CN114977503B - Full-chain monitoring system and method for running state of integrated system - Google Patents

Full-chain monitoring system and method for running state of integrated system Download PDF

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Publication number
CN114977503B
CN114977503B CN202210625006.2A CN202210625006A CN114977503B CN 114977503 B CN114977503 B CN 114977503B CN 202210625006 A CN202210625006 A CN 202210625006A CN 114977503 B CN114977503 B CN 114977503B
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data
power generation
time sequence
equipment data
integrated system
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CN114977503A (en
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宋文涛
赵欣
张宁
李豹
***
辛振兴
王顺
夏文龙
杨明亮
王鸿才
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Cccc Mechanical & Electrical Engineering Co ltd
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Cccc Mechanical & Electrical Engineering Co ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00016—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00028—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment involving the use of Internet protocols
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/10—The dispersed energy generation being of fossil origin, e.g. diesel generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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Abstract

The application discloses a full-chain monitoring system and method for the running state of an integrated system, wherein the full-chain monitoring system comprises an industrial monitoring network module, a multi-energy device running parameter acquisition module, a cloud data reading and storage module and a power station multi-data monitoring and analyzing module, and the remote monitoring module comprises a remote terminal and a remote webpage monitoring interface which is arranged on the remote terminal and is based on an MVC architecture, so that real-time data of the running state of the integrated system of the power station is read and visually displayed. The application designs a data acquisition system based on an RS485 bus and a Modbus protocol, adopts a data display interface of an MVC architecture, realizes remote monitoring of power generation parameters of a hybrid energy power station, judges the performance analysis of the power station according to the power generation efficiency, and builds a device data prediction model to pre-judge device data, thereby pre-judging the operation state of the power station integrated system, performing advanced exception handling, and reducing the influence of abnormal operation.

Description

Full-chain monitoring system and method for running state of integrated system
Technical Field
The application relates to the technical field of system operation monitoring, in particular to a full-chain monitoring system and method for an integrated system operation state.
Background
In the face of the situation of energy shortage, low energy consumption, little pollution and sustainable development become the necessary way of development. In the global scope, the use of informatization means to realize energy conservation, efficiency enhancement, safety guarantee and the like has become a common knowledge of various countries. The energy resources along the roads in China have superior endowment but large form difference, and the road network relates to different operation scenes such as highland, mountain areas, deserts and the like, so that the development and utilization difficulty of renewable low-carbon energy along the roads are high, the ratio of the low-carbon energy in the total energy consumption of the roads is lower than 1%, and the self-consistent energy supply rate is low; the energy requirements of transportation, transportation and maintenance are multiple, space-time coupling is complex, and the low-carbon energy supply forms are various, so flexible conversion among various forms of energy is difficult, the intensive control difficulty of a self-consistent energy system is increased, and the energy utilization efficiency is low.
The system provides technical services such as monitoring, analysis, control, evaluation, maintenance and the like for users, integrates functions such as data acquisition and processing, operation monitoring, real-time analysis, information display and the like, and provides means for the users to monitor, control, schedule and optimize energy and operate and maintain equipment on the premise of ensuring network safety.
Disclosure of Invention
The application aims to provide a full-chain monitoring system and method for the running state of an integrated system, which are used for solving the technical problems that in the prior art, the construction scene of the monitoring system is single, the monitoring data are few, only the equipment power consumption data are detected, the energy conversion rate cannot be effectively reflected, the abnormal early warning can not be carried out on the integrated system of a power station, and hysteresis exists in abnormal processing.
In order to solve the technical problems, the application specifically provides the following technical scheme:
the full-chain monitoring system and method for the running state of the integrated system comprises an industrial monitoring network module, a multi-energy equipment running parameter acquisition module, a cloud data reading and storage module and a power station multi-data monitoring and analysis module,
the industrial monitoring network module comprises an RS485 bus, an SPS controller, a bidirectional inverter, an MPPT controller, a ZKM fan controller and an Emerson power distribution controller, wherein the SPS controller, the bidirectional inverter, the MPPT controller, the ZKM fan controller and the Emerson power distribution controller are all connected to the RS485 bus in a hanging mode to achieve data interaction with a plurality of energy devices;
the multi-energy device operation parameter acquisition module comprises a CPU chip, a register and an RS485 communication interface, wherein the CPU chip is electrically connected with the register and the RS485 communication interface, and the RS485 communication interface is in communication connection with the RS485 bus to form a parameter acquisition channel of the multi-energy device operation parameters so as to realize that the CPU chip obtains the operation parameters of a plurality of energy devices through the parameter acquisition channel and analyzes and stores the operation parameters into the register;
the cloud data reading and storing module comprises an Internet of things data access module, a cloud server and a cloud database, wherein a data acquisition program is arranged in the cloud server, and the multi-energy device operation parameter acquisition module, the Internet of things data access module, the cloud server and the cloud database are sequentially in communication connection so as to realize that the cloud server sends Modbus protocol through the data acquisition program to control a CPU chip to read data in a register, and the read data is subjected to data analysis and stored in the cloud database;
the power station multi-data monitoring analysis module comprises a power station integrated system running state analysis module and a remote monitoring module, wherein the remote monitoring module is in communication connection with the cloud data reading and storing module and the power station integrated system running state analysis module, the remote monitoring module comprises a remote terminal and a remote webpage monitoring interface which is arranged on the remote terminal and is based on an MVC architecture, so that real-time data of the power station integrated system running state are read and visually displayed, and the power station running analysis module comprises an energy data analysis module and a power station state pre-judging module so as to analyze a plurality of energy equipment data to obtain the power station integrated system running state.
