WO2021208313A1 - 一种供热、供电、制冷一体自然能源智慧系统及控制方法 - Google Patents

一种供热、供电、制冷一体自然能源智慧系统及控制方法 Download PDF

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WO2021208313A1
WO2021208313A1 PCT/CN2020/110205 CN2020110205W WO2021208313A1 WO 2021208313 A1 WO2021208313 A1 WO 2021208313A1 CN 2020110205 W CN2020110205 W CN 2020110205W WO 2021208313 A1 WO2021208313 A1 WO 2021208313A1
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control
change curve
intelligent
control node
module
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PCT/CN2020/110205
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English (en)
French (fr)
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胡泽锋
袁美强
冯乐
胡海胶
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内蒙古润泰新能源科技有限公司
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Priority to AU2020442839A priority Critical patent/AU2020442839B2/en
Publication of WO2021208313A1 publication Critical patent/WO2021208313A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/31—From computer integrated manufacturing till monitoring
    • G05B2219/31168—Use of node, sensor, actuator and control object
    • 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]

Definitions

  • the invention relates to the technical field of intelligent data control for heating, in particular to a natural energy intelligent system and control method integrated with heating, power supply and refrigeration.
  • the above-mentioned source-end system includes cold and heat dual-collection energy panels, heat pumps and solar collectors, etc.
  • the control nodes involved are generally as follows: the source-end system generally includes the pipeline between the source-end system and the energy conversion system
  • the valve control node on the above includes the device switch control node used to control the start and stop of the solar collector, the device switch control node that controls the above-mentioned heat pump, the inverter control node that performs variable-frequency control of the above-mentioned heat pump, etc.
  • the above-mentioned conventional control strategy is simply to determine whether the control node needs to be controlled based on the client's demand and the time node. Obviously, this control method is too simple and is not an advanced intelligent control technology.
  • the control method of the traditional control node is relatively simple and lacks systematic intelligent design. It is not conducive to scientific and big data management, and it is also not conducive to the development and promotion requirements of science and technology new energy technology big data advocated by the national science and technology department. . In summary, how to overcome the above-mentioned technical shortcomings in the traditional technology is a technical problem to be solved urgently by those skilled in the art.
  • the purpose of the present invention is to provide an integrated natural energy intelligent system and control method for heating, power supply, and cooling, which solves the above technical problems.
  • the present invention provides a natural energy intelligent system integrating heating, power supply, and cooling, including a source end system, an energy conversion system, an energy storage system, an end system, a heat preservation water tank system, and an intelligent control system, and also includes the intelligent control system.
  • the cloud computing control server for the system to establish a communication connection;
  • the source end system, the energy conversion system, the energy storage system, the end system, and the thermal insulation water tank system all include control nodes for controlling devices in their respective systems;
  • the cloud computing control server includes a source location acquisition module, a weather monitoring module, and a local download module.
  • the source location acquisition module is used to first obtain the location information of the source system, and then access the weather monitoring module and initiate a request in real time Retrieve the meteorological data at the source end system corresponding to the location information;
  • the meteorological monitoring module is configured to retrieve the meteorological data at the source end system according to the request, and obtain based on the future
  • the outdoor meteorological parameter change in the time period establishes the meteorological data change curve in the time series;
  • the local download module is used to transmit the meteorological data change curve to the local database of the intelligent control system for downloading and saving; the local The database is also used to pre-store the temperature high limit threshold and the light high limit threshold set by the intelligent control system;
  • the intelligent control system includes a local database, a control strategy determination module, and a meteorological data update trigger module; the intelligent control system is used to save the meteorological data change curve through a local database; the meteorological data includes light intensity prediction data and temperature prediction Data; the meteorological data change curve includes a temperature forecast change curve and a light intensity forecast change curve; the control strategy determination module of the intelligent control system combines the light intensity forecast change curve with the temperature forecast change curve to coordinate all controls The node determines the autonomous control strategy;
  • the meteorological data update trigger module is used to obtain the actual outdoor temperature data at the source end system of the source end temperature sensor in real time; the meteorological data update trigger module is used to obtain the actual light intensity at the source end system of the source end light sensor in real time Data; the meteorological data update trigger module is used to preset a high temperature threshold, and obtain the temperature data of the temperature forecast change curve at the corresponding time in real time; the meteorological data update trigger module is used to preset a high light threshold, in real time Obtain the light intensity data of the predicted change curve of light intensity at the corresponding time; the intelligent control system judges the difference between the value of the actual outdoor temperature data at the current time minus the value of the temperature data of the predicted temperature change curve at the corresponding time Whether it exceeds the upper threshold, if the judgment is yes, return to the weather monitoring module to update the meteorological data change curve, and coordinate the control strategy determination module to re-determine the autonomous control strategy for all control nodes; at the same time, the intelligent The control system judges whether the difference between the value of the actual
  • control nodes mainly include device switch control nodes, valve control nodes, inverter control nodes, and deployment angle control nodes.
