Power plant energy consumption data online monitoring system and method based on big data analysis

Abstract

The invention provides a power plant energy consumption data on-line monitoring system and method based on big data analysis. The on-line monitoring system comprises an energy consumption data on-line detection module used for obtaining a sensor installed in energy consumption equipment to realize on-line monitoring of power plant energy consumption data; the energy consumption data packet generation and transmission module is used for transmitting the online monitoring energy consumption packet to the energy consumption analysis data platform; and the abnormal data segment acquisition module is used for outputting a result for the energy consumption data after the energy consumption analysis data platform receives the online monitoring energy consumption packet. According to the method, the monitored data flow is drawn into the triaxial curve, so that the risk abnormal condition is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, in particular to an online monitoring system and method for power plant energy consumption data based on big data analysis. BACKGROUND

[0002] With the increasing demand for electricity, transformers, as an important device for power transmission and distribution, must be operated efficiently and stably to ensure the normal operation of the power system. In this context, the development of transformer energy consumption monitoring systems has emerged. It can collect real-time operation parameters of transformers, automatically calculate energy efficiency indicators, and monitor the health of equipment by integrating sensors, data acquisition, analysis and processing, and cloud monitoring technologies. Patent application number 201210332307.2, entitled "A remote monitoring method for electric energy consumption data", discloses the following steps: collecting voltage and current signal data, converting them into a set of data table fields by a single-chip microcomputer processing device, and sending the data to a storage module and / or through an RS232 communication interface to a transmission module; data transmission sends data to a data forwarding device; the data forwarding device transmits to the cloud storage and cloud server of the background through the Internet of Things, and the cloud server analyzes, manages and / or issues control instructions according to the received control commands. This invention sends voltage and current signal data in the energy consumption in the form of data table fields for final analysis and management, which is not conducive to the overall security risk of the data. SUMMARY

[0003] The present application aims to at least solve the technical problems existing in the prior art, and particularly innovatively proposes an online monitoring system and method for power plant energy consumption data based on big data analysis.

[0004] In order to achieve the above-mentioned purpose of the present application, the present application provides an online monitoring system for power plant energy consumption data based on big data analysis, which comprises an energy consumption data online detection module, an energy consumption data packet generation and transmission module, and an abnormal data segment acquisition module.

[0005] The energy consumption data online detection module is used to acquire sensors installed in energy consumption equipment to realize online monitoring of power plant energy consumption data.

[0006] The energy consumption data packet generation and transmission module is used to transmit the online monitoring energy consumption packet to the energy consumption analysis data platform.

[0007] The abnormal data segment acquisition module is used for the energy consumption analysis data platform to receive the online monitoring energy consumption packet and output the energy consumption data.

[0008] In a preferred embodiment of the present application, the energy consumption data online detection module comprises:

[0009] The sensors installed in the energy-consuming equipment are voltage sensors and current sensors;

[0010] Voltage sensors are used to monitor the operating voltage of energy-consuming equipment online. ;

[0011] Current sensors are used to monitor the operating current value of energy-consuming equipment online. .

[0012] In a preferred embodiment of the present invention, the energy consumption data packet generation and transmission module includes:

[0013] S21, build the XYZ three-axis coordinate system:

[0014] Among them, the X-axis represents time, the Y-axis represents voltage, and the Z-axis represents current;

[0015] S22, the moment Operating voltage value and current value Draw it into the coordinate system and convert the time Operating voltage value and current value After drawing into the coordinate system, connect the drawing points on the surface where the XY axis is located to form - The time voltage curve is formed by connecting the plot points on the surface where the XZ axis is located. - The time-current curve is formed by connecting the plot points on the YZ axis surface - Voltage-current curve;

[0016] S23, after the curve is generated, an online monitoring image in JPEG or PNG format is generated;

[0017] S24, performing obfuscation transformation on the online monitoring image to generate an online monitoring obfuscated image;

[0018] S25, compressing the online monitoring confusion image to obtain an online monitoring energy consumption package.

