CN112258098B - Intelligent control data processing method and system for power equipment - Google Patents
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Abstract
According to the intelligent control data processing method and system for the power equipment, log event distribution data of the target power equipment, which is used for acquiring equipment operation log data, can be determined, and energy-saving state assessment and power utilization safety assessment of the log event distribution data are sequentially achieved, so that power utilization strategy data of first equipment and power utilization strategy data of second equipment are generated. In this way, the target power device can be intelligently controlled according to the second device power utilization strategy data. Because the second device power utilization strategy data comprises the corresponding user demand description curve, the energy-saving index description curve and the safety index description curve, when the target power equipment is intelligently controlled, the compatibility among the user demand, the power utilization safety and energy conservation and emission reduction can be considered, so that one-stop flow management of the target power equipment is realized, and the safe operation and the energy conservation and emission reduction of the power equipment can be realized on the premise of meeting the demands of power users.
Description
Technical Field
The present disclosure relates to the field of power equipment control and data processing technologies, and in particular, to a method and a system for processing power equipment intelligent control data.
Background
Along with the development of science and technology, the types and functions of power equipment are more and more, and the production and the life of people are greatly enriched. However, with the rapid development of science and technology and society, environmental deterioration is also caused to some extent. Therefore, at present, low carbon, energy conservation and environmental protection are trends of social development. The same is true for the operation of the power plant. In addition, with the increasing complexity of power grids, frequent power utilization accidents are also attracting attention of all social circles. Therefore, how to realize safe operation, energy conservation and emission reduction of power equipment on the premise of meeting the requirements of power users is a technical problem which needs to be solved urgently at the present stage.
Disclosure of Invention
In order to solve the technical problems in the related art, the present disclosure provides an intelligent control data processing method and system for an electrical device.
In a first aspect, a method for processing intelligent control data of an electrical device is provided, the method including:
acquiring n electricity demand data of target power equipment, wherein one electricity demand data comprises safety index data and electricity consumption data in an electricity working state, and n is a positive integer;
acquiring log event distribution data of the equipment operation log data based on an operation state label and a power consumption state label of the equipment operation log data of the target power equipment in the power consumption demand data;
performing energy-saving state evaluation on log event distribution data of the equipment operation log data and a target event data set in a preset event database to generate first equipment power utilization strategy data;
sampling and acquiring node control logic data from a strategy process node of the first equipment power utilization strategy data, wherein the strategy process node is a node corresponding to equipment operation log data in the first equipment power utilization strategy data;
performing power utilization safety evaluation on the first equipment power utilization strategy data based on the running state label and the power consumption state label mapped in the power utilization demand data by the node control logic data, and generating second equipment power utilization strategy data of the target power equipment; intelligently controlling the target power equipment according to the second equipment power utilization strategy data; the second equipment power utilization strategy data comprises a corresponding user demand description curve, an energy-saving index description curve and a safety index description curve.
Optionally, the performing energy saving state evaluation on the log event distribution data of the device operation log data and a target event data set in a preset event database to generate first device power utilization policy data includes:
determining first energy-saving planning data according to log event distribution data of the equipment operation log data, wherein the first energy-saving planning data is used for determining the matching degree between the first equipment power utilization strategy data and the power utilization demand data of the target power equipment;
and based on the first energy-saving planning data, performing energy-saving state evaluation on a target event data set in the preset event database to generate first equipment power utilization strategy data.
Optionally, the determining first energy-saving planning data according to log event distribution data of the device operation log data includes:
constructing a first equipment operation characteristic matrix;
the first device operational characteristic matrix comprises a first current matrix element, a first voltage matrix element, and a first reactive power matrix element; the first current matrix element is used for indicating that the power utilization event requirement of the screened equipment operation log data in the first equipment power utilization strategy data meets the preset requirement of corresponding log event distribution data, the screened equipment operation log data refers to the equipment operation log data obtained after the equipment operation log data with unstable voltage state is removed, the first voltage matrix element is used for indicating that the power utilization safety index of the equipment operation log data in the first equipment power utilization strategy data meets the set index of the corresponding log event distribution data, and the first reactive power matrix element is used for enabling the compatibility weight of the first equipment power utilization strategy data to approach to a target weight interval;
determining first energy-saving planning data meeting energy-saving planning indexes based on log event distribution data of the equipment operation log data and the first equipment operation characteristic matrix; the energy-saving planning index comprises a maximum value of the characteristic weighted value of the first equipment operation characteristic matrix.