As a preferred scheme of the application, the energy equipment comprises a solar array, an alternating current load array, a fan array, an oil engine array, a direct current load array and a storage battery, wherein the SPS controller is electrically connected with the solar array and the storage battery, the bidirectional inverter is electrically connected with the alternating current load array and the storage battery, the MPPT controller is electrically connected with the solar array and the storage battery, the ZKM fan controller is electrically connected with the fan array and the storage battery, the Emerson power distribution controller is electrically connected with the oil engine array, the direct current load array and the storage battery, and the solar array, the alternating current load array, the fan array, the oil engine array and the direct current load array are electrically connected with the storage battery.
As a preferred scheme of the application, the remote webpage monitoring interface comprises a data query display unit, an oil engine start-stop unit and an abnormality early warning unit, wherein the data query display unit is used for sending query instructions to a cloud database to read the generated energy, the generated voltage and the generated current in each solar array, each fan array and each oil engine array, monitoring the power consumption, the power consumption voltage and the generated current of each alternating current load array and each direct current load array, and storing the power quantity and the temperature data of the storage battery pack and displaying the power consumption, the power consumption voltage and the generated current by using a chart;
the organic start-stop unit is used for starting the oil machine matrix according to the total power generation amount and the total power consumption amount of the power station integrated system, wherein when the total power consumption amount is larger than the total power generation amount, the abnormal early warning unit can give an alarm and prompt that the oil machine matrix needs to be started to generate power, and when the total power generation amount is larger than or equal to the total power consumption amount, the oil machine matrix is closed to stop generating power.
As a preferable scheme of the application, the energy data analysis module comprises a wind-light power generation matrix generating capacity analysis unit, a wind-light power generation matrix generating efficiency analysis unit, an overall output quantity analysis unit and a power generation utilization rate analysis unit, wherein the wind-light power generation matrix generating capacity analysis unit is used for manufacturing a line graph according to generating capacity data of a 24-hour solar matrix and a fan matrix for each 1 hour so as to analyze generating capacity of solar energy and wind energy in different time periods, and the power generation matrix generating efficiency analysis unit is used for calculating solar matrix generating efficiency and fan generating efficiency, wherein a calculation formula of the solar matrix generating efficiency is as follows:
η light source ＝Q Light source /SH；
In which Q Light source The total power generation amount of the solar array is; s is the total area of the solar array; h is the total radiant quantity of solar energy;
the calculation formula of the power generation efficiency of the fan is as follows:
η wind power ＝Q Wind power /RVM；
In which Q Wind power The total power generation amount of the fan matrix is R, the radius of the blades, M, the number of the fans and V, the average wind speed;
the total output quantity analysis unit is used for counting the total power generation quantity of the power station integrated system, and the calculation formula of the total power generation quantity is as follows:
Q total (S) ＝Q Light source +Q Wind power +Q Oil (oil) ；
In which Q Total (S) To the total power generation, Q Oil (oil) The total power generation amount of the square matrix of the oil engine;
the power generation utilization rate analysis unit is used for counting the power generation utilization rate of the power station integrated system, and the calculation formula of the power generation utilization rate is as follows:
f＝Q load(s) /Q Total (S) ；
Wherein f is the power generation utilization rate, Q Load(s) The total power consumption of the alternating current load square matrix and the direct current load square matrix.
As a preferred embodiment of the present application, the present application provides a monitoring method of a full chain monitoring system according to an operation state of the integrated system, comprising the steps of:
step S1, the CPU chip sends a query instruction of data to the energy equipment through the parameter acquisition channel, equipment data conforming to the query instruction is returned to the CPU chip through the parameter acquisition channel after the energy equipment receives the query instruction, the CPU chip analyzes the data according to requirements after receiving the equipment data, and the analyzed equipment data is stored in a register;
step S2, the cloud server sends a Modbus protocol reading instruction to a CPU chip through a data acquisition program, the CPU chip receives the Modbus protocol reading instruction and then retrieves the device data stored in the register, the device data is returned to the cloud server through a corresponding Modbus code returning format, and the cloud server receives the device data, then performs data analysis and stores the analyzed device data in a cloud database;
and S3, the remote monitoring module sends a reading instruction to the cloud server, the cloud server receives the reading instruction and then invokes the equipment data stored in the cloud database to return to the remote monitoring module, the remote monitoring module transmits the equipment data to the power station operation analysis module after receiving the equipment data, the power station operation analysis module performs equipment data analysis after receiving the equipment data so as to pre-determine the operation state of the power station integrated system, and the pre-determination result is returned to the remote monitoring module to perform abnormal early warning and oil engine start-stop operation of the power station integrated system so as to realize remote control of the power station integrated system to ensure the stable operation of the power station integrated system.
In the step S2, when the CPU chip receives the read command of the Modbus protocol, the CPU chip performs CRC16 check on the read command to determine the format correctness of the read command.