  • the control strategy determination module is specifically configured to traverse all control nodes in the local database, and the intelligent control system specifically predicts the change curve and the light according to the temperature in the future time period Intensity prediction change curve, determine the control node that should be activated in the source system, and determine its activation value; determine the control node that should be activated in the energy conversion system, and determine its activation value; determine the energy storage system Determine the control node that should be activated, determine its activation value; determine the control node that should be activated in the terminal system, determine its activation value; determine the control node that should be activated in the thermal insulation water tank system, and determine its activation value;
  • the control strategy determination module is specifically further configured to be based on the startup information of all current control nodes in the source system, the energy conversion system, the energy storage system, the terminal system, and the thermal insulation water tank system at the current moment Integrate and compile the predictive sequential logic control diagrams of all the control nodes at the current moment and the start-up amount information of all the current control nodes, and finally compile the corresponding predictive sequential logic control diagrams in the future time period according to the time sequence. , Determine that it is a full sequential logic control diagram, and determine that the full sequential logic control diagram is an autonomous control strategy;
  • the meteorological data update trigger module is also specifically used to receive a setting request from the cloud computing control server, and then set the high temperature threshold and the high light threshold, and store them in the local database to facilitate the adjustment of the intelligent control system Pick.
  • control strategy determination module is further specifically configured to determine the cold and hot dual-receiving energy panel in the source system according to the predicted change curve of the wind speed index in the future time period The deployment angle of the control node's startup information and startup amount;
  • the wind pressure threshold of the cold and heat dual-receiving energy panel is designed to be that the start information of the deployment angle control node is turned on at this moment, and the start amount information of the deployment angle control node at this moment is that the deployment angle is 0.
  • the time is designed to be the start information of the expansion angle control node as closed
  • the activation amount information of the deployment angle control node is that the deployment angle is a preset angle
  • the predicted timing logic control diagram of the deployment angle control node at all times is integrated and compiled to form the control strategy of the deployment angle control node, and all The control strategy of the deployment angle control node is updated to the full sequential logic control diagram.
  • the intelligent control system further includes a management module, an abnormal control node monitoring module, and a control node update module, wherein:
  • the intelligent control system manages classification and numbering of the control nodes of the various equipment systems in real time through the management module, and determines the corresponding number of the control node to be executed according to the time sequence according to the full sequence logic control chart, if When the current time comes to a time sequence in the corresponding future time period, the number of the control node is identified, and the control node is called and controlled to perform the corresponding control operation;
  • the intelligent control system monitors the operating state of the control node through the abnormal control node monitoring module, analyzes and determines whether there is an abnormality in the operating state of the control node according to the results of the operating state, and obtains a control node monitoring report if so;
  • the intelligent control system uploads the abnormal control node to the local database to eliminate it through the control node update module, and reports the number of the abnormal control node to the cloud computing control server to provide the cloud computing control
  • the server publishes alarm maintenance information.
  • the client terminal further includes a display module and a storage module;
  • the storage module is used to obtain the continuously updated meteorological data in the intelligent control system in real time;
  • the display module is used to display the outdoor meteorological data change curve according to the meteorological data change curve;
  • the communication connection between the client and the intelligent control system is established through a communication module; the communication connection between the intelligent control system and all control nodes is also established through the communication module; the communication module includes Ethernet Module, WIFI module, Bluetooth module.