Optionally, before the constructing the first device operation feature matrix, the method further includes:
determining a voltage state stability curve corresponding to the equipment operation log data, and mapping the voltage state stability curve corresponding to the equipment operation log data into a preset coordinate plane according to log event distribution data of the equipment operation log data; the state index dimension of a voltage state stable curve of the equipment operation log data is superposed with the state index dimension of the preset coordinate plane;
acquiring a stability mapping value of a curve inflection point in a voltage state stable curve of the equipment operation log data in the preset coordinate plane;
and in response to the stability mapping value being lower than a stability preset value corresponding to the preset coordinate plane, removing the equipment operation log data corresponding to the corresponding curve inflection point of the stability mapping value to obtain the screened equipment operation log data.
Optionally, based on the first energy-saving planning data, performing energy-saving state evaluation on a target event data set in the preset event database, and generating the first device power utilization policy data includes:
determining an energy-saving current distribution queue, an energy-saving voltage distribution queue and an energy-saving reactive power distribution queue from the first energy-saving planning data; determining a first feature similarity between a first queue association feature corresponding to the energy-saving current distribution queue and a second queue association feature corresponding to the energy-saving voltage distribution queue and a second feature similarity between a second queue association feature corresponding to the energy-saving voltage distribution queue and a third queue association feature corresponding to the energy-saving reactive power distribution queue;
for the energy-saving current distribution queue, performing queue reconstruction on the energy-saving current distribution queue by taking the first queue association characteristic as a reference characteristic according to the first characteristic similarity to obtain a target current distribution queue; aiming at the energy-saving voltage distribution queue, performing queue reconstruction on the energy-saving voltage distribution queue by taking the second queue association characteristic as a reference characteristic according to the second characteristic similarity to obtain a target voltage distribution queue;
respectively carrying out queue correlation calculation on the energy-saving current distribution queue and the energy-saving voltage distribution queue, the energy-saving current distribution queue and the target current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue, and the energy-saving voltage distribution queue and the target voltage distribution queue to obtain first correlation data, second correlation data, third correlation data and fourth correlation data; determining a first correlation outlier between the first correlation data and the second correlation data and a second correlation outlier between the third correlation data and the fourth correlation data;
judging whether the first correlation abnormal value and the second correlation abnormal value are consistent with a set abnormal value or not; if so, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the third correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; if not, respectively determining a first difference value and a second difference value between the first correlation abnormal value and the set abnormal value and between the second correlation abnormal value and the set abnormal value; comparing the magnitude of the first difference and the second difference; when the first difference is smaller than the second difference, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the second correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; when the first difference is larger than the second difference, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the third correlation data and the fourth correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list;
and determining a power utilization event queue based on the energy-saving evaluation event list, and performing energy-saving state evaluation on the target event data set by adopting the power utilization event to obtain the first equipment power utilization strategy data.
Optionally, the performing, based on the running state tag and the power consumption state tag mapped in the power consumption demand data by the node control logic data, power consumption safety evaluation on the first device power consumption policy data to generate second device power consumption policy data of the target power device includes:
acquiring log event distribution data of the node control logic data based on an operation state label and a power consumption state label mapped in the power consumption demand data by the node control logic data;
determining second energy-saving planning data according to log event distribution data of the node control logic data, wherein the second energy-saving planning data is used for determining the matching degree between equipment power utilization strategy data of the target power equipment and power utilization demand data of the target power equipment;
and performing power utilization safety evaluation on the first equipment power utilization strategy data based on the second energy-saving planning data to generate second equipment power utilization strategy data of the target power equipment.
Optionally, the obtaining log event distribution data of the device operation log data based on the operation state tag and the power consumption state tag of the device operation log data of the target power device in the power consumption demand data includes:
acquiring an initial running state label and an initial power consumption state label of initial equipment running log data of the target power equipment in the power consumption demand data;
in response to that a target log parameter in the initial equipment operation log data is a dynamic log parameter and the target log parameter does not have a target power consumption state label, rejecting the target log parameter;
responding to that a target log parameter in the initial equipment operation log data is a non-dynamic log parameter and the target log parameter does not have a target operation state label, selecting a log parameter to be processed of the target power consumption state label corresponding to the target log parameter, and replacing the target log parameter;
and obtaining log event distribution data of the equipment operation log data based on the operation state label and the power consumption state label of the updated equipment operation log data in the power consumption demand data.
Optionally, the acquiring n power demand data of the target power device includes:
acquiring m electricity demand data of the target power equipment, wherein m is a positive integer larger than n;
extracting equipment operation log data of the target power equipment in safety index data;
determining the power utilization working state of the target power equipment in the safety index data according to the running state label of the equipment running log data of the target power equipment in the safety index data;
and selecting the n electricity demand data with the electricity working state meeting the working state requirement from the m electricity demand data.