[0019] In a preferred embodiment of the present invention, step S24 includes:

[0020] S241, swap positions, swap the pixel values ​​in the image in the following manner:

[0021] like ,but That is, at the pixel point No. The place value and Interchange of place values;

[0022] If , then is the value of the first bit of the pixel point ; is not interchanged with the value of the second bit of the pixel point ;

[0023] represents the value of the first bit of the pixel point in the online monitoring picture;

[0024] represents the value of the second bit of the pixel point in the online monitoring picture;

[0025] represents the number of horizontal pixel points of the picture;

[0026] represents the number of vertical pixel points of the picture;

[0027] represents the number of bits of the pixel value of the picture;

[0028] represents the division number;

[0029] represents the floor function;

[0030] represents the constraint condition;

[0031] represents the interchanging symbol;

[0032] S242, value transformation, the pixel value in the picture is transformed according to the following manner:

[0033] If , then is the value of the first bit of the pixel point ;

[0034] If , then is the value of the second bit of the pixel point ;

[0035] represents the value of the first bit of the pixel point in the online monitoring picture;

[0036] ​​​​​​represents the pixel value of the online monitoring picture at the pixel point ;

[0037] represents the number of horizontal pixels of the picture ;

[0038] represents the number of vertical pixels of the picture ;

[0039] represents the pixel value bit number of the picture ;

[0040] represents the horizontal division number ;

[0041] represents the vertical division number ;

[0042] represents the down rounding

[0043] represents the constraint condition

[0044] In a preferred embodiment of the present application, the abnormal data segment acquisition module comprises:

[0045] S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring picture

[0046] S32, the online platform monitoring picture is subjected to confusion inverse transformation to generate a normal monitoring picture

[0047] S33, voltage values and current values at all moments are extracted from the curve in the normal picture real-time energy consumption is obtained according to the extracted voltage values

[0048] ,

[0049] wherein, represents the real-time energy consumption of the energy consumption equipment at the moment ;

[0050] represents the running voltage value of the energy consumption equipment at the moment ;

[0051] represents the running current value of the energy consumption equipment at the moment ;

[0052] Forming energy consumption sequence according to time sequence of real-time energy consumption ;

[0053] S34, judging abnormal points in the sequence of energy consumption:

[0054] If , it is judged as energy consumption preliminary abnormal section;

[0055] That is The absolute difference between and is greater than , and is recorded as , otherwise ;

[0056] Indicates that the energy consumption is abnormal, Indicates that the energy consumption is normal;

[0057] Indicates the energy consumption abnormal setting value; , ;

[0058] Indicates the sequence interval;

[0059] Further judge the energy consumption equipment state in the abnormal time period:

[0060] If it is in shutdown state, the energy consumption equipment is not abnormal;

[0061] If it is in running state, the energy consumption equipment is abnormal.

[0062] The application also discloses an online monitoring method for power plant energy consumption data based on big data analysis, which comprises the following steps:

[0063] S1, obtaining the sensor arranged in the energy consumption equipment to realize online monitoring of the power plant energy consumption data;

[0064] S2, transmitting the online monitoring energy consumption package to the energy consumption analysis data platform;

[0065] S3, after the energy consumption analysis data platform receives the online monitoring energy consumption package, outputting the results according to the energy consumption data.

[0066] In a preferred embodiment of the application, step S1 comprises:

[0067] The sensor arranged in the energy consumption equipment is a voltage sensor and a current sensor;

[0068] The voltage sensor is used for online monitoring the running voltage value of the energy consumption equipment in the working state ;

[0069] Current sensor is used for monitoring the running current value of energy consumption equipment in working state .

[0070] In a preferred embodiment of the present application, step S2 comprises:

[0071] S21, constructing X-Y-Z three-axis coordinate system:

[0072] Wherein, X axis represents time, Y axis represents voltage, and Z axis represents current;

[0073] S22, drawing the running voltage value and current value at time to the coordinate system, drawing the running voltage value and current value at time to the coordinate system, connecting the drawing points on the XY plane to form - time-voltage curve, connecting the drawing points on the XZ plane to form - time-current curve, and connecting the drawing points on the YZ plane to form - voltage-current curve;

[0074] S23, after the curve is generated, generating online monitoring picture in JPEG or PNG format;

[0075] S24, performing confusion transformation on the online monitoring picture to generate online monitoring confusion picture;

[0076] S25, obtaining online monitoring energy consumption package after compressing the online monitoring confusion picture.