  • the present invention also provides an integrated natural energy intelligent control method for heating, power supply, and cooling (control method for short), which utilizes the integrated natural energy intelligent system for heating, power supply, and cooling to perform the following operation steps:
  • Step S10 The source-end location acquiring module of the cloud computing control server first acquires the location information of the source-end system, and then accesses the weather monitoring module and initiates a real-time request to retrieve the source-end system location corresponding to the location information Meteorological data;
  • Step S20 The meteorological monitoring module of the cloud computing control server retrieves the meteorological data at the source system according to the request, and obtains the establishment time based on the outdoor meteorological parameter change in the future time period according to the position information The change curve of meteorological data on the sequence;
  • Step S30 The cloud computing control server supplies the meteorological data change curve to the local intelligent control system for downloading and saving; the intelligent control system saves the meteorological data change curve through a local database; the meteorological data includes Light intensity forecast data and temperature forecast data; the meteorological data change curve includes a temperature forecast change curve and a light intensity forecast change curve;
  • Step S40 The intelligent control system coordinates all control nodes to determine an autonomous control strategy according to the predicted change curve of temperature and the predicted change curve of light intensity;
  • Step S50 The intelligent control system should also obtain the actual outdoor temperature data at the source end system of the source temperature sensor in real time; the intelligent control system should also obtain the actual light intensity data at the source end system of the source light sensor in real time.
  • the intelligent control system obtains the temperature data of the predicted temperature change curve at the corresponding time in real time; the intelligent control system obtains the light intensity data of the predicted light intensity change curve at the corresponding time in real time; the intelligent control system judges the current Whether the difference between the actual outdoor temperature data at the time minus the temperature data of the predicted temperature change curve at the corresponding time exceeds the upper limit threshold, if the judgment is yes, return to the meteorological monitoring module to update the meteorological data change curve, and coordinate Re-determine the autonomous control strategy for all control nodes; at the same time, the intelligent control system determines whether the difference between the actual outdoor light intensity data at the current moment minus the light intensity data of the light intensity forecast change curve at the corresponding time exceeds the If the high threshold is judged to be yes, return to the meteorological monitoring module to
  • the above-mentioned work platform of the integrated natural energy intelligent system for heating, power supply and cooling is actually a kind of integrated control node control platform of the Internet of Things combining software, hardware and control nodes. It collects meteorological data and predicts future meteorological dynamics based on the characteristics of meteorological data. Adjust the control parameters of the control node and give an autonomous control strategy based on the characteristics of the Internet of Things.
  • This is a time series temperature change model based on the outdoor meteorological parameter changes in a certain time period in the future, calculates and arranges the start state and start amount of the control nodes of each system part in the future time period, and develops an autonomous control strategy .
  • the meteorological data is changing.
  • the embodiment of the present invention can obtain the control method for predicting the control node of the meteorological change, and adjust the control method in the future period to make it adapt to the ever-changing work.
  • the environment achieves the technical purpose of intelligent management and control;
  • the technical solution of this embodiment assists the intelligent control system to implement scheduling and control plans for the control nodes of the source system and other system parts through outdoor weather data and other forecast information, thereby realizing intelligent autonomous control of big data.
  • FIG. 1 is a partial hardware system architecture diagram of a natural energy intelligent system integrating heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 2 is a schematic diagram of the control principle of the integrated natural energy intelligent system for heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 3 is a schematic diagram of a part of the control principle of the intelligent control system in the integrated natural energy intelligent system for heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 4 is a schematic diagram of the control principle of the cloud computing control server in the integrated natural energy smart system for heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 5 is a schematic diagram of another part of the control principle of the intelligent control system in the integrated natural energy intelligent system for heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 6 is a schematic diagram of the control principle of the client in the integrated natural energy intelligent system for heating, power supply, and cooling provided by an embodiment of the present invention
  • FIG. 7 is a flowchart of a natural energy intelligent control method integrating heating, power supply, and cooling provided by an embodiment of the present invention
  • Source end system 100 cold and hot dual-receiving energy board 101;
  • Energy storage system 300 heat storage 301; cold storage 302;
  • End system 400 client 401; display module 4011; storage module 4012; air conditioning output system 402; geothermal output system 403;
  • Insulation water tank system 500 Water storage tank 501;
  • Intelligent control system 600 local database 610; control strategy determination module 620; meteorological data update trigger module 630; management module 640; abnormal control node monitoring module 650; control node update module 660;
  • Cloud computing control server 700 source location acquisition module 710; weather monitoring module 720; local download module 730.