Optionally, the intelligently controlling the target power device according to the second device power utilization policy data includes:
generating a user demand description curve, an energy-saving index description curve and a safety index description curve corresponding to the target power equipment in a set curve plane through the second equipment power utilization strategy data;
and scheduling the power utilization state of the target power equipment according to the regional distribution information of the curve intersection points among the user demand description curve, the energy-saving index description curve and the safety index description curve.
In a second aspect, an intelligent control data processing system for electrical equipment is provided, which comprises an equipment control server and electrical equipment, wherein the equipment control server is in communication connection with the electrical equipment; wherein the device control server is configured to:
acquiring n electricity demand data of target power equipment, wherein one electricity demand data comprises safety index data and electricity consumption data in an electricity working state, and n is a positive integer;
acquiring log event distribution data of the equipment operation log data based on an operation state label and a power consumption state label of the equipment operation log data of the target power equipment in the power consumption demand data;
performing energy-saving state evaluation on log event distribution data of the equipment operation log data and a target event data set in a preset event database to generate first equipment power utilization strategy data;
sampling and acquiring node control logic data from a strategy process node of the first equipment power utilization strategy data, wherein the strategy process node is a node corresponding to equipment operation log data in the first equipment power utilization strategy data;
performing power utilization safety evaluation on the first equipment power utilization strategy data based on the running state label and the power consumption state label mapped in the power utilization demand data by the node control logic data, and generating second equipment power utilization strategy data of the target power equipment; intelligently controlling the target power equipment according to the second equipment power utilization strategy data; the second equipment power utilization strategy data comprises a corresponding user demand description curve, an energy-saving index description curve and a safety index description curve.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.
The method and the device have the advantages that the log event distribution data of the device operation log data can be obtained based on the operation state label and the power consumption state label of the device operation log data of the target power device in the power consumption demand data, and further energy-saving state assessment and power consumption safety assessment of the log event distribution data are sequentially achieved, so that first device power consumption strategy data and second device power consumption strategy data are generated. In this way, the target power device can be intelligently controlled according to the second device power utilization strategy data. Because the second device power utilization strategy data comprises the corresponding user demand description curve, the energy-saving index description curve and the safety index description curve, when the target power equipment is intelligently controlled, the compatibility among the user demand, the power utilization safety and energy conservation and emission reduction can be considered, so that one-stop flow management of the target power equipment is realized, and the safe operation and the energy conservation and emission reduction of the power equipment can be realized on the premise of meeting the demands of power users.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow chart illustrating a method of intelligent control data processing for a power device in accordance with an exemplary embodiment;
FIG. 2 is an architecture diagram illustrating a power equipment intelligent control data processing system in accordance with an exemplary embodiment;
fig. 3 is a schematic diagram illustrating a hardware configuration of a device control server according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
In order to realize safe operation, energy conservation and emission reduction of power equipment on the premise of meeting the requirements of power users, the embodiment of the invention provides an intelligent control data processing method and system for the power equipment.
Referring first to fig. 1, a flowchart of a method for processing intelligent control data of an electrical device according to the present disclosure is shown, where the method can be implemented through the following steps S11-S15.
In step S11, n pieces of power demand data of the target power device are acquired.
For example, one power demand data includes safety index data and power consumption data in a power utilization working state, and n is a positive integer.
Step S12, obtaining log event distribution data of the device operation log data based on the operation state label and the power consumption state label of the device operation log data of the target power device in the power consumption demand data.
And step S13, performing energy-saving state evaluation on the log event distribution data of the device operation log data and a target event data set in a preset event database to generate first device power utilization strategy data.
And step S14, sampling and acquiring node control logic data from the policy flow node of the first equipment power utilization policy data.
For example, the policy process node refers to a node corresponding to device operation log data in the first device power utilization policy data.
Step S15, performing power consumption safety evaluation on the first device power consumption policy data based on the operation state label and the power consumption state label mapped in the power consumption demand data by the node control logic data, and generating second device power consumption policy data of the target power device; and intelligently controlling the target power equipment according to the power utilization strategy data of the second equipment.
For example, the second device power utilization policy data includes a corresponding user demand description curve, an energy saving index description curve, and a safety index description curve.