[0077] In a preferred embodiment of the present application, step S24 comprises:

[0078] S241, position transposition, interchanging the pixel values in the picture according to the following manner:

[0079] If , the value at the first position and the value at the second position of the pixel point are interchanged; If , the value at the first position and the value at the second position of the pixel point are not interchanged;

[0080] ​​​​​​

[0081] represents the value of the first bit of the pixel point in the online monitoring picture;

[0082] represents the value of the first bit of the pixel point in the online monitoring picture;

[0083] represents the number of horizontal pixel points of the picture;

[0084] represents the number of vertical pixel points of the picture;

[0085] represents the number of bits of the pixel value of the picture;

[0086] represents the division number;

[0087] represents the floor;

[0088] represents the constraint condition;

[0089] represents the exchange symbol;

[0090] S242, value transformation, the pixel value in the picture is transformed in the following manner:

[0091] if , then the value of the first bit of the pixel point is 0;

[0092] if , then the value of the first bit of the pixel point is 1;

[0093] represents the value of the first bit of the pixel point in the online monitoring picture;

[0094] represents the value of the first bit of the pixel point in the online monitoring picture;

[0095] represents the number of horizontal pixel points of the picture;

[0096] ​​​​​​​ represents the number of vertical pixels of the picture;

[0097] represents the number of bits of the pixel value of the picture;

[0098] represents the number of horizontal divisions;

[0099] represents the number of vertical divisions;

[0100] represents the floor function;

[0101] represents the constraint condition.

[0102] In a preferred embodiment of the present application, step S3 comprises:

[0103] S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring picture;

[0104] S32, the online platform monitoring picture is subjected to confusion inverse transformation to generate a normal monitoring picture;

[0105] S33, voltage values at all time points and current values at all time points are extracted from the curve in the normal picture , real-time energy consumption is obtained according to the extracted voltage values at all time points and current values at all time points

[0106] ,

[0107] wherein, represents the real-time energy consumption of the energy consumption device at time point t;

[0108] represents the running voltage value of the energy consumption device at time point t; represents the running current value of the energy consumption device at time point t;

[0109] the real-time energy consumption is arranged in chronological order to form an energy consumption sequence

[0110]

[0111] S34, abnormal point judgment is performed on the energy consumption in the sequence:

[0112] if , it is judged as an energy consumption preliminary abnormal section;​​​​​​​​​

[0113] i.e. with an absolute difference greater than , recorded as , and vice versa ;

[0114] indicates that the energy consumption is abnormal, indicates that the energy consumption is normal;

[0115] indicates the energy consumption abnormality setting value; , ;

[0116] indicates the sequence interval;

[0117] Further determine the energy consumption device state in the abnormal time period:

[0118] If in the shutdown state, the energy consumption device is not abnormal;

[0119] If in the running state, the energy consumption device is abnormal.

[0120] As described above, by using the above technical scheme, the present application can reduce the risk of abnormal conditions by drawing the monitored data stream as a three-axis curve.

[0121] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following description and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0122] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood by considering the following detailed description, from which the singular features of the application will be more clearly identified, particularly when considered in connection with the accompanying drawings, in which:

[0123] Figure 1 is a schematic block diagram of the present application.

[0124] Figure 2 is a flowchart schematic block diagram of the present application. DETAILED DESCRIPTION

[0125] The embodiments of the present application will be described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation of the present application.

[0126] The present application provides an online monitoring system for power plant energy consumption data based on big data analysis, such as Figure 1As shown, including energy consumption data online detection module, energy consumption data packet generation and transmission module and abnormal data segment acquisition module;

[0127] Energy consumption data online detection module is used for acquiring the sensor installed in the energy consumption device to realize online monitoring of the power plant energy consumption data;

[0128] Energy consumption data packet generation and transmission module is used for transmitting the online monitoring energy consumption packet to the energy consumption analysis data platform;

[0129] The abnormal data segment acquisition module is used for the energy consumption analysis data platform to receive the online monitoring energy consumption packet, and the energy consumption data output result is obtained.

[0130] In a preferred embodiment of the present application, the energy consumption data online detection module comprises:

[0131] The sensor installed in the energy consumption device is a voltage sensor and a current sensor;

[0132] The voltage sensor is used for monitoring the running voltage value of the energy consumption device in the working state ;

[0133] The current sensor is used for monitoring the running current value of the energy consumption device in the working state .

