CN112783127A - Enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management system and method - Google Patents
Enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management system and method Download PDFInfo
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Abstract
The application discloses a comprehensive energy real-time optimization operation and maintenance management system and method for enterprise energy stations, which comprises the following steps: the data perception module acquires relevant operation data and equipment state information of energy stations from different sources, and when point-oriented alarm data are generated, the point-oriented alarm data are identified by the model base module to generate real-time equipment-oriented alarm data; and after reading the equipment parameter information and the preset fault rule base information, the diagnosis optimization module performs fault early warning analysis and equipment health diagnosis and sends an equipment optimization operation suggestion and an equipment operation and maintenance guidance suggestion. According to the invention, the traditional energy station operation and maintenance mode is changed through data perception, analog-to-digital fusion and diagnosis optimization, the passive management mode of regular inspection of the energy station operation and maintenance is changed into the pre-inspection mode of real-time analysis of field operation data and intelligent drive of operation and maintenance work, the fine management of daily operation and maintenance services of the energy station of an enterprise can be obviously enhanced, and the work efficiency of operation and maintenance personnel is effectively improved.
Description
Technical Field
The invention belongs to the technical field of comprehensive energy operation and maintenance management, and relates to a comprehensive energy real-time optimization operation and maintenance management system and method for an enterprise energy station.
Background
The enterprise energy supply is an engine for driving the normal operation of enterprises, the management capability of enterprise energy directly determines the benefit level of enterprise industry, and the demand for energy management is continuously increased no matter manufacturing enterprises, factories and public transportation industry enterprises which mainly drive energy or bank service enterprises which use energy as auxiliary support.
Energy management systems have been developed for a considerable time, from initial simple energy monitoring to comprehensive energy monitoring, optimization and coordination, with the user's expectations for energy management systems developing in parallel. The general enterprise park has a plurality of energy stations with scattered geographic positions, wherein the energy stations comprise energy stations for providing energy such as cold, heat, electricity, gas and the like, and the traditional operation and maintenance management system only comprises management on equipment information and operation and maintenance tasks and lacks real-time operation data management of the system and the equipment, so that operation and maintenance personnel cannot find out system abnormality in time, the operation and maintenance efficiency is low, and economic loss is caused.
Disclosure of Invention
In order to solve the defects in the prior art, the application provides a comprehensive energy real-time optimization operation and maintenance management system and method for an enterprise energy station, unified online management is performed on real-time operation data and operation and maintenance data related to equipment, real-time online diagnosis is performed on the equipment state, real-time operation and maintenance suggestions of the equipment are provided, the operation and maintenance efficiency of the energy station is improved, and support is provided for efficient operation and maintenance of the enterprise comprehensive energy station.
In order to achieve the above purpose, the invention adopts the following technical scheme:
an enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management system comprises a data sensing module, a model library module and a diagnosis and optimization module;
the data perception module is used for acquiring relevant operation data and equipment state information of the energy station from different sources through a data plug-in, converting the acquired various data into a format which can be recognized by a system after data alarm analysis is carried out on the acquired various data, and transmitting the data to the model base module;
the model library module is used for matching discrete data input by the data sensing module to corresponding model attributes, completing model mapping of the data, and forming an object-oriented data block with model attribute characteristics, so that the diagnosis optimization module can conveniently identify the data block;
and the diagnosis optimization module is used for performing fault early warning analysis and equipment health diagnosis according to the data block which is processed by the model library module and faces the equipment object and has the model attribute characteristics.
The invention further comprises the following preferred embodiments:
preferably, the energy station comprises an air compression system, an ice water system, a boiler system and a power distribution system,
the air compression system comprises an air compressor, an air storage tank, a suction dryer, a cooling tower and a filter;
the ice water system comprises a cooling tower, a cooling pump, an ice maker, a primary cooling pump, a secondary cooling pump, a water collector and a water separator;
the boiler system comprises a water softener, a soft water tank, a dechlorination water pump, a dechlorination device, a pressure pump, a water replenishing pump, a boiler and a steam distributing cylinder;
the power distribution system comprises a high-voltage cabinet, a transformer and a switch.
Preferably, the data perception module obtains real-time data from different SCADA systems and data of equipment-related static information sources through a SCADA data plug-in and a static data plug-in.