It can be understood that through the contents described in the above steps S11 to S15, log event distribution data of the device operation log data can be obtained based on the operation state tag and the power consumption state tag of the device operation log data of the target electrical device in the power demand data, and further energy saving state evaluation and power consumption safety evaluation on the log event distribution data are sequentially performed, so as to generate the first device power utilization policy data and the second device power utilization policy data. In this way, the target power device can be intelligently controlled according to the second device power utilization strategy data. Because the second device power utilization strategy data comprises the corresponding user demand description curve, the energy-saving index description curve and the safety index description curve, when the target power equipment is intelligently controlled, the compatibility among the user demand, the power utilization safety and energy conservation and emission reduction can be considered, so that one-stop flow management of the target power equipment is realized, and the safe operation and the energy conservation and emission reduction of the power equipment can be realized on the premise of meeting the demands of power users.
In some examples, the performing, by the step S13, the energy saving state evaluation on the log event distribution data of the device operation log data and the target event data set in the preset event database to generate the first device power utilization policy data may further include implementing, by the following step S131 and step S132.
Step S131, determining first energy-saving planning data according to log event distribution data of the equipment operation log data.
For example, the first energy saving plan data is used to determine a degree of matching between the first device electricity policy data and the electricity demand data of the target electrical device.
Step S132, based on the first energy-saving planning data, performs energy-saving state evaluation on the target event data set in the preset event database, and generates the first device power utilization policy data.
Therefore, the compatibility and balance between the user demand and energy conservation and emission reduction can be realized through the energy-saving state evaluation.
Further, on the basis of step S131, in order to ensure global stability of the first device operation characteristic matrix, determining the first energy-saving planning data according to the log event distribution data of the device operation log data, further includes what is described in the following steps: constructing a first equipment operation characteristic matrix; and determining the first energy-saving planning data meeting energy-saving planning indexes based on the log event distribution data of the equipment operation log data and the first equipment operation characteristic matrix.
In this embodiment, the first device operational characteristic matrix includes a first current matrix element, a first voltage matrix element, and a first reactive power matrix element; the first current matrix element is used for indicating that the power utilization event requirement of the screened device operation log data in the first device power utilization strategy data meets the preset requirement of corresponding log event distribution data, the screened device operation log data is the device operation log data obtained after the device operation log data with unstable voltage state is removed, the first voltage matrix element is used for indicating that the power utilization safety index of the device operation log data in the first device power utilization strategy data meets the set index of the corresponding log event distribution data, and the first reactive power matrix element is used for enabling the compatibility weight of the first device power utilization strategy data to approach to the target weight interval. The energy-saving planning index comprises a maximum value of the characteristic weighted value of the first equipment operation characteristic matrix. Therefore, the determined global stability of the first equipment operation characteristic matrix can be ensured through the energy-saving planning index.
Further, before constructing the first device operation feature matrix, the following may be included: determining a voltage state stability curve corresponding to the equipment operation log data, and mapping the voltage state stability curve corresponding to the equipment operation log data into a preset coordinate plane according to log event distribution data of the equipment operation log data; the state index dimension of a voltage state stable curve of the equipment operation log data is superposed with the state index dimension of the preset coordinate plane; acquiring a stability mapping value of a curve inflection point in a voltage state stable curve of the equipment operation log data in the preset coordinate plane; and in response to the stability mapping value being lower than a stability preset value corresponding to the preset coordinate plane, removing the equipment operation log data corresponding to the corresponding curve inflection point of the stability mapping value to obtain the screened equipment operation log data. By adopting the design, the device operation log data is screened, so that the device operation log data can be simplified, and the ratio of noise data of the device operation log data is reduced.
In a possible embodiment, the step S132 of performing energy saving state evaluation on the target event data set in the preset event database based on the first energy saving plan data to generate the first device electricity policy data may further include the following steps S1321 to S1325,
step S1321, determining an energy-saving current distribution queue, an energy-saving voltage distribution queue and an energy-saving reactive power distribution queue from the first energy-saving planning data; and determining a first feature similarity between a first queue association feature corresponding to the energy-saving current distribution queue and a second queue association feature corresponding to the energy-saving voltage distribution queue and a second feature similarity between a second queue association feature corresponding to the energy-saving voltage distribution queue and a third queue association feature corresponding to the energy-saving reactive power distribution queue.
Step S1322, performing queue reconstruction on the energy-saving current distribution queue according to the first feature similarity with respect to the energy-saving current distribution queue using the first queue-related feature as a reference feature to obtain a target current distribution queue; and for the energy-saving voltage distribution queue, performing queue reconstruction on the energy-saving voltage distribution queue by taking the second queue association characteristic as a reference characteristic according to the second characteristic similarity to obtain a target voltage distribution queue.
