quantity curves is determined, the stability corresponding to the characteristic quantity curves is determined according to the dispersion degree and the distance threshold corresponding to the characteristic quantity curves, the stability corresponding to the characteristic quantity curves is compared with a preset stability threshold, and the characteristic quantity data analysis result corresponding to the pumped storage equipment is determined according to the comparison result.
Fig. 4 is a schematic structural diagram of an operation data analysis device of a pumped-storage device according to a fourth embodiment of the present invention, as shown in fig. 4, where the device includes: a data acquisition module 410, a stationarity determination module 420, and a data analysis module 430.
The data acquisition module 410 is configured to acquire a plurality of feature quantity data generated during an operation process of the pumped storage device, perform preprocessing on the plurality of feature quantity data, and determine a feature quantity curve corresponding to the pumped storage device according to the preprocessed plurality of feature quantity data;
the stationarity determining module 420 is configured to determine, according to the plurality of feature data, a stationarity corresponding to the feature curve if a maximum value and a minimum value corresponding to the feature curve satisfy a preset interval and an average value corresponding to the feature curve is within a preset range;
and the data analysis module 430 is configured to determine a feature quantity data analysis result corresponding to the pumped storage device according to the smoothness corresponding to the feature quantity curve.
According to the technical scheme provided by the embodiment of the invention, the characteristic quantity data generated in the operation process of the pumped storage equipment are obtained, the characteristic quantity data are preprocessed, and the characteristic quantity curve corresponding to the pumped storage equipment is determined according to the preprocessed characteristic quantity data; if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to a plurality of characteristic quantity data; according to the stability corresponding to the characteristic quantity curve, the technical means of determining the characteristic quantity data analysis result corresponding to the pumped storage equipment can improve the accuracy of the operation data analysis result of the pumped storage equipment.
On the basis of the above embodiment, the data acquisition module 410 includes:
an abnormal data removing unit, configured to screen abnormal feature data from the plurality of feature data, and remove the abnormal feature data;
a blank value supplementing unit, configured to supplement a blank value if the plurality of feature quantity data includes the blank value;
the data set dividing unit is used for dividing the characteristic quantity data into a plurality of data sets according to the corresponding acquisition time;
the abnormal data screening unit is used for acquiring the corresponding maximum value of each data set, and screening abnormal characteristic data from the plurality of characteristic data according to the quantity of the maximum values in the corresponding data set and the adjacent data sets and the difference value between the maximum value and the next maximum value in the corresponding data set.
The stationarity determination module 420 includes:
the slope obtaining unit is used for obtaining average values corresponding to the characteristic quantity data and trend line slopes corresponding to the characteristic quantity curves;
the curve judging unit is used for determining a difference value between the average value and a preset average value and judging whether the characteristic quantity curve is a safety curve according to the product of the difference value and the slope; if yes, determining the stability corresponding to the characteristic quantity curve according to the characteristic quantity data;
the dispersion determining unit is used for determining the dispersion, the upper mean value and the lower mean value corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data;
a distance threshold determining unit, configured to determine a distance threshold corresponding to the feature quantity curve according to the distances between the average values corresponding to the feature quantity data and the upper average value and the lower average value, respectively;
the stability obtaining unit is used for determining the stability corresponding to the characteristic quantity curve according to the dispersion corresponding to the characteristic quantity curve and the distance threshold value;
a difference determining unit configured to determine a difference between each of the feature quantity data and the average value;
and the difference processing unit is used for determining the dispersion corresponding to the characteristic quantity curve according to the difference values and the preset weights corresponding to the characteristic quantity data.
The data analysis module 430 includes:
the stability comparison unit is used for comparing the stability corresponding to the characteristic quantity curve with a preset stability threshold;
and the analysis result determining unit is used for determining the characteristic quantity data analysis result corresponding to the pumped storage equipment according to the comparison result.
The device can execute the method provided by all the embodiments of the invention, and has the corresponding functional modules and beneficial effects of executing the method. Technical details not described in detail in the embodiments of the present invention can be found in the methods provided in all the foregoing embodiments of the present invention.
Fig. 5 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the method of analyzing operational data of the pumped-storage device.