As a preferred embodiment of the present application, in the step S3, the data reading method of the cloud server includes:
the data acquisition program operates and starts the cloud server and monitors the cloud server port, and waits for the remote terminal in the remote monitoring module to be connected through a remote webpage monitoring interface;
when the remote terminal is monitored to be accessed, the cloud server obtains the IP and the port of the corresponding DTU and starts to automatically send a reading instruction, and the cloud server sets 6min to send the reading instruction to the CPU chip once so as to read the cloud data corresponding to the equipment data storage value of the corresponding register;
after the equipment data are stored in the cloud database, the cloud server sends a completion instruction to the remote terminal, waits for a reading instruction of the remote terminal, and performs CRC16 check after receiving the reading instruction of the remote terminal.
As a preferable scheme of the application, after the remote monitoring module receives the device data, the device data is stored in a memory of the remote terminal, and the device data is displayed in real time by the data query display unit.
As a preferred solution of the present application, the power station operation analysis module performs device data analysis after receiving device data to implement pre-determination of an operation state of a power station integrated system, including:
extracting a set of front-end equipment data positioned on a front-end time sequence of current equipment data on a remote terminal, arranging the front-end equipment data and the current equipment data in the time sequence to obtain a set of operation analysis data, taking the time sequence in the set of operation analysis data as an input item of an LSTM neural network, taking the equipment data in the set of operation analysis data as an output item of the LSTM neural network, and carrying out network training by utilizing the LSTM neural network based on the input item and the output item to obtain an equipment data prediction model, wherein the function expression of the equipment data prediction model is as follows:
S＝LSTM(t)；
wherein S is a model identifier of the equipment data, t is a model identifier of the equipment data time sequence, and LSTM is a model identifier of the LSTM neural network;
selecting a rear time sequence of current equipment data, inputting the rear time sequence into an equipment data prediction model to obtain an equipment data prediction value of the rear time sequence, inputting the equipment data prediction value into an energy data analysis module for data analysis to obtain generating capacity, generating efficiency, total output and generating utilization rate of a wind-light generation matrix at different time periods in a power station integrated system at the rear time sequence, comparing the electric consumption of the power station integrated system at the rear time sequence with the generating capacity,
if the total power consumption at the rear time sequence is larger than the total power generation amount, judging that the power station integrated system at the rear time sequence is in a power generation abnormal state, and prompting the rear time sequence to start the oil engine matrix to start the oil engine for power generation at the current time sequence in advance through an abnormal early warning unit;
if the total power generation amount at the rear time sequence is larger than or equal to the total power consumption amount, judging that the power station integrated system at the rear time sequence is in a normal power generation state, and prompting the rear time sequence to close the oil engine matrix to stop the oil engine power generation at the current time sequence through the abnormal early warning unit;
the time sequence of the equipment data is the time sequence of the remote monitoring module receiving the equipment data.
As a preferable scheme of the application, the total power generation amount comprises the sum of the total power generation amount of a solar array, the total power generation amount of a fan array and the total power generation amount of an oil engine array, the total power consumption amount comprises the total power consumption amount of an alternating current load array and a direct current load array, the total power generation amount of the solar array is the sum of the power generation amounts of the solar arrays, the total power generation amount of the fan array is the sum of the power generation amounts of the fan arrays, the total power generation amount of the oil engine array is the sum of the power generation amounts of the oil engine arrays, the total power consumption amount of the alternating current load array is the sum of the power consumption amounts of the alternating current load arrays, and the total power consumption amount of the direct current load array is the sum of the power consumption amounts of the direct current load arrays.
Compared with the prior art, the application has the following beneficial effects:
according to the application, a data acquisition system based on an RS485 bus and a Modbus protocol is designed, and a data display interface of an MVC architecture is adopted, so that remote monitoring of power generation parameters of a hybrid energy power station is realized, an administrator can monitor the hybrid energy power station without being on a power generation site, and when wind and light energy is insufficient, an oil engine is started to provide electric quantity for loads, a cloud server can analyze and evaluate the generated energy of different power generation matrixes of the power station and different time periods according to the acquired data, judge the performance analysis of the power station according to the power generation efficiency, and construct a device data prediction model to pre-judge device data, thereby pre-judging the running state of the power station integrated system, performing advanced abnormal treatment and reducing the influence of abnormal running.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
FIG. 1 is a block diagram showing the overall structure of a full chain monitoring system according to an embodiment of the present application;
FIG. 2 is a detailed block diagram of a full chain monitoring system according to an embodiment of the present application;
fig. 3 is a flowchart of a data reading method of a cloud server according to an embodiment of the present application.
Reference numerals in the drawings are respectively as follows:
1-an industrial monitoring network module; 2-a multi-energy device operation parameter acquisition module; 3-cloud data reading and storing module; 4-a multi-data monitoring and analyzing module of the power station.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
As shown in fig. 1 and 2, the application provides a full chain monitoring system and method for an integrated system running state, comprising an industrial monitoring network module, a multi-energy device running parameter acquisition module, a cloud data reading and storage module and a power station multi-data monitoring and analysis module, wherein,
the industrial monitoring network module comprises an RS485 bus, an SPS controller, a bidirectional inverter, an MPPT controller, a ZKM fan controller and an Emerson power distribution controller, wherein the SPS controller, the bidirectional inverter, the MPPT controller, the ZKM fan controller and the Emerson power distribution controller are all hung on the RS485 bus to realize data interaction with a plurality of energy devices;
RS485 is one of the common communication modes in industrial sites, has the characteristics of good anti-noise interference, long transmission distance, capability of connecting a plurality of transceivers on a bus and the like, and meets the requirement of monitoring a multi-energy matrix for a power station integrated system containing mixed energy. The data of each energy matrix is collected by designing an RS485 port of the main control CPU chip and connecting the port with an industrial monitoring network and sending reading instructions of different controllers to the industrial monitoring network.