Step S1323, performing queue correlation calculation on the energy-saving current distribution queue and the energy-saving voltage distribution queue, the energy-saving current distribution queue and the target current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue, and the energy-saving voltage distribution queue and the target voltage distribution queue respectively to obtain first correlation data, second correlation data, third correlation data and fourth correlation data; determining a first correlation outlier between the first correlation data and the second correlation data and a second correlation outlier between the third correlation data and the fourth correlation data.
Step S1324 of determining whether or not both the first correlation abnormal value and the second correlation abnormal value match a set abnormal value; if so, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the third correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; if not, respectively determining a first difference value and a second difference value between the first correlation abnormal value and the set abnormal value and between the second correlation abnormal value and the set abnormal value; comparing the magnitude of the first difference and the second difference; when the first difference is smaller than the second difference, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the second correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; when the first difference is larger than the second difference, determining an energy-saving evaluation index list for performing energy-saving state evaluation on the target event data set according to the third correlation data and the fourth correlation data, and performing queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list.
Step S1325, determining a power utilization event queue based on the energy-saving evaluation event list, and performing energy-saving state evaluation on the target event data set by using the power utilization event to obtain the first equipment power utilization strategy data.
It can be understood that, by executing the steps S1321 to S1325, the energy-saving current distribution queue, the energy-saving voltage distribution queue, and the energy-saving reactive power distribution queue can be determined from the first energy-saving planning data, so that the energy-saving state can be evaluated three-dimensionally based on the energy-saving current distribution queue, the energy-saving voltage distribution queue, and the energy-saving reactive power distribution queue, and thus the energy-saving state can be comprehensively evaluated based on three aspects of current, voltage, and reactive power, so that it can be ensured that the first device power utilization policy data can be highly compatible with the user requirements and the energy-saving emission reduction requirements.
In some examples, in step S15, the power utilization safety evaluation is performed on the first device power utilization policy data based on the operation status tag and the power consumption status tag mapped in the power demand data by the node control logic data, and second device power utilization policy data of the target power device is generated, which further includes the contents described in the following steps S151 to S153.
Step S151, obtaining log event distribution data of the node control logic data based on the running state label and the power consumption state label mapped by the node control logic data in the power consumption demand data.
Step S152, determining second energy-saving planning data according to the log event distribution data of the node control logic data, where the second energy-saving planning data is used to determine a matching degree between the device power utilization policy data of the target power device and the power utilization demand data of the target power device.
Step S153, based on the second energy-saving planning data, performing power consumption safety evaluation on the first device power consumption policy data, and generating second device power consumption policy data of the target power device.
Therefore, the second equipment power utilization strategy data can be compatible with user requirements, power utilization safety requirements and energy conservation and emission reduction requirements.
It can be understood that, because the power consumption safety evaluation is performed on the first device power consumption policy data based on the second energy-saving planning data, and an implementation manner of generating the second device power consumption policy data of the target power device is similar to that of generating the first device power consumption policy data by performing the energy-saving state evaluation on the target event data set in the preset event database based on the first energy-saving planning data described in step S132, the implementation manner is not described herein again.
Further, the acquiring of the log event distribution data of the device operation log data based on the operation status label and the power consumption status label of the device operation log data of the target electrical power device in the power demand data, which is described in step S12, may exemplarily include the following contents described in step S221 to step S124.
Step S121, acquiring an initial operating state tag and an initial power consumption state tag of the initial device operating log data of the target power device in the power consumption demand data.
Step S122, in response to that the target log parameter in the initial device operation log data is a dynamic log parameter and the target log parameter does not have a target power consumption state label, rejecting the target log parameter.
Step S123, in response to that the target log parameter in the initial device operation log data is a non-dynamic log parameter and the target log parameter does not have a target operation state tag, selecting a to-be-processed log parameter having a target power consumption state tag corresponding to the target log parameter, and replacing the target log parameter.
Step S124, obtaining log event distribution data of the device operation log data based on the operation state label and the power consumption state label of the updated device operation log data in the power consumption demand data.
When the contents described in the above steps S121 to S124 are applied, the timeliness of the log event distribution data of the device operation log data can be ensured by the operation status tag and the power consumption status tag, and the log event distribution data can be prevented from being derailed from the actual operation status of the target power device.