Preferably, the data acquired by the data perception module is divided into: metering data, telemetry data, operating condition data and event records;
the metering data includes: electricity amount, water flow, natural gas amount, heat and compressed air amount;
the telemetry data includes: three-phase line voltage, three-phase current, frequency, power factor, active power, reactive power, pressure and temperature;
the working condition data comprises: collecting operation, fault and standby information of a terminal, an intelligent meter and measurement and control equipment;
the event record comprises: and collecting events recorded by the terminal and the intelligent meter, wherein the events comprise time scales and event description information.
Preferably, the model library module models the equipment attributes, the space attributes, the time attributes, the environment attributes, the management attributes and the real-time attributes of the energy station and the contained equipment;
the device attributes include: name, model, power rating and life cycle;
the spatial attributes include: location, public area, floor, and room;
the time attributes include: season and available time period;
the environmental attributes include: humidity, temperature, illuminance and noise;
the management attributes include: users and managers;
the real-time attributes include: real-time power consumption, accumulated power consumption and start-stop time.
The invention also discloses an enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management method, which comprises the following steps:
the data perception module acquires relevant operation data and equipment state information of energy stations from different sources, and when the data perception module generates point-oriented alarm data, the data perception module generates real-time equipment-oriented alarm data through identification of the model base module;
and after reading the equipment parameter information and the preset fault rule base information, the diagnosis optimization module performs fault early warning analysis and equipment health diagnosis and sends an equipment optimization operation suggestion and an equipment operation and maintenance guidance suggestion.
Preferably, in the diagnosis optimization module, the system and equipment fault categories are divided into fault early warning, general fault and serious fault;
the fault early warning refers to general out-of-limit warning which does not affect normal operation and needs to focus on tracking attention and routing inspection;
the general fault is a fault which does not affect the normal operation of the main equipment of the system, and manual order dispatching and field inspection are needed;
the serious fault is a fault which affects the production safety and needs to be stopped for maintenance.
Preferably, the diagnosis optimization module performs fault early warning analysis, specifically:
taking the equipment as a monitoring unit, carrying out similarity analogy on parameter data of the equipment during historical faults, judging the out-of-limit condition of each index or counting key statistics related to the equipment, identifying the fault category according to a predefined judgment rule, and confirming and remarking if the fault is early-warned; if general faults occur, manual dispatching and field inspection are carried out; and if the fault is serious, stopping the machine for maintenance.
Preferably, the diagnosis optimization module performs equipment health diagnosis, specifically:
selecting equipment health influence factors from equipment parameters, calculating a health evaluation score of the equipment, and providing an equipment optimization operation suggestion for equipment operation and maintenance personnel, wherein the equipment optimization operation suggestion comprises the following steps:
step 1: configuring equipment health influence factors, weights of the health influence factors and operation and maintenance rules;
step 2: monitoring the change of the health influence factor and the change time period of the health influence factor in real time;
and step 3: periodically calculating the device health score Hi:
Hi＝∑fi(Zi)*Wi
in the formula:
wi is the weight of the ith health impact factor;
zi is the original value of the ith health impact factor;
(fi) (Zi) is a health assessment function of the ith health impact factor;
and 4, step 4: and providing equipment optimization operation suggestions for equipment operation and maintenance personnel according to the health influence factor change condition and the equipment health score.
Preferably, the step 1 of manually configuring the device health impact factor and the weight of the health impact factor includes:
selecting a health-affecting factor;
modifying the weight of each health influence factor, increasing and deleting the health influence factors, and configuring a reasonable interval of each health influence factor;
configuring upper and lower limits of equipment health values of each health influence factor;
the health assessment function of the health impact factor is modified.
The beneficial effect that this application reached:
according to the invention, the traditional energy station operation and maintenance mode is changed through data perception, analog-to-digital fusion and diagnosis optimization, the passive management mode of regular inspection of the energy station operation and maintenance is changed into the pre-inspection mode of real-time analysis of field operation data and intelligent drive of operation and maintenance work, the fine management of daily operation and maintenance services of the energy station of an enterprise can be obviously enhanced, and the work efficiency of operation and maintenance personnel is effectively improved.
Drawings
FIG. 1 is a structural diagram of a comprehensive energy real-time optimization operation and maintenance management system facing an enterprise energy station;
FIG. 2 is a flow chart of the comprehensive energy real-time optimization operation and maintenance management method for the enterprise energy station of the invention;
FIG. 3 is a flow chart of the diagnostic optimization module of the present invention for performing device health diagnostics.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
An enterprise energy station is a comprehensive energy supply station for providing cold, heat, electricity, gas and other energy sources for an enterprise, and an enterprise park generally has a plurality of distributed energy supply stations. The comprehensive energy implementation optimization operation and maintenance management system for the enterprise energy station takes the running states of an energy supply system and equipment as main management objects, and provides related functional support for daily inspection and operation and maintenance of operation and maintenance personnel.