In some embodiments, the method of analyzing operational data of the pumped-hydro energy storage device may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method of analyzing operational data of the pumped-hydro energy storage device described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the operational data analysis method of the pumped-storage device in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of analyzing operational data of a pumped-storage device, the method comprising:
acquiring a plurality of characteristic quantity data generated in the operation process of the pumped storage equipment, preprocessing the plurality of characteristic quantity data, and determining a characteristic quantity curve corresponding to the pumped storage equipment according to the preprocessed plurality of characteristic quantity data;
if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range, determining the stability corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data;
and determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
2. The method according to claim 1, wherein preprocessing the plurality of feature quantity data includes:
screening abnormal characteristic quantity data from the plurality of characteristic quantity data, and eliminating the abnormal characteristic quantity data;
and if the plurality of feature quantity data comprise the vacancy values, carrying out supplement processing on the vacancy values.
3. The method according to claim 2, wherein screening abnormal feature quantity data among the plurality of feature quantity data includes:
dividing the characteristic quantity data into a plurality of data sets according to corresponding acquisition moments;
and acquiring the corresponding maximum value of each data set, and screening abnormal characteristic quantity data from the plurality of characteristic quantity data according to the quantity of the maximum values in the corresponding data set and the adjacent data sets and the difference value between the maximum value and the next maximum value in the corresponding data set.
4. The method according to claim 1, wherein determining the smoothness corresponding to the characteristic curve from the plurality of characteristic data includes:
acquiring an average value corresponding to the characteristic quantity data and a trend line slope corresponding to a characteristic quantity curve;
determining a difference value between the average value and a preset average value, and judging whether the characteristic quantity curve is a safety curve according to the product of the difference value and the slope;
if yes, determining the stability corresponding to the characteristic quantity curve according to the characteristic quantity data.
5. The method according to claim 1, wherein determining the smoothness corresponding to the characteristic curve from the plurality of characteristic data includes:
determining corresponding dispersion, upper mean value and lower mean value of the characteristic quantity curves according to the characteristic quantity data;
according to the average value corresponding to the characteristic quantity data, determining a distance threshold value corresponding to the characteristic quantity curve according to the distances between the average value corresponding to the characteristic quantity data and the upper average value and the lower average value respectively;
and determining the smoothness corresponding to the characteristic quantity curve according to the dispersion and the distance threshold corresponding to the characteristic quantity curve.
6. The method of claim 5, wherein determining the corresponding dispersion of the feature curve from the plurality of feature data comprises:
determining a difference between each of the feature quantity data and the average value;
and determining the dispersion corresponding to the characteristic quantity curve according to the difference values and preset weights corresponding to the characteristic quantity data.
7. The method according to claim 1, wherein determining a feature data analysis result corresponding to the pumped-storage device according to the smoothness corresponding to the feature curve includes:
comparing the stability corresponding to the characteristic quantity curve with a preset stability threshold;
and determining a characteristic quantity data analysis result corresponding to the pumped storage equipment according to the comparison result.
8. An operational data analysis device for a pumped-storage facility, the device comprising:
the data acquisition module is used for acquiring a plurality of characteristic quantity data generated in the operation process of the pumped storage equipment, preprocessing the plurality of characteristic quantity data, and determining a characteristic quantity curve corresponding to the pumped storage equipment according to the preprocessed plurality of characteristic quantity data;
the stability determining module is used for determining the stability corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data if the maximum value and the minimum value corresponding to the characteristic quantity curve meet a preset interval and the average value corresponding to the characteristic quantity curve is in a preset range;
and the data analysis module is used for determining the characteristic quantity data analysis result corresponding to the pumped storage equipment according to the stability corresponding to the characteristic quantity curve.
9. The apparatus of claim 8, wherein the stationarity determination module comprises:
the dispersion determining unit is used for determining the dispersion, the upper mean value and the lower mean value corresponding to the characteristic quantity curve according to the plurality of characteristic quantity data;
a distance threshold determining unit, configured to determine a distance threshold corresponding to the feature quantity curve according to distances between average values corresponding to the feature quantity data and an upper average value and a lower average value respectively;
and the stability acquisition unit is used for determining the stability corresponding to the characteristic quantity curve according to the dispersion and the distance threshold corresponding to the characteristic quantity curve.
10. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of analyzing operational data of the pumped-storage device of any one of claims 1-7.
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| CN202310288524.4A CN116304635A (en) | 2023-03-21 | 2023-03-21 | Operation data analysis method, device and equipment of pumped storage equipment |
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| CN202310288524.4A CN116304635A (en) | 2023-03-21 | 2023-03-21 | Operation data analysis method, device and equipment of pumped storage equipment |
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