Real-time monitoring system and method of regional energy consumption based on power big data

Abstract

The present application provides a system and method for real-time monitoring of regional energy consumption based on power big data, the system comprising: a selection module for selecting a monitoring area; a data acquisition module for acquiring real-time power data of the monitoring area; a data input module for determining the power type of the monitoring area based on the power data, and inputting the power data analysis into different calculation channels based on the power type; a data calculation module for calling calculation rules for the calculation channel, and calculating the energy consumption value of each type of the power data according to the calculation rules; a data statistics module for acquiring energy consumption values ​​calculated from multiple types of power data, and generating a total energy consumption value. The present application monitors energy consumption by reading power data in real time, thereby realizing real-time detection of energy consumption.

Description

Technical Field

[0001] The present application seeks to protect an energy consumption monitoring technology, and in particular, relates to a regional energy consumption real-time monitoring system based on power big data. The present application also relates to a regional energy consumption real-time monitoring method based on power big data. Background Art

[0002] Real-time detection of regional energy consumption refers to the detection of electricity consumption in a certain area. Through the detection of energy consumption, a variety of big data analyses can be performed, including industrial development level, commercial development level and carbon emission detection.

[0003] At present, energy consumption monitoring of electricity consumption is mainly achieved through classification and statistics methods. This method has a long working cycle, a huge data load, and is difficult to detect in real time. Summary of the invention

[0004] In order to solve one or more technical problems in the above technical solutions, the present application provides a real-time monitoring system for regional energy consumption based on power big data. The present application also relates to a real-time monitoring method for regional energy consumption based on power big data.

[0005] The present application provides a regional energy consumption real-time monitoring system based on power big data, including:

[0006] Selection module, used to select monitoring area;

[0007] A data acquisition module, used to acquire real-time power data of the monitoring area;

[0008] A data input module, used to determine the power type of the monitoring area according to the power data, and analyze and input the power data into different calculation channels based on the power type;

[0009] A data calculation module, used to call calculation rules for the calculation channel, and calculate the energy consumption value of each type of power data according to the calculation rules;

[0010] The data statistics module is used to obtain energy consumption values ​​calculated from multiple types of power data and generate a total energy consumption value.

[0011] Optionally, the types of electricity include: industrial electricity, commercial electricity, agricultural electricity and domestic electricity.

[0012] Optionally, the calculation channel is started according to the power type, including:

[0013] The power type is obtained, a computing channel start instruction is generated based on the power type, and one or more computing channels are started respectively according to the start instruction.

[0014] Optionally, the calculation rules include:

[0015] Calculating work power and determining the type of work;

[0016] Calculate the work loss of this work type;

[0017] The work power and the power loss are summed.

[0018] Optionally, an early warning module is also included;

[0019] The warning module determines whether the energy consumption value exceeds a preset warning value, and issues a warning message when it exceeds the preset warning value.

[0020] The present application also provides a method for real-time monitoring of regional energy consumption based on power big data, including:

[0021] Select the monitoring area;

[0022] Acquiring real-time power data of the monitoring area;

[0023] According to the power data, determining the power type of the monitoring area, and analyzing and inputting the power data into different calculation channels based on the power type;

[0024] Calling a calculation rule for the calculation channel, and calculating the energy consumption value of each type of the power data according to the calculation rule;

[0025] Optionally, the types of electricity include: industrial electricity, commercial electricity, agricultural electricity and domestic electricity.

[0026] Optionally, the calculation channel is started according to the power type, including:

[0027] The power type is obtained, a computing channel start instruction is generated based on the power type, and one or more computing channels are started respectively according to the start instruction.

[0028] Optionally, the calculation rules include:

[0029] Calculating work power and determining the type of work;

[0030] Calculate the work loss of this work type;

[0031] The work power and the power loss are summed.

[0032] Optionally, an early warning module is also included;

[0033] The warning module determines whether the energy consumption value exceeds a preset warning value, and issues a warning message when it exceeds the preset warning value.