As shown in FIG. 1, the comprehensive energy real-time optimization operation and maintenance management system for the enterprise energy station comprises a data sensing module, a model library module and a diagnosis optimization module;
the data perception module is used for acquiring relevant operation data and equipment state information of the energy station from different sources through a data plug-in, converting the acquired various data into a format which can be recognized by a system after data alarm analysis is carried out on the acquired various data, and transmitting the data to the model base module;
in specific implementation, the data perception module obtains real-time data from different SCADA systems and data of static information sources related to equipment through the SCADA data plug-in and the static data plug-in.
The data acquired by the data perception module are divided into: metering data, telemetry data, operating condition data and event records;
the metering data includes: energy metering data such as electricity quantity, water flow, natural gas quantity, heat quantity, compressed air quantity and the like;
the telemetry data includes: real-time information of measurement quantities such as three-phase line voltage, three-phase current, frequency, power factor, active power, reactive power, pressure, temperature and the like;
the working condition data comprises: collecting working condition information of operation, fault, standby and the like of a terminal, an intelligent meter and measurement and control equipment;
the event record comprises: collecting events recorded by a terminal and an intelligent meter, wherein the events comprise information such as time scales, event descriptions and the like; the recording event content is related to the terminal type.
The model base module is used for matching discrete data transmitted by the data sensing module to corresponding model attributes by the model base, wherein the matching from points to the model is completed according to the preset configuration, the model mapping of the data is completed, and an object-oriented data block with model attribute characteristics is formed, so that the diagnosis optimization module can conveniently identify the data block;
the model library module models the equipment attributes, the space attributes, the time attributes, the environment attributes, the management attributes and the real-time attributes of the energy station and the contained equipment;
the device attributes include: name, model, power rating and life cycle;
the spatial attributes include: location, public area, floor, and room;
the time attributes include: season and available time period;
the environmental attributes include: humidity, temperature, illuminance and noise;
the management attributes include: users and managers;
the real-time attributes include: real-time power consumption, accumulated power consumption and start-stop time.
And the data block which is processed by the model library module and is formed for the equipment object and has the model attribute characteristics is transmitted to the diagnosis optimization module.
The energy station comprises an air compression system, an ice water system, a boiler system and a power distribution system,
the air compression system comprises an air compressor, an air storage tank, a suction dryer, a cooling tower and a filter;
the ice water system comprises a cooling tower, a cooling pump, an ice maker, a primary cooling pump, a secondary cooling pump, a water collector and a water separator;
the boiler system comprises a water softener, a soft water tank, a dechlorination water pump, a dechlorination device, a pressure pump, a water replenishing pump, a boiler and a steam distributing cylinder;
the power distribution system comprises a high-voltage cabinet, a transformer and a switch.
And the diagnosis optimization module is used for performing fault early warning analysis and equipment health diagnosis according to the data block which is processed by the model library module and faces the equipment object and has the model attribute characteristics.
As shown in fig. 2, the method for integrated energy real-time optimization operation and maintenance management for enterprise energy stations of the present invention includes:
the data perception module acquires relevant operation data and equipment state information of energy stations from different sources, and generates real-time data facing equipment, such as equipment real-time alarm data, equipment real-time operation data, equipment real-time energy consumption data, equipment static information and equipment operation and maintenance data;
when the data perception module generates SCADA alarm data facing to points, the SCADA alarm data is identified by the model base module to generate real-time alarm data facing to equipment,
the diagnosis optimization module runs in a cycle mode periodically, supports message triggering, performs fault early warning analysis and equipment health diagnosis after reading equipment key parameter information and preset fault rule base information, and sends equipment optimization running suggestions and equipment operation and maintenance guide suggestions.
In specific implementation, system/device failures are classified as shown in table 1:
TABLE 1 hierarchical definition of System/Equipment failures
The diagnosis optimization module carries out fault early warning analysis, and specifically comprises the following steps:
taking the equipment as a monitoring unit, carrying out similarity analogy with historical failure parameter data of the equipment, judging the out-of-limit condition of each index or counting the related key statistics of the equipment by using the time, environment, load, duration, maintenance times and other factors before failure, identifying the failure category according to a predefined judgment rule, and confirming and remarking if the failure is early warned; if general faults occur, dispatching the order; and if the fault is serious, stopping the machine for maintenance.