The multi-energy equipment operation parameter acquisition module comprises a CPU chip, a register and an RS485 communication interface, wherein the CPU chip is electrically connected with the register and the RS485 communication interface, and the RS485 communication interface is in communication connection with an RS485 bus to form a parameter acquisition channel of the multi-energy equipment operation parameters so as to realize that the CPU chip obtains the operation parameters of the multi-energy equipment through the parameter acquisition channel and analyzes and stores the operation parameters into the register;
because the data collection amount of the power station integrated system is large and the variety is multiple, the data is transmitted by adopting a Modbus communication protocol, the Modbus communication protocol is adopted as the Modbus communication protocol, the Modbus protocol is a master-slave communication protocol used for accessing the self-control equipment in the industrial control network, the self-control equipment and other equipment can freely communicate through the Modbus communication protocol, the Modbus protocol comprises ASCII, RTU, TCP and other modes, and the traditional RS232, RS422, RS485 and Ethernet transmission can be supported.
The cloud data reading and storing module comprises an Internet of things data access module, a cloud server and a cloud database, wherein a data acquisition program is arranged in the cloud server, and the multi-energy device operation parameter acquisition module, the Internet of things data access module, the cloud server and the cloud database are sequentially in communication connection so as to realize that the cloud server sends Modbus protocol through the data acquisition program to control a CPU chip to read data in a register, and the read data is subjected to data analysis and stored in the cloud database;
the software writing of the data acquisition program in the cloud server is completed by adopting the Net technology, and the data is stored in the SQL server database. The software writing is based on a B/S architecture, and the server side is designed to wait for the connection of the remote terminal.
The power station multi-data monitoring analysis module comprises a power station integrated system running state analysis module and a remote monitoring module, wherein the remote monitoring module is in communication connection with the cloud data reading and storing module and the power station integrated system running state analysis module, the remote monitoring module comprises a remote terminal and a remote webpage monitoring interface which is arranged on the remote terminal and is based on an MVC framework, so that real-time data of the power station integrated system running state are read and visually displayed, and the power station running analysis module comprises an energy data analysis module and a power station state pre-judging module so as to analyze a plurality of energy equipment data to obtain the power station integrated system running state.
Based on the remote webpage monitoring interface of the MVC architecture, an administrator can monitor the power station integrated system containing the hybrid energy without installing any software. And when the remote webpage monitoring interface enters the query interface and no operation is performed for 5min, the remote webpage monitoring interface automatically refreshes and queries the data of the power station once, so that the real-time performance of data display is ensured.
The energy equipment comprises a solar array, an alternating current load array, a fan array, an oil engine array, a direct current load array and a storage battery, wherein the SPS controller is electrically connected with the solar array and the storage battery, the bidirectional inverter is electrically connected with the alternating current load array and the storage battery, the MPPT controller is electrically connected with the solar array and the storage battery, the ZKM fan controller is electrically connected with the fan array and the storage battery, the Emerson power distribution controller is electrically connected with the oil engine array, the direct current load array and the storage battery, and the solar array, the alternating current load array, the fan array, the oil engine array and the direct current load array are electrically connected with the storage battery.
The remote webpage monitoring interface comprises a data query display unit, an oil engine start-stop unit and an abnormal early warning unit, wherein the data query display unit is used for sending query instructions to the cloud database to read the generated energy, the generated voltage and the generated current in each solar array, each fan array and each oil engine array, monitoring the power consumption, the power consumption voltage and the generated current of each alternating current load array and each direct current load array, and storing the power quantity and the temperature data of the storage battery pack and displaying the power consumption, the power consumption voltage and the generated current by using a chart;
the organic start-stop unit is used for starting and stopping the oil engine matrix according to the total power generation amount and the total power consumption amount of the power station integrated system, wherein when the total power consumption amount is larger than the total power generation amount, the abnormal early warning unit can give an alarm and prompt that the oil engine matrix needs to be started to generate power, and when the total power generation amount is larger than or equal to the total power consumption amount, the oil engine matrix is closed to stop generating power.