[0034] The advantages of this application compared to the prior art are:

[0035] The present application provides a regional energy consumption real-time monitoring system based on power big data, including: a selection module for selecting a monitoring area; a data acquisition module for acquiring real-time power data of the monitoring area; a data input module for judging the power type of the monitoring area according to the power data, and inputting the power data analysis into different calculation channels based on the power type; a data calculation module for calling calculation rules for the calculation channel, and calculating the energy consumption value of each type of the power data according to the calculation rules; a data statistics module for acquiring energy consumption values ​​calculated by multiple types of power data, and generating a total energy consumption value. The present application monitors energy consumption by reading power data in real time, thereby realizing real-time detection of energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the real-time monitoring system of regional energy consumption based on power big data in this application.

[0037] Figure 2 It is a flow chart of calculation channel allocation in this application.

[0038] Figure 3 This is a flow chart of real-time monitoring of regional energy consumption based on power big data in this application. DETAILED DESCRIPTION

[0039] The following contents are all examples of specific implementation processes provided for describing in detail the technical solutions to be protected by this application. However, this application may also be implemented in other ways different from the descriptions herein. Persons skilled in the art may, under the guidance of the concepts of this application, adopt different technical means to implement this application. Therefore, this application is not limited to the specific embodiments below.

[0040] The present application provides a regional energy consumption real-time monitoring system based on power big data, including: a selection module for selecting a monitoring area; a data acquisition module for acquiring real-time power data of the monitoring area; a data input module for judging the power type of the monitoring area according to the power data, and inputting the power data analysis into different calculation channels based on the power type; a data calculation module for calling calculation rules for the calculation channel, and calculating the energy consumption value of each type of the power data according to the calculation rules; a data statistics module for acquiring energy consumption values ​​calculated by multiple types of power data, and generating a total energy consumption value. The present application monitors energy consumption by reading power data in real time, thereby realizing real-time detection of energy consumption.

[0041] Figure 1 It is a schematic diagram of the real-time monitoring system of regional energy consumption based on power big data in this application.

[0042] Please refer to Figure 1 As shown, the selection module 101 is used to select a monitoring area.

[0043] The monitoring area refers to an area to be detected, which can be an administrative area or a natural area. The area can generate and sell electricity by itself, receive input electricity, and export electricity.

[0044] The selecting of the monitoring area refers to selecting the entire area or a part of the area within a detectable area, and using the selected area as the energy consumption monitoring area.

[0045] Specifically, the monitoring area is displayed on the display and is pre-divided into a plurality of basic areas of preset sizes. When selecting, one or more basic areas can be selected by clicking the mouse to select the area for energy consumption monitoring.

[0046] The data acquisition module 102 is used to acquire the real-time power data of the monitoring area;

[0047] The power data is acquired through sensors. Specifically, when an area is selected, the power generated in the area is detected, and the power input to the area is also detected, and the detected signal is sent to the data acquisition module 102 to read the power data. In this application, the power data includes: power generation.

[0048] After acquiring the power data, the power data is stored in the cache in chronological order for reading, and the data is stored in the memory in chronological order for preservation, and can be directly read when needed, for example, when changing the selected area, the data in the memory can be read for energy consumption calculation.

[0049] The data input module 103 is used to determine the power type of the monitoring area according to the power data, and analyze and input the power data into different calculation channels based on the power type.

[0050] The electricity type refers to the type of electricity used, including industrial electricity, commercial electricity, agricultural electricity and domestic electricity. Industrial electricity refers to electricity used in industrial production, commercial electricity refers to electricity used in commercial transactions and operations, agricultural electricity refers to electricity used in agricultural production, and domestic electricity refers to electricity used in users' lives.

[0051] Figure 2 It is a flow chart of calculation channel allocation in this application.

[0052] Please refer to Figure 2As shown, according to the different types of power usage, the power data is classified and input into different calculation channels for energy consumption calculation, including:

[0053] S201 obtains the power type;

[0054] S202 generates a calculation channel start instruction based on the power type, and starts one or more calculation channels respectively according to the start instruction.

[0055] A data calculation module 104, configured to call a calculation rule for the calculation channel and calculate the energy consumption value of each type of the power data according to the calculation rule;

[0056] The calculation channel refers to different types of data, and their energy consumption calculation methods are also different, so multiple calculation methods are performed simultaneously, and each calculation method refers to a calculation channel.