In one possible example, the acquiring of the n electricity demand data of the target power device described in step S11 may include: acquiring m electricity demand data of the target power equipment, wherein m is a positive integer larger than n; extracting equipment operation log data of the target power equipment in safety index data; determining the power utilization working state of the target power equipment in the safety index data according to the running state label of the equipment running log data of the target power equipment in the safety index data; and selecting the n electricity demand data with the electricity working state meeting the working state requirement from the m electricity demand data. In this way, it can be ensured that the obtained electricity demand data is highly correlated with the electricity demand of the user.
In one example, the intelligent control of the target power device according to the second device power policy data in step S15 may further include the following steps: generating a user demand description curve, an energy-saving index description curve and a safety index description curve corresponding to the target power equipment in a set curve plane through the second equipment power utilization strategy data; and scheduling the power utilization state of the target power equipment according to the regional distribution information of the curve intersection points among the user demand description curve, the energy-saving index description curve and the safety index description curve. Therefore, by analyzing the user demand description curve, the energy-saving index description curve and the curve intersection point between the safety index description curves, the compatibility among the user demand, the power utilization safety and the energy conservation and emission reduction can be considered, so that the one-stop flow management of the target power utilization equipment is realized, and the safe operation, the energy conservation and the emission reduction of the power equipment can be realized on the premise of meeting the demands of power users.
Based on the same inventive concept, please refer to fig. 2 in combination, which shows an architecture diagram of an intelligent control data processing system 200 for an electric power device, where the intelligent control data processing system 200 for an electric power device includes a device control server 100 and an electric power device 300, and the device control server 100 is communicatively connected to the electric power device 200; wherein the device control server 100 is configured to:
acquiring n electricity demand data of target power equipment, wherein one electricity demand data comprises safety index data and electricity consumption data in an electricity working state, and n is a positive integer;
acquiring log event distribution data of the equipment operation log data based on an operation state label and a power consumption state label of the equipment operation log data of the target power equipment in the power consumption demand data;
performing energy-saving state evaluation on log event distribution data of the equipment operation log data and a target event data set in a preset event database to generate first equipment power utilization strategy data;
sampling and acquiring node control logic data from a strategy process node of the first equipment power utilization strategy data, wherein the strategy process node is a node corresponding to equipment operation log data in the first equipment power utilization strategy data;
performing power utilization safety evaluation on the first equipment power utilization strategy data based on the running state label and the power consumption state label mapped in the power utilization demand data by the node control logic data, and generating second equipment power utilization strategy data of the target power equipment; intelligently controlling the target power equipment according to the second equipment power utilization strategy data; the second equipment power utilization strategy data comprises a corresponding user demand description curve, an energy-saving index description curve and a safety index description curve.
It is to be understood that the description of the system embodiment refers to the description of the method embodiment shown in fig. 1.
Based on the same inventive concept as above, please refer to fig. 3 in conjunction, which shows a hardware structure diagram of the device control server 100, the device control server 100 includes a processor 110 and a memory 120 communicating with each other. The processor 110 implements the method shown in fig. 1 by retrieving the computer program from the memory 120 and running it.
In summary, the method and system for processing the intelligent control data of the power equipment disclosed by the disclosure can determine the log event distribution data of the target power equipment, which is used for acquiring the equipment operation log data, and further sequentially realize energy-saving state evaluation and power utilization safety evaluation on the log event distribution data, so that the power utilization policy data of the first equipment and the power utilization policy data of the second equipment are generated. In this way, the target power device can be intelligently controlled according to the second device power utilization strategy data. Because the second device power utilization strategy data comprises the corresponding user demand description curve, the energy-saving index description curve and the safety index description curve, when the target power equipment is intelligently controlled, the compatibility among the user demand, the power utilization safety and energy conservation and emission reduction can be considered, so that one-stop flow management of the target power equipment is realized, and the safe operation and the energy conservation and emission reduction of the power equipment can be realized on the premise of meeting the demands of power users.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. An intelligent control data processing method for electric power equipment is characterized by comprising the following steps:
acquiring n electricity demand data of target power equipment, wherein one electricity demand data comprises safety index data and electricity consumption data in an electricity working state, and n is a positive integer;
acquiring log event distribution data of the equipment operation log data based on an operation state label and a power consumption state label of the equipment operation log data of the target power equipment in the power consumption demand data;
performing energy-saving state evaluation on log event distribution data of the equipment operation log data and a target event data set in a preset event database to generate first equipment power utilization strategy data;
sampling and acquiring node control logic data from a strategy process node of the first equipment power utilization strategy data, wherein the strategy process node is a node corresponding to equipment operation log data in the first equipment power utilization strategy data;
performing power utilization safety evaluation on the first equipment power utilization strategy data based on the running state label and the power consumption state label mapped in the power utilization demand data by the node control logic data, and generating second equipment power utilization strategy data of the target power equipment; intelligently controlling the target power equipment according to the second equipment power utilization strategy data; the second equipment power utilization strategy data comprises a corresponding user demand description curve, an energy-saving index description curve and a safety index description curve.