[0134] In a preferred embodiment of the present application, the energy consumption data packet generation and transmission module comprises:

[0135] S21, an X-Y-Z three-axis coordinate system is constructed:

[0136] Wherein, the X axis represents time, the Y axis represents voltage, and the Z axis represents current;

[0137] S22, the running voltage value and the current value at time are drawn into the coordinate system, the running voltage value and the current value at time are drawn into the coordinate system, and then the drawing points on the XY plane are connected to form - Time-voltage curve, the drawing points on the XZ plane are connected to form - Time-current curve, and the drawing points on the YZ plane are connected to form - Voltage-current curve;

[0138] S23, after the curve is generated, the online monitoring picture in the format of JPEG or PNG is generated; the online monitoring picture can be converted into a gray image by using a gray scale algorithm;

[0139] S24, the online monitoring picture is transformed by confusion to generate an online monitoring confusion picture;

[0140] S25, after the online monitoring confusion picture is compressed, an online monitoring energy consumption package is obtained.

[0141] In a preferred embodiment of the present application, step S24 comprises:

[0142] S241, position transposition, the pixel value in the picture is exchanged according to the following manner:

[0143] If , the value of the first bit and the value of the second bit of the pixel point are exchanged;

[0144] If , the value of the first bit and the value of the second bit of the pixel point are not exchanged;

[0145] represents the value of the first bit of the pixel point in the online monitoring picture;

[0146] represents the value of the second bit of the pixel point in the online monitoring picture;

[0147] represents the number of horizontal pixel points of the picture;

[0148] represents the number of vertical pixel points of the picture;

[0149] represents the bit number of the pixel value of the picture;

[0150] represents the division number;

[0151] represents the floor;

[0152] represents the constraint condition;

[0153] ​​​​​​​​​ Indicates interchange symbols;

[0154] S242, numerical transformation, transforming the pixel values ​​in the image (the pixel values ​​are in binary form) in the following manner:

[0155] like ,but That is, at the pixel point No. The digit value is 0;

[0156] like ,but That is, at the pixel point No. The digit value is 1;

[0157] Indicates the pixel in the online monitoring image. No. Place value;

[0158] Indicates the pixel in the online monitoring image. No. Place value;

[0159] Indicates the number of horizontal pixels in the image;

[0160] Indicates the number of vertical pixels in the image;

[0161] The number of pixel values ​​representing the image;

[0162] Indicates the number of horizontal divisions; ;

[0163] Indicates the number of vertical divisions; ;

[0164] Indicates rounding down;

[0165] Indicates constraints.

[0166] For example, assuming that the online monitoring picture is an H×W (5×6) image, the specific image values ​​are shown in Table 1.

[0167] First, obtain the image values ​​of the online monitoring image (the number of bits of each image value is equal to the number of bits of the image) as shown in Table 1;

[0168] Table 1 5×6 image values

[0169] 11000000 00111100 00110000 01000010 01100001 11100110 11101001 11000100 11110001 11100000 11000000 10011100 01111111 00110111 10011101 10011101 11111001 11110011 11011000 00111110 11111100 11110001 01111101 00111011 11101110 01111110 00011110 11100111 11111100 10110110

[0170] Secondly, the image values in the picture are interchanged in position, and the image values in the picture after being interchanged in position are shown in Table 2;

[0171] Table 2 image values after interchanging positions

[0172] 00000011 00111100 00001100 01000010 10000110 01100111 10010111 00100011 10001111 00000111 00000011 00111001 11111110 11101100 10111001 10111001 10011111 11001111 00011011 01111100 00111111 10001111 10111110 11011100 01110111 01111110 01111000 11100111 00111111 01101101

[0173] Furthermore, the image values in the picture are transformed in value, and the image values in the picture after being transformed in value are shown in Table 3;

[0174] Table 3 image values after transforming in value

[0175] 01000010 01001100 11001100 01000010 10000110 01100111 11110111 01100101 11001001 00000111 00000011 00111001 11111110 11101100 10111001 10111001 10011111 11001111 00011011 01111100 00111111 10001111 10111110 11011100 01110111 01111110 01111000 11100111 00111111 01101101

[0176] Finally, the confusion picture can be generated according to the image values after being transformed in value.