[0057] Specifically, the present application is provided with a plurality of calculation channels, and each of the calculation channels performs energy consumption calculation according to the calculation method of the circuit data of this type after reading the power data, including:

[0058] The work power is calculated and the type of work is determined, and the type parameter is determined by determining the type.

[0059] Calculate the work loss of this work type;

[0060] The work power and the power loss are summed.

[0061] Specifically, the parameters for calculating energy consumption for different types of power data are different, and the calculation expressions are as follows:

[0062]

[0063] Wherein, N is the energy consumption data of each power type, x represents time, a and b represent the start time and end time of energy consumption monitoring, L represents the type parameter, and m is the loss percentage. The value of each power type is different.

[0064] The data statistics module 105 is used to obtain energy consumption values ​​calculated from multiple types of power data and generate a total energy consumption value.

[0065] The energy consumption value of the power data is composed of multiple different types of power type energy consumption, and the total energy consumption value can be obtained by adding up the different types of energy consumption.

[0066] In addition, if the region has electricity exported to other regions, the energy consumption value of the exported electricity is subtracted; if there is imported electricity, the imported electricity is added to obtain complete energy consumption data.

[0067] In the present application, the energy consumption monitoring is real-time, but the calculation of the energy consumption data has certain intervals. Such intervals do not actually affect the real-time nature of the energy consumption monitoring, but increase the stability and reliability of the data.

[0068] Preferably, it also includes an early warning module for determining whether the energy consumption value exceeds a preset early warning value, and issuing an early warning message when it exceeds the preset early warning value.

[0069] The present application also provides a method for real-time monitoring of regional energy consumption based on power big data, which monitors energy consumption by reading power data in real time, thereby realizing real-time detection of energy consumption.

[0070] Figure 3 This is a flow chart of real-time monitoring of regional energy consumption based on power big data in this application.

[0071] Please refer to Figure 3 As shown, S301 selects a monitoring area.

[0072] The monitoring area refers to an area to be detected, which can be an administrative area or a natural area. The area can generate and sell electricity by itself, receive input electricity, and export electricity.

[0073] The selecting of the monitoring area refers to selecting the entire area or a part of the area within a detectable area, and using the selected area as the energy consumption monitoring area.

[0074] Specifically, the monitoring area is displayed on the display and is pre-divided into a plurality of basic areas of preset sizes. When selecting, one or more basic areas can be selected by clicking the mouse to select the area for energy consumption monitoring.

[0075] Please refer to step 3, S302 obtains real-time power data of the monitoring area.

[0076] The power data is acquired through sensors. Specifically, when an area is selected, the power generated in the area is detected, and the power input to the area is also detected, and the detected signal is sent to the data acquisition module 102 to read the power data. In this application, the power data includes: power generation.

[0077] After acquiring the power data, the power data is stored in the cache in chronological order for reading, and the data is stored in the memory in chronological order for preservation, and can be directly read when needed, for example, when changing the selected area, the data in the memory can be read for energy consumption calculation.

[0078] Please refer to Figure 3As shown, S303 determines the power type of the monitoring area according to the power data, and inputs the power data analysis into different calculation channels based on the power type.

[0079] The electricity type refers to the type of electricity used, including industrial electricity, commercial electricity, agricultural electricity and domestic electricity. Industrial electricity refers to electricity used in industrial production, commercial electricity refers to electricity used in commercial transactions and operations, agricultural electricity refers to electricity used in agricultural production, and domestic electricity refers to electricity used in users' lives.

[0080] Please refer to Figure 2 As shown, according to the different types of power usage, the power data is classified and input into different calculation channels for energy consumption calculation, including:

[0081] S201 obtains the power type;

[0082] S202 generates a calculation channel start instruction based on the power type, and starts one or more calculation channels respectively according to the start instruction.

[0083] Please refer to Figure 3 In step S304, the calculation channel calls a calculation rule, and calculates the energy consumption value of each type of the power data according to the calculation rule;

[0084] The calculation channel refers to different types of data, and their energy consumption calculation methods are also different, so multiple calculation methods are performed simultaneously, and each calculation method refers to a calculation channel.

[0085] Specifically, the present application is provided with a plurality of calculation channels, and each of the calculation channels performs energy consumption calculation according to the calculation method of the circuit data of this type after reading the power data, including:

[0086] The work power is calculated and the type of work is determined, and the type parameter is determined by determining the type.