2. The method of claim 1, wherein the performing energy saving state evaluation on the log event distribution data of the device operation log data and a target event data set in a preset event database to generate first device power utilization policy data comprises:
determining first energy-saving planning data according to log event distribution data of the equipment operation log data, wherein the first energy-saving planning data is used for determining the matching degree between the first equipment power utilization strategy data and the power utilization demand data of the target power equipment;
and based on the first energy-saving planning data, performing energy-saving state evaluation on a target event data set in the preset event database to generate first equipment power utilization strategy data.
3. The method of claim 2, wherein determining the first energy saving planning data according to the log event distribution data of the device operation log data comprises:
constructing a first equipment operation characteristic matrix;
the first device operational characteristic matrix comprises a first current matrix element, a first voltage matrix element, and a first reactive power matrix element; the first current matrix element is used for indicating that the power utilization event requirement of the screened equipment operation log data in the first equipment power utilization strategy data meets the preset requirement of corresponding log event distribution data, the screened equipment operation log data refers to the equipment operation log data obtained after the equipment operation log data with unstable voltage state is removed, the first voltage matrix element is used for indicating that the power utilization safety index of the equipment operation log data in the first equipment power utilization strategy data meets the set index of the corresponding log event distribution data, and the first reactive power matrix element is used for enabling the compatibility weight of the first equipment power utilization strategy data to approach to a target weight interval;
determining first energy-saving planning data meeting energy-saving planning indexes based on log event distribution data of the equipment operation log data and the first equipment operation characteristic matrix; the energy-saving planning index comprises a maximum value of the characteristic weighted value of the first equipment operation characteristic matrix.
4. The method of claim 3, wherein before constructing the first device operational feature matrix, further comprising:
determining a voltage state stability curve corresponding to the equipment operation log data, and mapping the voltage state stability curve corresponding to the equipment operation log data into a preset coordinate plane according to log event distribution data of the equipment operation log data; the state index dimension of a voltage state stable curve of the equipment operation log data is superposed with the state index dimension of the preset coordinate plane;
acquiring a stability mapping value of a curve inflection point in a voltage state stable curve of the equipment operation log data in the preset coordinate plane;
and in response to the stability mapping value being lower than a stability preset value corresponding to the preset coordinate plane, removing the equipment operation log data corresponding to the corresponding curve inflection point of the stability mapping value to obtain the screened equipment operation log data.
5. The method of claim 2, wherein performing energy saving state evaluation on a target event data set in the preset event database based on the first energy saving plan data to generate the first device power utilization policy data comprises:
determining an energy-saving current distribution queue, an energy-saving voltage distribution queue and an energy-saving reactive power distribution queue from the first energy-saving planning data; determining a first feature similarity between a first queue association feature corresponding to the energy-saving current distribution queue and a second queue association feature corresponding to the energy-saving voltage distribution queue and a second feature similarity between a second queue association feature corresponding to the energy-saving voltage distribution queue and a third queue association feature corresponding to the energy-saving reactive power distribution queue;
for the energy-saving current distribution queue, performing queue reconstruction on the energy-saving current distribution queue by taking the first queue association characteristic as a reference characteristic according to the first characteristic similarity to obtain a target current distribution queue; aiming at the energy-saving voltage distribution queue, performing queue reconstruction on the energy-saving voltage distribution queue by taking the second queue association characteristic as a reference characteristic according to the second characteristic similarity to obtain a target voltage distribution queue;
respectively carrying out queue correlation calculation on the energy-saving current distribution queue and the energy-saving voltage distribution queue, the energy-saving current distribution queue and the target current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue, and the energy-saving voltage distribution queue and the target voltage distribution queue to obtain first correlation data, second correlation data, third correlation data and fourth correlation data; determining a first correlation outlier between the first correlation data and the second correlation data and a second correlation outlier between the third correlation data and the fourth correlation data;
judging whether the first correlation abnormal value and the second correlation abnormal value are consistent with a set abnormal value or not; if so, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the third correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; if not, respectively determining a first difference value and a second difference value between the first correlation abnormal value and the set abnormal value and between the second correlation abnormal value and the set abnormal value; comparing the magnitude of the first difference and the second difference; when the first difference is smaller than the second difference, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the first correlation data and the second correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list; when the first difference is larger than the second difference, determining an energy-saving evaluation index list for carrying out energy-saving state evaluation on the target event data set according to the third correlation data and the fourth correlation data, and carrying out queue fusion on the energy-saving current distribution queue, the energy-saving voltage distribution queue and the energy-saving reactive power distribution queue according to the energy-saving evaluation index list corresponding to the target event data set to obtain an energy-saving evaluation event list;
and determining a power utilization event queue based on the energy-saving evaluation event list, and performing energy-saving state evaluation on the target event data set by adopting the power utilization event queue to obtain the power utilization strategy data of the first equipment.