[0177] In a preferred embodiment of the present application, the abnormal data segment acquisition module comprises:

[0178] S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring picture;

[0179] S32, the online platform monitoring picture is subjected to confusion inverse transformation to generate a normal monitoring picture;

[0180] S33, voltage values at all time points are extracted from the curve in the normal picture and current values , real-time energy consumption is obtained according to the extracted voltage values at all time points and current values

[0181] ,

[0182] wherein, represents the real-time energy consumption of the energy consumption equipment at time point ;

[0183] represents the running voltage value of the energy consumption equipment at time point ;

[0184] represents the running current value of the energy consumption equipment at time point ;

[0185] The real-time energy consumption is formed into an energy consumption sequence in chronological order;

[0186] S34, abnormal point judgment is performed on the energy consumption in the sequence:​

[0187] like , it is judged as the initial abnormal energy consumption period;

[0188] That is and The absolute difference is greater than , recorded as ,on the contrary ;

[0189] Indicates abnormal energy consumption. Indicates normal energy consumption;

[0190] Indicates abnormal energy consumption setting value; , ;

[0191] represents the serial interval;

[0192] The abnormal energy consumption setting value is an empirical summary value. During the long-term normal operation of the equipment, the normal operating energy consumption is arranged from large to small and the median is taken. The absolute difference between the median and the maximum and minimum values ​​is taken, and the larger value is our abnormal energy consumption setting value.

[0193] The sequence interval is a set interval, generally 550ms to 1500ms. We use 1s. If an abnormality occurs within this 1s, then this 1s is the abnormal time period;

[0194] when This means that in the sequence arrive is the abnormal time period, the corresponding sequence Corresponding moments and sequences The corresponding time difference is 1s.

[0195] Equipment operation data includes a series of data such as the temperature and humidity of the environment in which the equipment is located, the temperature of the equipment itself, input voltage, working mode, current operation time, cumulative time, etc.; requesting this data facilitates comprehensive status analysis and control of the equipment system.

[0196] Then determine the status of energy-consuming devices during the abnormal time period:

[0197] If it is in shutdown state, the energy-consuming equipment is not abnormal;

[0198] If it is in the running state, the energy-consuming equipment is abnormal.

[0199] The present invention also discloses an online monitoring method for power plant energy consumption data based on big data analysis, such as Figure 2 As shown, the following steps are included:

[0200] S1, obtaining a sensor installed in the energy consumption device to realize online monitoring of the power plant energy consumption data;

[0201] S2, transmitting the online monitoring energy consumption package to the energy consumption analysis data platform;

[0202] S3, after the energy consumption analysis data platform receives the online monitoring energy consumption package, outputting results for the energy consumption data.

[0203] In a preferred embodiment of the present application, step S1 comprises:

[0204] The sensor installed in the energy consumption device is a voltage sensor and a current sensor;

[0205] The voltage sensor is used to monitor the running voltage value of the energy consumption device in the working state . , represents the starting time of the sensor collection, represents the end time of the sensor collection;

[0206] The current sensor is used to monitor the running current value of the energy consumption device in the working state .

[0207] In a preferred embodiment of the present application, step S2 comprises:

[0208] S21, constructing an X-Y-Z three-axis coordinate system:

[0209] Wherein, the X axis represents time, the Y axis represents voltage, and the Z axis represents current;

[0210] S22, drawing the running voltage value and the current value at time to the coordinate system, drawing the running voltage value and the current value at time to the coordinate system, connecting the drawing points on the XY plane to form - time-voltage curve, connecting the drawing points on the XZ plane to form - time-current curve, and connecting the drawing points on the YZ plane to form - voltage-current curve; wherein the three curves are marked in different colors for easy identification, which can be - time-voltage curve is yellow, - The time-current curve is red, - The voltage-current curve is orange; it can also be the same color, such as yellow or red or orange; the background is white or cyan;

[0211] S23, after the curve is generated, an online monitoring picture in JPEG or PNG format is generated;

[0212] S24, the online monitoring picture is transformed by confusion to generate an online monitoring confusion picture;

[0213] S25, after the online monitoring confusion picture is compressed, an online monitoring energy consumption package is obtained. The compression method uses rar or zip compression.