As shown in fig. 3, the diagnosis optimization module performs equipment health diagnosis, specifically:
selecting equipment health influence factors from equipment parameters, such as states of key parameters including operation duration, maintenance times, serious alarm ratio, equipment energy efficiency ratio, operation efficiency and the like, calculating health evaluation scores of the equipment, and providing equipment optimization operation suggestions for equipment operation and maintenance personnel, wherein the equipment optimization operation suggestions comprise:
step 1: manually configuring equipment health influence factors, weights of the health influence factors and operation and maintenance rules;
the manual configuration of the equipment health impact factor comprises the following steps:
the system administrator can carry out health diagnosis configuration management, including modifying the weight of each factor, adding and deleting the health influence factors and configuring the reasonable interval of each health influence factor;
selecting health influence factors, such as equipment operation duration, maintenance times, overhaul times and whether key operation parameters are in a health range;
the weight of the health influence factor adopts a percentile mode;
configuring upper and lower limits of the equipment health value of each health influence factor, manually modifying, and recording modification reasons;
the health impact factor health assessment function is modified.
Step 2: monitoring the change of the health influence factor and the change time period of the health influence factor in real time;
and step 3: periodic calculation (daily/monthly) of device health score Hi:
Hi＝∑fi(Zi)*Wi
in the formula:
wi is the weight of the ith health impact factor;
zi is the original value of the ith health impact factor;
fi (Zi) is a health assessment function of the ith health impact factor.
And 4, step 4: and providing equipment optimization operation suggestions for equipment operation and maintenance personnel according to the health influence factor change condition and the equipment health score.
According to the invention, the traditional energy station operation and maintenance mode is changed through data perception, analog-to-digital fusion and diagnosis optimization, the passive management mode of regular inspection of the energy station operation and maintenance is changed into the pre-inspection mode of real-time analysis of field operation data and intelligent drive of operation and maintenance work, the fine management of daily operation and maintenance services of the energy station of an enterprise can be obviously enhanced, and the work efficiency of operation and maintenance personnel is effectively improved.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. The comprehensive energy real-time optimization operation and maintenance management system for the enterprise energy station comprises a data sensing module, a model library module and a diagnosis and optimization module, and is characterized in that:
the data perception module is used for acquiring relevant operation data and equipment state information of the energy station from different sources through a data plug-in, converting the acquired various data into a format which can be recognized by a system after data alarm analysis is carried out on the acquired various data, and transmitting the data to the model base module;
the model library module is used for matching discrete data input by the data sensing module to corresponding model attributes, completing model mapping of the data, and forming an object-oriented data block with model attribute characteristics, so that the diagnosis optimization module can conveniently identify the data block;
and the diagnosis optimization module is used for performing fault early warning analysis and equipment health diagnosis according to the data block which is processed by the model library module and faces the equipment object and has the model attribute characteristics.
2. The integrated energy real-time optimization operation and maintenance management system for the enterprise energy station as claimed in claim 1, wherein:
the energy station comprises an air compression system, an ice water system, a boiler system and a power distribution system,
the air compression system comprises an air compressor, an air storage tank, a suction dryer, a cooling tower and a filter;
the ice water system comprises a cooling tower, a cooling pump, an ice maker, a primary cooling pump, a secondary cooling pump, a water collector and a water separator;
the boiler system comprises a water softener, a soft water tank, a dechlorination water pump, a dechlorination device, a pressure pump, a water replenishing pump, a boiler and a steam distributing cylinder;
the power distribution system comprises a high-voltage cabinet, a transformer and a switch.
3. The integrated energy real-time optimization operation and maintenance management system for the enterprise energy station as claimed in claim 1, wherein:
the data perception module obtains real-time data from different SCADA systems and data of static information sources related to equipment through the SCADA data plug-in and the static data plug-in.
4. The integrated energy real-time optimization operation and maintenance management system for the enterprise energy station as claimed in claim 1, wherein:
the data acquired by the data perception module are divided into: metering data, telemetry data, operating condition data and event records;
the metering data includes: electricity amount, water flow, natural gas amount, heat and compressed air amount;
the telemetry data includes: three-phase line voltage, three-phase current, frequency, power factor, active power, reactive power, pressure and temperature;
the working condition data comprises: collecting operation, fault and standby information of a terminal, an intelligent meter and measurement and control equipment;
the event record comprises: and collecting events recorded by the terminal and the intelligent meter, wherein the events comprise time scales and event description information.