  • a natural energy intelligent system integrating heating, power supply, and cooling (abbreviated as natural energy intelligent system) is designed; the thicker connections between the intelligent control system and each system part in Figure 1 are pipelines , The thin wire connection between the intelligent control system and each system part is the control signal line (or control line); among them, Figure 1 is part of the heating, power supply, and cooling integrated natural energy intelligent system provided by the embodiment of the present invention Hardware system architecture diagram; Figure 2 is a schematic diagram of the control principle of the integrated natural energy smart system for heating, power supply, and cooling provided by an embodiment of the present invention.
  • the embodiment of the present invention provides a natural energy intelligent system integrating heating, power supply, and cooling.
  • the main control objects include the source end system 100, the energy conversion system 200, the energy storage system 300, and the end system 400.
  • the thermal insulation water tank system 500, the intelligent control system 600 (see Figures 3 and 5 for details), and the cloud computing control server 700, the specific system architecture schemes are as follows:
  • the above-mentioned intelligent control system 600 establishes a communication connection with the control nodes of each system part.
  • the intelligent control system 600 can be used to locally control each system part (including the source end system 100, the energy conversion system 200, the energy storage system 300, and the end system 400).
  • the source end system, energy conversion system, energy storage system, end system, and thermal insulation water tank system all include The control node used to control the equipment in the respective system;
  • the aforementioned cloud computing control server 700 includes a source location acquisition module 710, a weather monitoring module 720, and a local download module 730.
  • the source location acquisition module 710 is used to first acquire the location information of the source system. Then visit the meteorological monitoring module and initiate a request in real time to retrieve the meteorological data at the source system corresponding to the location information (that is, send the location information to the meteorological monitoring module at the same time);
  • the meteorological monitoring module 720 is used to retrieve the source system according to the request Meteorological data, and based on the location information to obtain the outdoor meteorological parameter changes in the future time period (for example, 3-24 hours in the future, in this embodiment, preferably 3 hours of setting parameters) to establish the weather on the time series Data change curve;
  • the local download module 730 is used to transmit the meteorological data change curve to the local database 610 of the intelligent control system 600 for downloading and saving;
  • the local database is also used to pre-store the high temperature threshold and the high light threshold set by the intelligent control system ;
  • the above-mentioned intelligent control system 600 includes a local database 610, a control strategy determination module 620, and a meteorological data update trigger module 630; the intelligent control system 600 is used to store the change curve of meteorological data through the local database; the meteorological data includes light intensity forecast data and temperature forecast data; The meteorological data change curve includes the temperature forecast change curve and the light intensity forecast change curve; the control strategy determination module 620 of the intelligent control system 600 combines the temperature forecast change curve and the light intensity forecast change curve to coordinate all control nodes to determine the autonomous control strategy (including Specifically, according to the predicted change curve of temperature and the predicted change curve of light intensity, implement the control operation according to the control node at a predetermined time, such as starting a certain device, preparing for heating at a certain time, and other autonomous control strategies); Note the above-mentioned autonomous control strategy
  • the control strategy is an autonomous control strategy.