[0214] In a preferred embodiment of the present application, step S24 includes:

[0215] S241, position transposition, the pixel values in the picture are exchanged according to the following method:

[0216] If , then that is, the first bit value and the first bit value of the pixel point are exchanged;

[0217] If , then that is, the first bit value and the first bit value of the pixel point are not exchanged;

[0218] represents the first bit value of the pixel point in the online monitoring picture;

[0219] represents the first bit value of the pixel point in the online monitoring picture;

[0220] represents the number of horizontal pixel points of the picture;

[0221] represents the number of vertical pixel points of the picture;

[0222] represents the pixel value bit number of the picture;

[0223] represents the division number; ;

[0224] denotes rounding down;

[0225] denotes a constraint condition;

[0226] denotes an exchange symbol;

[0227] S242, numerical transformation, the pixel value in the picture is transformed in the following manner:

[0228] If , then the value of the first bit of the pixel point is 0;

[0229] If , then the value of the first bit of the pixel point is 1;

[0230] denotes the value of the first bit of the pixel point in the picture under online monitoring;

[0231] denotes the value of the first bit of the pixel point in the picture under online monitoring;

[0232] denotes the number of horizontal pixel points of the picture;

[0233] denotes the number of vertical pixel points of the picture;

[0234] denotes the bit number of the pixel value of the picture;

[0235] denotes the horizontal division number; ;

[0236] denotes the vertical division number; ;

[0237] denotes rounding down;

[0238] denotes a constraint condition.

[0239] In a preferred embodiment of the present application, step S3 comprises:

[0240] ​​​​S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring picture;

[0241] S32, the online platform monitoring picture is subjected to confusion inverse transformation to generate a normal monitoring picture;

[0242] S33, voltage values at all time points are extracted from a curve in the normal picture and current values , real-time energy consumption is obtained according to the extracted voltage values at all time points and current values

[0243] ,

[0244] wherein, represents real-time energy consumption of the energy consumption equipment at time point ;

[0245] represents running voltage value of the energy consumption equipment at time point ;

[0246] represents running current value of the energy consumption equipment at time point ;

[0247] real-time energy consumption is formed into an energy consumption sequence in chronological order;

[0248] S34, abnormal point judgment is performed on energy consumption in the sequence:

[0249] if , it is judged as an energy consumption preliminary abnormal section;

[0250] that is, and absolute difference is greater than , recorded as , otherwise ;

[0251] represents energy consumption abnormality, represents energy consumption normality;

[0252] represents energy consumption abnormality setting value; , ;

[0253] represents sequence interval;

[0254] then, the state of the energy consumption equipment in the abnormal time section is judged:

[0255] ​If it is in shutdown state, the energy-consuming equipment is not abnormal;

[0256] If it is in the running state, the energy-consuming equipment is abnormal.

[0257] In a preferred embodiment of the present invention, step S32 includes:

[0258] S321, numerical transformation, transforms the pixel values ​​in the online platform monitoring image in the following manner:

[0259] like ,but That is, at the pixel point No. The digit value is 0;

[0260] like ,but That is, at the pixel point No. The digit value is 1;

[0261] Indicates the pixel in the online platform monitoring image No. Place value;

[0262] Indicates the pixel in the online platform monitoring image No. Place value;

[0263] Indicates the number of horizontal pixels in the image;

[0264] Indicates the number of vertical pixels in the image;

[0265] The number of pixel values ​​representing the image;

[0266] Indicates the number of horizontal divisions; ;

[0267] Indicates the number of vertical divisions; ;

[0268] Indicates rounding down;

[0269] Indicates constraints;

[0270] S322, swapping positions, swapping pixel values ​​in the online platform monitoring image in the following manner:

[0271] like ,but That is, at the pixel point No. The place value and Interchange of place values;

[0272] like ,but That is, at the pixel point No. The place value and Place values ​​are not interchanged;

[0273] Indicates the pixel in the online platform monitoring image No. Place value;

[0274] Indicates the pixel in the online platform monitoring image No. Place value;

[0275] Indicates the number of horizontal pixels in the image;

[0276] Indicates the number of vertical pixels in the image;

[0277] The number of pixel values ​​representing the image;

[0278] Indicates the number of partitions; ;

[0279] Indicates rounding down;

[0280] Indicates constraints;

[0281] Indicates interchange symbols.

[0282] The present invention also discloses a computer system, comprising:

[0283] processor;

[0284] a memory for storing processor-executable instructions;

[0285] Wherein, the processor is configured to implement the online monitoring method of power plant energy consumption data based on big data analysis when executing the executable instructions.