The energy data analysis module comprises a wind-light power generation matrix different-period generating capacity analysis unit, a wind-light power generation matrix generating efficiency analysis unit, a total output quantity analysis unit and a generating utilization rate analysis unit, wherein the wind-light power generation matrix different-period generating capacity analysis unit is used for manufacturing a line graph according to generating capacity data of a 24-hour solar matrix and a fan matrix every 1 hour a day so as to analyze generating capacity of solar energy and wind energy in different periods, the wind-light power generation matrix generating efficiency analysis unit is used for calculating solar matrix generating efficiency and fan generating efficiency, and a calculation formula of the solar matrix generating efficiency is as follows:
η light source ＝Q Light source /SH；
In which Q Light source The total power generation amount of the solar array is; s is the total area of the solar array; h is the total radiant quantity of solar energy;
the calculation formula of the fan power generation efficiency is as follows:
η wind power ＝Q Wind power /RVM；
In which Q Wind power The total power generation amount of the fan matrix is R, the radius of the blades, M, the number of the fans and V, the average wind speed;
the total output quantity analysis unit is used for counting the total power generation quantity of the power station integrated system, and the calculation formula of the total power generation quantity is as follows:
Q total (S) ＝Q Light source +Q Wind power +Q Oil (oil) ；
In which Q Total (S) To the total power generation, Q Oil (oil) The total power generation amount of the square matrix of the oil engine;
the power generation utilization rate analysis unit is used for counting the power generation utilization rate of the power station integrated system, and the calculation formula of the power generation utilization rate is as follows:
f＝Q load(s) /Q Total (S) ；
Wherein f is the power generation utilization rate, Q Load(s) The total power consumption of the alternating current load square matrix and the direct current load square matrix.
The application provides a full chain monitoring system based on the running state of an integrated system, which comprises the following steps:
step S1, a CPU chip sends a query instruction of data to an energy device through a parameter acquisition channel, after the energy device receives the query instruction, the CPU chip returns device data conforming to the query instruction to the CPU chip through the parameter acquisition channel, and after receiving the device data, the CPU chip analyzes the data according to the requirement and stores the analyzed device data into a register;
step S2, the cloud server sends a Modbus protocol reading instruction to the CPU chip through the data acquisition program, the CPU chip receives the Modbus protocol reading instruction and then retrieves the device data stored in the register, the device data is returned to the cloud server through a corresponding Modbus code returning format, and the cloud server receives the device data, then performs data analysis and stores the analyzed device data in a cloud database;
in step S2, when the CPU chip receives the read command of the Modbus protocol, the CPU chip first performs CRC16 check on the read command to determine the format correctness of the read command.
The data are transmitted by using the Modbus communication protocol because the data collected by the hybrid energy power station are large in quantity and various. The query command format is shown in table 1.
Table 1RTU mode Modbus query command format
The cloud server sends a query instruction to the CPU chip, and when the CPU chip receives the instruction, the CPU chip firstly performs CRC16 check on the CPU chip to judge whether the format is correct, and queries the value in the corresponding register according to the instruction to obtain the data
Table 2RTU mode Modbus code return format
And returning the format of the return code to the cloud server. After receiving the return codes, the cloud server unpacks the return codes to obtain the data to be queried and stores the data into a corresponding cloud database. Its code back format is shown in table 2.
And S3, the remote monitoring module sends a reading instruction to the cloud server, the cloud server receives the reading instruction and then invokes the equipment data stored in the cloud database to return to the remote monitoring module, the remote monitoring module receives the equipment data and then transmits the equipment data to the power station operation analysis module, the power station operation analysis module receives the equipment data and then performs equipment data analysis to pre-determine the operation state of the power station integrated system, and a pre-determination result is returned to the remote monitoring module to perform abnormal early warning and oil engine start-stop operation of the power station integrated system so as to realize remote control of the power station integrated system to ensure stable operation of the power station integrated system.
As shown in fig. 3, in step S3, the data reading method of the cloud server includes:
the data acquisition program operates and starts the cloud server and monitors the cloud server port, and waits for the remote terminal in the remote monitoring module to be connected through a remote webpage monitoring interface;
when the remote terminal is monitored to be accessed, the cloud server obtains the IP and the port of the corresponding DTU and starts to automatically send a reading instruction, and the cloud server sets 6min to send the reading instruction to the CPU chip once so as to read the cloud data corresponding to the equipment data storage value of the corresponding register;
after the equipment data are stored in the cloud database, the cloud server sends a completion instruction to the remote terminal, waits for a reading instruction of the remote terminal, and performs CRC16 check after receiving the reading instruction of the remote terminal.
After the remote monitoring module receives the equipment data, the equipment data is stored in a memory of the remote terminal, and the data query display unit displays the equipment data in real time.
The power station operation analysis module performs equipment data analysis after receiving the equipment data to realize pre-determination of the operation state of the power station integrated system, and comprises the following steps:
extracting a set of front-end equipment data positioned on a front-end time sequence of current equipment data on a remote terminal, arranging the front-end equipment data and the current equipment data in the time sequence to obtain a set of operation analysis data, taking the time sequence in the set of operation analysis data as an input item of an LSTM neural network, taking the equipment data in the set of operation analysis data as an output item of the LSTM neural network, and carrying out network training by utilizing the LSTM neural network based on the input item and the output item to obtain an equipment data prediction model, wherein the function expression of the equipment data prediction model is as follows:
S＝LSTM(t)；
wherein S is a model identifier of the equipment data, t is a model identifier of the equipment data time sequence, and LSTM is a model identifier of the LSTM neural network;
selecting a rear time sequence of current equipment data, inputting the rear time sequence into an equipment data prediction model to obtain an equipment data prediction value of the rear time sequence, inputting the equipment data prediction value into an energy data analysis module to perform data analysis to obtain generating capacity, generating efficiency, total output and generating utilization rate of a wind-light generation matrix in a power station integrated system at the rear time sequence, comparing the power consumption and the generating capacity of the power station integrated system at the rear time sequence,
if the total electricity consumption at the rear time sequence is larger than the total electricity generation amount, judging that the power station integrated system at the rear time sequence is in an abnormal power generation state, and prompting a power station manager at the current time sequence in advance through an abnormal early warning unit that an oil engine matrix needs to be started to start oil engine for power generation;
if the total power generation amount at the rear time sequence is larger than or equal to the total power consumption amount, judging that the power station integrated system at the rear time sequence is in a normal power generation state, and prompting a power station manager to close the oil engine matrix at the rear time sequence in advance through an abnormal early warning unit to stop the oil engine power generation;
the method and the system realize that the running condition of the power station integrated system at the rear time sequence is predicted at the current time sequence, and early warning prompt is carried out on the manager at the current time sequence when the predicted position is abnormal, so that the manager is helped to carry out pre-adjustment before abnormal running occurs, and the influence caused by the abnormal running is reduced.