  • the control strategy can be used as an overall control strategy or as an auxiliary control strategy; when used as an auxiliary control strategy, it can also specifically adjust the control method of a control node according to the client's request when the client requests instructions (it can be changed according to the client's request) Control strategy), the above autonomous control strategy does not affect the client's control of temperature adjustment, hot water supply adjustment, etc., and will not conflict with the requests sent by the client; note that the client's request priority can be greater than the above autonomous control Priority of control strategy;
  • the above-mentioned meteorological data update trigger module 630 is used to obtain the actual outdoor temperature data at the source end system of the source temperature sensor in real time; the meteorological data update trigger module 630 is used to obtain the actual light intensity data at the source end system of the source light sensor in real time ;
  • the meteorological data update trigger module presets the temperature upper limit threshold to obtain real-time temperature data of the temperature forecast change curve at the corresponding time; the meteorological data update trigger module presets the light upper limit threshold to obtain the light intensity forecast change curve at the corresponding time in real time Strong data;
  • the intelligent control system judges whether the difference between the value of the actual outdoor temperature data at the current moment minus the value of the temperature data of the temperature forecast change curve at the corresponding time exceeds the upper threshold, and if the judgment is yes, it returns to the weather monitoring module to update
  • the change curve of meteorological data is coordinated by the control strategy determination module to re-determine the autonomous control strategy for all control nodes; at the same time, the intelligent control system judges the value of the actual
  • the above-mentioned weather monitoring module can obtain the latest weather data change curve, but the weather data update trigger module needs to perform logical calculations and judgments, and finally decide whether to The weather monitoring module triggers the execution of subsequent control strategy update operations.
  • the above-mentioned working platform of the integrated natural energy smart system for heating, power supply, and cooling is actually an IoT integrated control node control platform that combines software, hardware, and control nodes.
  • the meteorological data predicts the future weather dynamics, adjusts the control parameters of the control node according to the characteristics of the meteorological data, and gives an autonomous control strategy according to the characteristics of the Internet of Things.
  • This is a time series temperature change model based on the outdoor meteorological parameter changes in a certain time period in the future (for example, within 3-24 hours), and calculate and arrange the startup status and startup of the control nodes of each system part in the future time period Quantity, develop an autonomous control strategy.
  • the auxiliary intelligent control system implements scheduling and control plans for the control nodes of the source system and other parts of the system, so as to realize the intelligent autonomous control of big data.
  • the types of the above-mentioned control nodes mainly include device switch control nodes, valve control nodes, frequency converter control nodes, deployment angle control nodes, and so on.
  • the control nodes in the aforementioned source system, end system, energy storage system, and energy conversion system are not completely limited to this. Other control nodes can be added as needed; generally speaking, the types of control nodes mentioned above mainly include device switches Control nodes, valve control nodes, equipment emergency stop control nodes, inverter control nodes, etc.; the control nodes involved in each of the above systems (ie source end system, end system, energy storage system, energy conversion system) are as follows illustrate.
  • the above-mentioned source-end system 100 is mainly composed of a solar collector including a cold-heat dual-collecting energy board 101 (referred to as energy board in Figure 1), a heat pump (not shown in the figure), and a source-end illumination sensor (Figure 1).
  • a solar collector including a cold-heat dual-collecting energy board 101 (referred to as energy board in Figure 1), a heat pump (not shown in the figure), and a source-end illumination sensor ( Figure 1).
  • the source end system is used to absorb solar heat at the source end through a cold and heat dual-receiving energy panel, and convert the absorbed solar energy into heat energy through a solar collector, and transfer it to the energy conversion system;
  • the source end system is used to absorb the air cooling energy at the source end through the cold and heat dual-receiving energy panel, and transfer the air cooling energy to the energy conversion system;
  • the control node of the source end system mainly involves: the source end system and energy The valve control node on the pipeline between the conversion systems, the expansion angle control node that controls the expansion angle of the above-mentioned cold and heat dual-receiving energy panels, the device switch control node used to control the start and stop of the solar collector, and the above The switch control node of the equipment that controls the heat pump, the inverter control node that controls the frequency conversion of the heat pump, etc.;
  • the main equipment of the above-mentioned energy conversion system 200 includes a conversion unit 201; the above-mentioned energy conversion system is used to receive the thermal energy or air-cooling energy supplied by the source end system when obtaining the first control command, and transmit it to the energy storage system or the end point The above-mentioned energy conversion system is also used to receive the thermal energy or air-cooling energy supplied by the energy storage system and transmit it to the end system when acquiring the second control command; generally speaking, the control node of the above-mentioned energy conversion system 200 also includes : ARM embedded control node (not shown in the figure) used to switch and control the transfer pump in the conversion unit, equipment switch control node (not shown in the figure) used to control the transfer pump of the conversion unit, A frequency converter control node (not shown in the figure) for the transfer pump of the conversion unit to perform frequency conversion control, etc.;
  • the above-mentioned energy storage system 300 includes other equipment (not shown in the figure) such as a heat storage 301 and a cold storage 302; the energy storage system is used to receive the thermal energy transmitted by the energy conversion system and store it in the heat storage. Call; the energy storage system is also used to receive the air-cooled energy transmitted by the energy conversion system and store it in the cold storage, and call it when needed; generally speaking, the energy storage system generally includes the pipeline between the energy storage system and the energy conversion system
  • the valve control node also includes a device switch control node (not shown in the figure) that controls the start and stop of the above-mentioned heat storage device, including equipment that controls the start and stop of the above-mentioned cold storage device Switch control node.