[0286] The present invention also discloses a computer-readable storage medium, comprising:

[0287] a memory having a computer program stored thereon;

[0288] a processor for executing the program in the memory to implement the online monitoring method for power plant energy consumption data based on big data analysis.

[0289] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.

Claims

1. An online monitoring system for power plant energy consumption data based on big data analysis, characterized in that: It includes energy consumption data online detection module, energy consumption data packet generation and transmission module and abnormal data segment acquisition module; The energy consumption data online detection module is used to obtain sensors installed in energy consumption equipment to realize online monitoring of power plant energy consumption data; The energy consumption data packet generation and transmission module is used to transmit the online monitoring energy consumption package to the energy consumption analysis data platform; the energy consumption data packet generation and transmission module includes: S21, build the XYZ three-axis coordinate system: Among them, the X-axis represents time, the Y-axis represents voltage, and the Z-axis represents current; S22, the moment Operating voltage value and current value Draw it into the coordinate system and convert the time Operating voltage value and current value After drawing into the coordinate system, connect the drawing points on the surface where the XY axis is located to form - The time voltage curve is formed by connecting the plot points on the surface where the XZ axis is located. - The time-current curve is formed by connecting the plot points on the YZ axis surface - Voltage-current curve; S23, after the curve is generated, an online monitoring image in JPEG or PNG format is generated; S24, performing obfuscation transformation on the online monitoring image to generate an online monitoring obfuscated image; S25, compressing the online monitoring confusion image to obtain an online monitoring energy consumption package; The abnormal data segment acquisition module is used to output the results of energy consumption data after the energy consumption analysis data platform receives the online monitoring energy consumption package.

2. The online monitoring system for power plant energy consumption data based on big data analysis according to claim 1 is characterized in that: The energy consumption data online detection module includes: The sensors installed in the energy-consuming equipment are voltage sensors and current sensors; Voltage sensors are used to monitor the operating voltage of energy-consuming equipment online. ; Current sensors are used to monitor the operating current value of energy-consuming equipment online. .

3. The online monitoring system for power plant energy consumption data based on big data analysis according to claim 1 is characterized in that: Step S24 includes: S241, swap positions, swap the pixel values ​​in the image in the following manner: like ,but That is, at the pixel point No. The place value and Interchange of place values; like ,but That is, at the pixel point No. The place value and Place values ​​are not interchanged; Indicates the pixel point in the online monitoring image No. Place value; Indicates the pixel point in the online monitoring image No. Place value; Indicates the number of horizontal pixels in the image; Indicates the number of vertical pixels in the image; The number of pixel values ​​representing the image; Indicates the number of partitions; ; Indicates rounding down; Indicates constraints; Indicates interchange symbols; S242, numerical transformation, transforms the pixel values ​​in the image in the following manner: like ,but That is, at the pixel point No. The digit value is 0; like ,but That is, at the pixel point No. The digit value is 1; Indicates the pixel point in the online monitoring image No. Place value; Indicates the pixel point in the online monitoring image No. Place value; Indicates the number of horizontal pixels in the image; Indicates the number of vertical pixels in the image; The number of pixel values ​​representing the image; Indicates the number of horizontal divisions; ; Indicates the number of vertical divisions; ; Indicates rounding down; Indicates constraints.

4. The online monitoring system for power plant energy consumption data based on big data analysis according to claim 1 is characterized in that: The abnormal data segment acquisition module includes: S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring image; S32, performing an obfuscation inverse transformation on the online platform monitoring image to generate a normal monitoring image; S33, extract the voltage value at all times from the curve in the normal image and current value , according to the voltage values ​​extracted at all times and current value Get real-time energy consumption: ， in, Indicates the energy consumption equipment at time Real-time energy consumption; Indicates the energy consumption equipment at time The operating voltage value; Indicates the energy consumption equipment at time The operating current value; The real-time energy consumption is formed into an energy consumption sequence in chronological order ; S34, determine the abnormal points of energy consumption in the sequence: like , it is judged as the initial abnormal energy consumption period; That is and The absolute difference is greater than , recorded as ,on the contrary ; Indicates abnormal energy consumption. Indicates normal energy consumption; Indicates abnormal energy consumption setting value; , ; represents the serial interval; Then determine the status of energy-consuming devices during the abnormal time period: If it is in shutdown state, the energy-consuming equipment is not abnormal; If it is in the running state, the energy-consuming equipment is abnormal.