6. The method of claim 1, wherein the performing the power utilization safety assessment on the first device power utilization policy data based on the operating status label and the power consumption status label mapped in the power utilization demand data by the node control logic data, and generating the second device power utilization policy data of the target power device comprises:
acquiring log event distribution data of the node control logic data based on an operation state label and a power consumption state label mapped in the power consumption demand data by the node control logic data;
determining second energy-saving planning data according to log event distribution data of the node control logic data, wherein the second energy-saving planning data is used for determining the matching degree between equipment power utilization strategy data of the target power equipment and power utilization demand data of the target power equipment;
and performing power utilization safety evaluation on the first equipment power utilization strategy data based on the second energy-saving planning data to generate second equipment power utilization strategy data of the target power equipment.
7. The method according to any one of claims 1 to 6, wherein the obtaining of the log event distribution data of the device operation log data based on the operation status tag and the power consumption status tag of the device operation log data of the target electrical device in the power consumption demand data comprises:
acquiring an initial running state label and an initial power consumption state label of initial equipment running log data of the target power equipment in the power consumption demand data;
in response to that a target log parameter in the initial equipment operation log data is a dynamic log parameter and the target log parameter does not have a target power consumption state label, rejecting the target log parameter;
responding to that a target log parameter in the initial equipment operation log data is a non-dynamic log parameter and the target log parameter does not have a target operation state label, selecting a log parameter to be processed of the target power consumption state label corresponding to the target log parameter, and replacing the target log parameter;
and obtaining log event distribution data of the equipment operation log data based on the operation state label and the power consumption state label of the updated equipment operation log data in the power consumption demand data.
8. The method according to any one of claims 1 to 6, wherein the acquiring n electricity demand data of the target power device comprises:
acquiring m electricity demand data of the target power equipment, wherein m is a positive integer larger than n;
extracting equipment operation log data of the target power equipment in safety index data;
determining the power utilization working state of the target power equipment in the safety index data according to the running state label of the equipment running log data of the target power equipment in the safety index data;
and selecting the n electricity demand data with the electricity working state meeting the working state requirement from the m electricity demand data.
9. The method of claim 1, wherein intelligently controlling the target power device according to the second device power policy data comprises:
generating a user demand description curve, an energy-saving index description curve and a safety index description curve corresponding to the target power equipment in a set curve plane through the second equipment power utilization strategy data;
and scheduling the power utilization state of the target power equipment according to the regional distribution information of the curve intersection points among the user demand description curve, the energy-saving index description curve and the safety index description curve.
10. The intelligent control data processing system for the electric power equipment is characterized by comprising an equipment control server and the electric power equipment, wherein the equipment control server is in communication connection with the electric power equipment; wherein the device control server is configured to:
acquiring n electricity demand data of target power equipment, wherein one electricity demand data comprises safety index data and electricity consumption data in an electricity working state, and n is a positive integer;
acquiring log event distribution data of the equipment operation log data based on an operation state label and a power consumption state label of the equipment operation log data of the target power equipment in the power consumption demand data;
performing energy-saving state evaluation on log event distribution data of the equipment operation log data and a target event data set in a preset event database to generate first equipment power utilization strategy data;
sampling and acquiring node control logic data from a strategy process node of the first equipment power utilization strategy data, wherein the strategy process node is a node corresponding to equipment operation log data in the first equipment power utilization strategy data;
performing power utilization safety evaluation on the first equipment power utilization strategy data based on the running state label and the power consumption state label mapped in the power utilization demand data by the node control logic data, and generating second equipment power utilization strategy data of the target power equipment; intelligently controlling the target power equipment according to the second equipment power utilization strategy data; the second equipment power utilization strategy data comprises a corresponding user demand description curve, an energy-saving index description curve and a safety index description curve.
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| CN107947337A (en) * | 2016-10-12 | 2018-04-20 | 尼欧科技股份有限公司 | Power control unit based on ups system |
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