5. The integrated energy real-time optimization operation and maintenance management system for the enterprise energy station as claimed in claim 1, wherein:
the model library module models the equipment attributes, the space attributes, the time attributes, the environment attributes, the management attributes and the real-time attributes of the energy station and the contained equipment;
the device attributes include: name, model, power rating and life cycle;
the spatial attributes include: location, public area, floor, and room;
the time attributes include: season and available time period;
the environmental attributes include: humidity, temperature, illuminance and noise;
the management attributes include: users and managers;
the real-time attributes include: real-time power consumption, accumulated power consumption and start-stop time.
6. The real-time operation and maintenance management method for the integrated energy sources facing the enterprise energy source station of the real-time operation and maintenance management system for the integrated energy sources facing the enterprise energy source station, according to any one of claims 1 to 5, is characterized in that:
the method comprises the following steps:
the data perception module acquires relevant operation data and equipment state information of energy stations from different sources, and when point-oriented alarm data are generated, the point-oriented alarm data are identified by the model base module to generate real-time equipment-oriented alarm data;
and after reading the equipment parameter information and the preset fault rule base information, the diagnosis optimization module performs fault early warning analysis and equipment health diagnosis and sends an equipment optimization operation suggestion and an equipment operation and maintenance guidance suggestion.
7. The integrated energy real-time optimization operation and maintenance management method facing the enterprise energy station as claimed in claim 6, wherein:
in the diagnosis optimization module, system and equipment fault types are divided into fault early warning, general faults and serious faults;
the fault early warning refers to general out-of-limit warning which does not affect normal operation and needs to focus on tracking attention and routing inspection;
the general fault is a fault which does not affect the normal operation of the main equipment of the system, and manual order dispatching and field inspection are needed;
the serious fault is a fault which affects the production safety and needs to be stopped for maintenance.
8. The integrated energy real-time optimization operation and maintenance management method facing the enterprise energy station as claimed in claim 6, wherein:
the diagnosis optimization module carries out fault early warning analysis, and specifically comprises the following steps:
taking the equipment as a monitoring unit, carrying out similarity analogy on parameter data of the equipment during historical faults, judging the out-of-limit condition of each index or counting key statistics related to the equipment, identifying the fault category according to a predefined judgment rule, and confirming and remarking if the fault is early-warned; if general faults occur, manual dispatching and field inspection are carried out; and if the fault is serious, stopping the machine for maintenance.
9. The integrated energy real-time optimization operation and maintenance management method facing the enterprise energy station as claimed in claim 6, wherein:
the diagnosis optimization module carries out equipment health diagnosis, and specifically comprises the following steps:
selecting equipment health influence factors from equipment parameters, calculating a health evaluation score of the equipment, and providing an equipment optimization operation suggestion for equipment operation and maintenance personnel, wherein the equipment optimization operation suggestion comprises the following steps:
step 1: configuring equipment health influence factors, weights of the health influence factors and operation and maintenance rules;
step 2: monitoring the change of the health influence factor and the change time period of the health influence factor in real time;
and step 3: periodically calculating the device health score Hi:
Hi＝Σfi(Zi)*Wi
in the formula:
wi is the weight of the ith health impact factor;
zi is the original value of the ith health impact factor;
(fi) (Zi) is a health assessment function of the ith health impact factor;
and 4, step 4: and providing equipment optimization operation suggestions for equipment operation and maintenance personnel according to the health influence factor change condition and the equipment health score.
10. The integrated energy real-time optimization operation and maintenance management method for the enterprise energy station as claimed in claim 9, wherein:
step 1, the manual configuration of the equipment health influence factor and the weight of the health influence factor comprises the following steps:
selecting a health-affecting factor;
modifying the weight of each health influence factor, increasing and deleting the health influence factors, and configuring a reasonable interval of each health influence factor;
configuring upper and lower limits of equipment health values of each health influence factor;
the health assessment function of the health impact factor is modified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011637941.8A CN112783127B (en) | 2020-12-31 | 2020-12-31 | Enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202011637941.8A CN112783127B (en) | 2020-12-31 | 2020-12-31 | Enterprise energy station-oriented comprehensive energy real-time optimization operation and maintenance management system and method |
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