[0087] Calculate the work loss of this work type;

[0088] The work power and the power loss are summed.

[0089] Specifically, the parameters for calculating energy consumption for different types of power data are different, and the calculation expressions are as follows:

[0090]

[0091] Wherein, N is the energy consumption data of each power type, x represents time, a and b represent the start time and end time of energy consumption monitoring, L represents the type parameter, and m is the loss percentage. The value of each power type is different.

[0092] Please refer to Figure 3 As shown, S305 obtains energy consumption values ​​calculated from multiple types of power data and generates a total energy consumption value.

[0093] The energy consumption value of the power data is composed of multiple different types of power type energy consumption, and the total energy consumption value can be obtained by adding up the different types of energy consumption.

[0094] In addition, if the region has electricity exported to other regions, the energy consumption value of the exported electricity is subtracted; if there is imported electricity, the imported electricity is added to obtain complete energy consumption data.

[0095] In the present application, the energy consumption monitoring is real-time, but the calculation of the energy consumption data has certain intervals. Such intervals do not actually affect the real-time nature of the energy consumption monitoring, but increase the stability and reliability of the data.

[0096] Preferably, it also includes an early warning module for determining whether the energy consumption value exceeds a preset early warning value, and issuing an early warning message when it exceeds the preset early warning value.

[0097] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0098] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A regional energy consumption real-time monitoring system based on power big data, characterized in that: include: Selection module, used to select monitoring area; A data acquisition module, used to acquire real-time power data of the monitoring area; A data input module, used to determine the power type of the monitoring area according to the power data, and analyze and input the power data into different calculation channels based on the power type; A data calculation module, used to call calculation rules for the calculation channel, and calculate the energy consumption value of each type of power data according to the calculation rules; The data statistics module is used to obtain energy consumption values ​​calculated from multiple types of power data and generate a total energy consumption value.

2. According to claim 1, the regional energy consumption real-time monitoring system based on power big data is characterized in that: The types of electricity include: industrial electricity, commercial electricity, agricultural electricity and domestic electricity.

3. According to claim 1, the regional energy consumption real-time monitoring system based on power big data is characterized in that: The calculation channel is started according to the power type and includes: The power type is obtained, a computing channel start instruction is generated based on the power type, and one or more computing channels are started respectively according to the start instruction.

4. According to claim 1, the regional energy consumption real-time monitoring system based on power big data is characterized in that: The calculation rules include: Calculating work power and determining the type of work; Calculate the work loss of this work type; The work power and the power loss are summed.

5. According to claim 1, the regional energy consumption real-time monitoring system based on power big data is characterized in that: It also includes an early warning module; The warning module determines whether the energy consumption value exceeds a preset warning value, and issues a warning message when it exceeds the preset warning value.

6. A method for real-time monitoring of regional energy consumption based on power big data, characterized in that: include: Select the monitoring area; Acquiring real-time power data of the monitoring area; According to the power data, determining the power type of the monitoring area, and analyzing and inputting the power data into different calculation channels based on the power type; Calling a calculation rule for the calculation channel, and calculating the energy consumption value of each type of the power data according to the calculation rule; Energy consumption values ​​calculated from the power data of multiple types are acquired, and a total energy consumption value is generated.

7. The method for real-time monitoring of regional energy consumption based on power big data according to claim 6 is characterized in that: The types of electricity include: industrial electricity, commercial electricity, agricultural electricity and domestic electricity.

8. The method for real-time monitoring of regional energy consumption based on power big data according to claim 6 is characterized in that: The calculation channel is started according to the power type and includes: The power type is obtained, a computing channel start instruction is generated based on the power type, and one or more computing channels are started respectively according to the start instruction.

9. The method for real-time monitoring of regional energy consumption based on power big data according to claim 6 is characterized in that: The calculation rules include: Calculating work power and determining the type of work; Calculate the work loss of this work type; The work power and the power loss are summed.

10. The method for real-time monitoring of regional energy consumption based on power big data according to claim 6 is characterized in that: It also includes an early warning module; The warning module determines whether the energy consumption value exceeds a preset warning value, and issues a warning message when it exceeds the preset warning value.

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