  • the energy storage system includes a device switch control node that controls the heat pump, and a frequency converter control node (not shown in the figure) that controls the heat pump.
  • the energy storage system 300 may also include phase change.
  • the above-mentioned terminal system 400 includes a client 401 (that is, a client installed in each user's home), an air conditioning output system 402 (main equipment includes fan coils or fan coils), and a geothermal output system 403 (main equipment includes floor heating) Coil);
  • the air-conditioning output system 402 is used to receive the heat energy or air-cooled energy transferred from the energy conversion system to heat or cool in the air-conditioning manner;
  • the geothermal output system 403 is used to receive the heat energy transferred from the energy conversion system Heat supply is realized by floor heating;
  • the air conditioning output system generally includes a valve control node (not shown in the figure) on the pipeline between the air conditioning output system and the energy conversion system, and also includes transmission to the above air conditioning output system
  • the device switch control node (not shown in the figure) that controls the start and stop of the pump, including the inverter control node (not shown in the figure) that performs variable frequency control on the delivery pump in the above-mentioned air-conditioning output system
  • the above-mentioned thermal insulation water tank system 500 includes a water storage tank 501 and a hot water delivery pump (not shown in the figure); the thermal insulation water tank system is used to receive the heated hot water delivered by the energy conversion system, store it in the water storage tank and release water supply; The pump can be used to deliver the hot water in the water storage tank to the shower head, etc.; generally speaking, the heat preservation water tank system generally includes a valve control node on the pipeline between the heat preservation water tank system and the energy conversion system, and the implementation of the hot water delivery pump. The device switch control node for shutdown control, the inverter control node for frequency conversion control of the hot water delivery pump, etc. (the control node is not shown in the figure).
  • valve control node is a network interconnected flow control valve control node; and the device switch control node, valve control node, inverter control node, expansion angle control node, ARM embedded control node are all available Communication network control node, and other control nodes may include air conditioning unit inverter control node, etc., geothermal unit inverter control node, etc. This invention will not be repeated one by one;
  • the above-mentioned control strategy determination module 620 is specifically used to traverse all control nodes in the local database 610, and the intelligent control system (the main control device of the intelligent control system is a high-performance computing processing chip) is specifically based on The temperature forecast change curve and the light intensity forecast change curve in the future time period, determine the control node that should be activated in the source system, and determine its activation value; determine the control node that should be activated in the energy conversion system, and determine its activation value; Determine the control node that should be activated in the energy storage system, and determine its activation value; determine the control node that should be activated in the end system, and determine its activation value; determine the control node that should be activated in the thermal insulation water tank system, and determine its activation value;
  • the above-mentioned control strategy determination module 620 is also specifically used to start information (including specific start-up information, such as Start or not start) and the start-up information of all current control nodes, integrate and compile the predictive sequential logic control diagrams of all control nodes at the current moment, and finally compile the corresponding predictive sequential logic control in the future time period according to the time sequence.
  • start information including specific start-up information, such as Start or not start
  • start-up information such as Start or not start
  • the start-up information of all current control nodes integrate and compile the predictive sequential logic control diagrams of all control nodes at the current moment, and finally compile the corresponding predictive sequential logic control in the future time period according to the time sequence.