The time sequence of the equipment data is the time sequence of the remote monitoring module receiving the equipment data.
The total power generation amount comprises the total power generation amount of the solar square matrix, the total power generation amount of the fan square matrix and the total power generation amount of the oil engine square matrix, the total power consumption amount comprises the total power consumption amount of the alternating current load square matrix and the direct current load square matrix, the total power generation amount of the solar square matrix is the sum of the power generation amounts of the solar square matrixes, the total power generation amount of the fan square matrix is the sum of the power generation amounts of the fan square matrixes, the total power generation amount of the oil engine square matrix is the sum of the power generation amounts of the oil engine square matrixes, the total power consumption amount of the alternating current load square matrix is the sum of the power consumption amounts of the alternating current load square matrixes, and the total power consumption amount of the direct current load square matrix is the sum of the power consumption amounts of the direct current load square matrixes.
According to the application, a data acquisition system based on an RS485 bus and a Modbus protocol is designed, and a data display interface of an MVC architecture is adopted, so that remote monitoring of power generation parameters of a hybrid energy power station is realized, an administrator can monitor the hybrid energy power station without being on a power generation site, and when wind and light energy is insufficient, an oil engine is started to provide electric quantity for loads, a cloud server can analyze and evaluate the generated energy of different power generation matrixes of the power station and different time periods according to the acquired data, judge the performance analysis of the power station according to the power generation efficiency, and construct a device data prediction model to pre-judge device data, thereby pre-judging the running state of the power station integrated system, performing advanced abnormal treatment and reducing the influence of abnormal running.
The mixed energy power station remote monitoring system based on the Modbus protocol realizes remote and real-time monitoring of each power generation matrix parameter of the mixed energy power station. The long-term operation shows that the system is safe and reliable to operate and can quickly acquire the power station parameters. And the obtained data are analyzed and calculated to obtain the power generation efficiency, the generated energy of different periods and the utilization rate of the generated energy of the power station, so that a reliable basis is provided for the design of the hybrid energy power station and the distribution of each power generation matrix.
The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application, the scope of which is defined by the claims. Various modifications and equivalent arrangements of this application will occur to those skilled in the art, and are intended to be within the spirit and scope of the application.

Claims (9)

1. The utility model provides a full chain monitoring system of integrated system running state which characterized in that: comprises an industrial monitoring network module, a multi-energy equipment operation parameter acquisition module, a cloud data reading and storing module and a power station multi-data monitoring and analyzing module,
the industrial monitoring network module comprises an RS485 bus, an SPS controller, a bidirectional inverter, an MPPT controller, a ZKM fan controller and a power distribution controller, wherein the SPS controller, the bidirectional inverter, the MPPT controller, the ZKM fan controller and the power distribution controller are all hung on the RS485 bus to realize data interaction with a plurality of energy devices;
the multi-energy device operation parameter acquisition module comprises a CPU chip, a register and an RS485 communication interface, wherein the CPU chip is electrically connected with the register and the RS485 communication interface, and the RS485 communication interface is in communication connection with the RS485 bus to form a parameter acquisition channel of the multi-energy device operation parameters so as to realize that the CPU chip obtains the operation parameters of a plurality of energy devices through the parameter acquisition channel and analyzes and stores the operation parameters into the register;
the cloud data reading and storing module comprises an Internet of things data access module, a cloud server and a cloud database, wherein a data acquisition program is arranged in the cloud server, and the multi-energy device operation parameter acquisition module, the Internet of things data access module, the cloud server and the cloud database are sequentially in communication connection so as to realize that the cloud server sends Modbus protocol through the data acquisition program to control a CPU chip to read data in a register, and the read data is subjected to data analysis and stored in the cloud database;
the power station multi-data monitoring and analyzing module comprises a power station integrated system running state analyzing module and a remote monitoring module, wherein the remote monitoring module is in communication connection with the cloud data reading and storing module and the power station integrated system running state analyzing module, the remote monitoring module comprises a remote terminal and a remote webpage monitoring interface which is arranged on the remote terminal and is based on an MVC (model-view controller) framework, so that real-time data of the power station integrated system running state can be read and visually displayed, and the power station running analyzing module comprises an energy data analyzing module and a power station state pre-judging module, so that a plurality of energy equipment data can be analyzed to obtain the power station integrated system running state;
the power station operation analysis module performs equipment data analysis after receiving the equipment data to realize pre-determination of the operation state of the power station integrated system, and comprises the following steps:
extracting a set of front-end equipment data positioned on a front-end time sequence of current equipment data on a remote terminal, arranging the front-end equipment data and the current equipment data in the time sequence to obtain a set of operation analysis data, taking the time sequence in the set of operation analysis data as an input item of an LSTM neural network, taking the equipment data in the set of operation analysis data as an output item of the LSTM neural network, and carrying out network training by utilizing the LSTM neural network based on the input item and the output item to obtain an equipment data prediction model, wherein the function expression of the equipment data prediction model is as follows:
S＝LSTM(t)；
wherein S is a model identifier of the equipment data, t is a model identifier of the equipment data time sequence, and LSTM is a model identifier of the LSTM neural network;
selecting a rear time sequence of current equipment data, inputting the rear time sequence into an equipment data prediction model to obtain an equipment data prediction value of the rear time sequence, inputting the equipment data prediction value into an energy data analysis module for data analysis to obtain generating capacity, generating efficiency, total output and generating utilization rate of a wind-light generation matrix at different time periods in a power station integrated system at the rear time sequence, comparing the electric consumption of the power station integrated system at the rear time sequence with the generating capacity,
if the total power consumption at the rear time sequence is larger than the total power generation amount, judging that the power station integrated system at the rear time sequence is in a power generation abnormal state, and prompting the rear time sequence to start the oil engine matrix to start the oil engine for power generation at the current time sequence in advance through an abnormal early warning unit;
if the total power generation amount at the rear time sequence is larger than or equal to the total power consumption amount, judging that the power station integrated system at the rear time sequence is in a normal power generation state, and prompting the rear time sequence to close the oil engine matrix to stop the oil engine power generation at the current time sequence through the abnormal early warning unit;
the time sequence of the equipment data is the time sequence of the remote monitoring module receiving the equipment data.
2. The full chain monitoring system of an integrated system operating condition of claim 1, wherein: the energy equipment comprises a solar array, an alternating current load array, a fan array, an oil engine array, a direct current load array and a storage battery, wherein the SPS controller is electrically connected with the solar array and the storage battery, the two-way inverter is electrically connected with the alternating current load array and the storage battery, the MPPT controller is electrically connected with the solar array and the storage battery, the ZKM fan controller is electrically connected with the fan array and the storage battery, the power distribution controller is electrically connected with the oil engine array, the direct current load array and the storage battery, and the solar array, the alternating current load array, the fan array, the oil engine array and the direct current load array are electrically connected with the storage battery.
3. The full chain monitoring system of an integrated system operating condition of claim 2, wherein: the remote webpage monitoring interface comprises a data query display unit, an oil engine start-stop unit and an abnormality early warning unit, wherein the data query display unit is used for sending query instructions to the cloud database to read the generated energy, the generated voltage and the generated current in each solar array, each fan array and each oil engine array, monitoring the power consumption, the power consumption voltage and the generated current of each alternating current load array and each direct current load array, and displaying the stored energy and the temperature data of the storage battery by using a chart;
the oil engine start-stop unit is used for starting and stopping the oil engine matrix according to the total power generation amount and the total power consumption amount of the power station integrated system, wherein when the total power consumption amount is larger than the total power generation amount, the abnormal early warning unit can give an alarm and prompt that the oil engine matrix needs to be started to generate power, and when the total power generation amount is larger than or equal to the total power consumption amount, the oil engine matrix is closed to stop generating power.
4. A full chain monitoring system for an integrated system operating condition according to claim 3, wherein: the energy data analysis module comprises a wind-light power generation matrix different-period generating capacity analysis unit, a wind-light power generation matrix generating efficiency analysis unit, an overall output quantity analysis unit and a power generation utilization rate analysis unit, wherein the wind-light power generation matrix different-period generating capacity analysis unit is used for manufacturing a line graph according to generating capacity data of a 24h solar matrix and a fan matrix in every 1 hour so as to analyze generating capacity of solar energy and wind energy in different periods, and the wind-light power generation matrix generating efficiency analysis unit is used for calculating solar matrix generating efficiency and fan generating efficiency, wherein a calculation formula of the solar matrix generating efficiency is as follows:
η light source ＝Q Light source /SH；
In which Q Light source The total power generation amount of the solar array is; s is the total area of the solar array; h is the total radiant quantity of solar energy;
the calculation formula of the power generation efficiency of the fan is as follows:
η wind power ＝Q Wind power /RVM；
In which Q Wind power The total power generation amount of the fan matrix is R, the radius of the blades, M, the number of the fans and V, the average wind speed;
the total output quantity analysis unit is used for counting the total power generation quantity of the power station integrated system, and the calculation formula of the total power generation quantity is as follows:
Q total (S) ＝Q Light source +Q Wind power +Q Oil (oil) ；
In which Q Total (S) To the total power generation, Q Oil (oil) The total power generation amount of the square matrix of the oil engine;
the power generation utilization rate analysis unit is used for counting the power generation utilization rate of the power station integrated system, and the calculation formula of the power generation utilization rate is as follows:
f＝Q load(s) /Q Total (S) ；
Wherein f is the power generation utilization rate, Q Load(s) The total power consumption of the alternating current load square matrix and the direct current load square matrix.