5. A method for online monitoring of power plant energy consumption data based on big data analysis, characterized in that: The following steps are involved: S1, obtain sensors installed in energy-consuming equipment to realize online monitoring of power plant energy consumption data; S2, transmitting the online monitoring energy consumption package to the energy consumption analysis data platform; step S2 includes: S21, build the XYZ three-axis coordinate system: Among them, the X-axis represents time, the Y-axis represents voltage, and the Z-axis represents current; S22, the moment Operating voltage value and current value Draw it into the coordinate system and convert the time Operating voltage value and current value After drawing into the coordinate system, connect the drawing points on the surface where the XY axis is located to form - The time voltage curve is formed by connecting the plot points on the surface where the XZ axis is located. - The time-current curve is formed by connecting the plot points on the YZ axis surface - Voltage-current curve; S23, after the curve is generated, an online monitoring image in JPEG or PNG format is generated; S24, performing obfuscation transformation on the online monitoring image to generate an online monitoring obfuscated image; S25, compressing the online monitoring confusion image to obtain an online monitoring energy consumption package; S3: After receiving the online monitoring energy consumption package, the energy consumption analysis data platform outputs the results for the energy consumption data.

6. The method for online monitoring of power plant energy consumption data based on big data analysis according to claim 5 is characterized in that: Step S1 includes: The sensors installed in the energy-consuming equipment are voltage sensors and current sensors; Voltage sensors are used to monitor the operating voltage of energy-consuming equipment online. ; Current sensors are used to monitor the operating current value of energy-consuming equipment online. .

7. The method for online monitoring of power plant energy consumption data based on big data analysis according to claim 5 is characterized in that: Step S24 includes: S241, swap positions, swap the pixel values ​​in the image in the following manner: like ,but That is, at the pixel point No. The place value and Interchange of place values; like ,but That is, at the pixel point No. The place value and Place values ​​are not interchanged; Indicates the pixel point in the online monitoring image No. Place value; Indicates the pixel point in the online monitoring image No. Place value; Indicates the number of horizontal pixels in the image; Indicates the number of vertical pixels in the image; The number of pixel values ​​representing the image; Indicates the number of partitions; ; Indicates rounding down; Indicates constraints; Indicates interchange symbols; S242, numerical transformation, transforms the pixel values ​​in the image in the following manner: like ,but That is, at the pixel point No. The digit value is 0; like ,but That is, at the pixel point No. The digit value is 1; Indicates the pixel point in the online monitoring image No. Place value; Indicates the pixel point in the online monitoring image No. Place value; Indicates the number of horizontal pixels in the image; Indicates the number of vertical pixels in the image; The number of pixel values ​​representing the image; Indicates the number of horizontal divisions; ; Indicates the number of vertical divisions; ; Indicates rounding down; Indicates constraints.

8. The method for online monitoring of power plant energy consumption data based on big data analysis according to claim 5 is characterized in that: Step S3 includes: S31, the energy consumption analysis data platform decompresses the received online monitoring energy consumption package to obtain an online platform monitoring image; S32, performing an obfuscation inverse transformation on the online platform monitoring image to generate a normal monitoring image; S33, extract the voltage value at all times from the curve in the normal image and current value , according to the voltage values ​​extracted at all times and current value Get real-time energy consumption: ， in, Indicates the energy consumption equipment at time Real-time energy consumption; Indicates the energy consumption equipment at time The operating voltage value; Indicates the energy consumption equipment at time The operating current value; The real-time energy consumption is formed into an energy consumption sequence in chronological order ; S34, determine the abnormal points of energy consumption in the sequence: like , it is judged as the initial abnormal energy consumption period; That is and The absolute difference is greater than , recorded as ,on the contrary ; Indicates abnormal energy consumption. Indicates normal energy consumption; Indicates abnormal energy consumption setting value; , ; represents the serial interval; Then determine the status of energy-consuming devices during the abnormal time period: If it is in shutdown state, the energy-consuming equipment is not abnormal; If it is in the running state, the energy-consuming equipment is abnormal.

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