5. A method of monitoring a full chain monitoring system for an operating condition of an integrated system according to any one of claims 1-4, comprising the steps of:
step S1, the CPU chip sends a query instruction of data to the energy equipment through the parameter acquisition channel, equipment data conforming to the query instruction is returned to the CPU chip through the parameter acquisition channel after the energy equipment receives the query instruction, the CPU chip analyzes the data according to requirements after receiving the equipment data, and the analyzed equipment data is stored in a register;
step S2, the cloud server sends a Modbus protocol reading instruction to a CPU chip through a data acquisition program, the CPU chip receives the Modbus protocol reading instruction and then retrieves the device data stored in the register, the device data is returned to the cloud server through a corresponding Modbus code returning format, and the cloud server receives the device data, then performs data analysis and stores the analyzed device data in a cloud database;
step S3, the remote monitoring module sends a reading instruction to the cloud server, the cloud server receives the reading instruction and then invokes equipment data stored in the cloud database to return to the remote monitoring module, the remote monitoring module receives the equipment data and then transmits the equipment data to the power station operation analysis module, the power station operation analysis module receives the equipment data and then performs equipment data analysis to pre-judge the operation state of the power station integrated system, and a pre-judging result is returned to the remote monitoring module to perform abnormal early warning and oil engine start-stop operation of the power station integrated system so as to realize remote control of the power station integrated system to ensure stable operation of the power station integrated system;
the power station operation analysis module performs equipment data analysis after receiving the equipment data to realize pre-determination of the operation state of the power station integrated system, and comprises the following steps:
extracting a set of front-end equipment data positioned on a front-end time sequence of current equipment data on a remote terminal, arranging the front-end equipment data and the current equipment data in the time sequence to obtain a set of operation analysis data, taking the time sequence in the set of operation analysis data as an input item of an LSTM neural network, taking the equipment data in the set of operation analysis data as an output item of the LSTM neural network, and carrying out network training by utilizing the LSTM neural network based on the input item and the output item to obtain an equipment data prediction model, wherein the function expression of the equipment data prediction model is as follows:
S＝LSTM(t)；
wherein S is a model identifier of the equipment data, t is a model identifier of the equipment data time sequence, and LSTM is a model identifier of the LSTM neural network;
selecting a rear time sequence of current equipment data, inputting the rear time sequence into an equipment data prediction model to obtain an equipment data prediction value of the rear time sequence, inputting the equipment data prediction value into an energy data analysis module for data analysis to obtain generating capacity, generating efficiency, total output and generating utilization rate of a wind-light generation matrix at different time periods in a power station integrated system at the rear time sequence, comparing the electric consumption of the power station integrated system at the rear time sequence with the generating capacity,
if the total power consumption at the rear time sequence is larger than the total power generation amount, judging that the power station integrated system at the rear time sequence is in a power generation abnormal state, and prompting the rear time sequence to start the oil engine matrix to start the oil engine for power generation at the current time sequence in advance through an abnormal early warning unit;
if the total power generation amount at the rear time sequence is larger than or equal to the total power consumption amount, judging that the power station integrated system at the rear time sequence is in a normal power generation state, and prompting the rear time sequence to close the oil engine matrix to stop the oil engine power generation at the current time sequence through the abnormal early warning unit;
the time sequence of the equipment data is the time sequence of the remote monitoring module receiving the equipment data.
6. The method of monitoring according to claim 5, wherein: in step S2, when the CPU chip receives the read command of the Modbus protocol, the CPU chip first performs CRC16 check on the read command to determine the format correctness of the read command.
7. The monitoring method according to claim 6, wherein in the step S3, the data reading method of the cloud server includes:
the data acquisition program operates and starts the cloud server and monitors the cloud server port, and waits for the remote terminal in the remote monitoring module to be connected through a remote webpage monitoring interface;
when the remote terminal is monitored to be accessed, the cloud server obtains the IP and the port of the corresponding DTU and starts to automatically send a reading instruction, and the cloud server sets 6min to send the reading instruction to the CPU chip once so as to read the cloud data corresponding to the equipment data storage value of the corresponding register;
after the equipment data are stored in the cloud database, the cloud server sends a completion instruction to the remote terminal, waits for a reading instruction of the remote terminal, and performs CRC16 check after receiving the reading instruction of the remote terminal.
8. The monitoring method according to claim 7, wherein the remote monitoring module stores the device data in a memory of the remote terminal after receiving the device data, and the device data is displayed in real time by the data query display unit.
9. The monitoring method according to claim 8, wherein the total power generation amount includes a total power generation amount of a solar array, a total power generation amount of a fan array, and a total power generation amount of an oil engine array, the total power consumption amount includes a total power consumption amount of an ac load array and a dc load array, the total power generation amount of the solar array is a sum of power generation amounts of the respective solar arrays, the total power generation amount of the fan array is a sum of power generation amounts of the respective fan arrays, the total power generation amount of the oil engine array is a sum of power generation amounts of the respective oil engine arrays, the total power consumption amount of the ac load array is a sum of power consumption amounts of the respective ac load arrays, and the total power consumption amount of the dc load array is a sum of power consumption amounts of the respective dc load arrays.
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