  • Figure determine that it is a full sequential logic control diagram, and determine that the full sequential logic control diagram is an autonomous control strategy.
  • the meteorological data update trigger module 630 specifically receives a setting request from the cloud computing control server, and then sets the temperature high limit threshold and the light high limit threshold, and stores them in the local database to facilitate retrieval by the intelligent control system.
  • the startup information of the aforementioned control node generally includes specific startup information (such as startup or non-start), and the startup amount information of the control node generally includes control parameters, such as: general equipment switch control node startup amount information If no, the starting amount of the valve control node may involve flow control, valve opening control, etc.; in specific implementation, take the source system as an example, calculate a certain outdoor temperature prediction value and light intensity prediction value, and determine the source system Whether a certain device should be started or not, what is the amount of startup, so as to determine the control strategy of the control node of the device at a certain time, determine the startup information and startup amount of the control nodes of multiple devices, and finally compile it into a full sequential logic control diagram; forecast; The predicted value of temperature at a certain time (higher temperature) and predicted value of light intensity (higher light intensity).
  • big data can be used to analyze and determine that the current time is noon during the day.
  • the source system's cold and hot dual-receiving energy panel The start information of the valve control node of the hot water pipeline should be start, and the start amount can also be determined based on other factors; similarly, the start information of the deployment angle control node of the source system should be start, and the start amount information should be complete Unfold or unfold at a certain angle, such as 30 degrees -45 degrees, etc., so that the cold and heat dual-receiving energy panel can absorb solar energy in time.
  • the above-mentioned control strategy determination module 620 is also specifically configured to determine the expansion angle control node of the cooling and heating dual-receiving energy plate in the source system according to the predicted change curve of the wind speed index in the future time period. Start-up information and start-up volume;
  • the wind pressure threshold is designed to be the start information of the expansion angle control node at this time, and the start amount information of the expansion angle control node at this moment is that the expansion angle is 0 (that is, the cold and hot dual-receiving energy plate is controlled to be completely closed
  • the wind speed index value at a certain time in the future time period is less than or equal to the wind pressure threshold value of the cold and heat dual-receiving energy plate, then this time is designed as the expansion angle control node
  • the startup information of is closed (that is, not started) and the startup amount information of the expansion angle control node is the expansion angle is the preset angle (generally, the preset angle is 45 degrees); the expansion angle control node at all times is integrated and compiled
  • the above-mentioned intelligent control system 600 further includes a management module 640, an abnormal control node monitoring module 650, and a control node update module 660, where:
  • the above-mentioned intelligent control system manages classification and numbering of the control nodes of each equipment system in real time through the management module 640, and determines the corresponding control node number to be executed according to the time sequence according to the full sequence logic control chart. If the current time comes to the corresponding future time period Recognize the number of the control node at the time of the internal sequence, and call and control it to perform the corresponding control operation;
  • the above-mentioned intelligent control system monitors the operating state of the control node through the abnormal control node monitoring module 650, and analyzes and determines whether the operating state of the control node is abnormal according to the results of the operating state, and if so, obtains the control node monitoring report;
  • the above-mentioned intelligent control system uploads the abnormal control node to the local database to eliminate it through the control node update module 660, and reports the number of the abnormal control node to the cloud computing control server, and provides the cloud computing control server for the disclosure of alarm maintenance information.
  • the above-mentioned client 401 further includes a display module 4011 and a storage module 4012;
  • the above-mentioned storage module 4012 is used to obtain the continuously updated meteorological data in the intelligent control system in real time;
  • the above-mentioned display module 4011 is used to display the outdoor meteorological data change curve according to the meteorological data change curve (note: here is a forecast curve change, the above-mentioned intelligent control When the system is updated, the client will be updated, and the local call and transmission are more stable and faster);
  • the communication connection between the above-mentioned client and the intelligent control system is established through a communication module; the communication connection between the intelligent control system and all control nodes is also established through the communication module; the above-mentioned communication module (ie, the Internet of Things communication module) includes an Ethernet module , WIFI module, Bluetooth module.
  • the embodiment of the present invention also designs a natural energy intelligent control method integrated with heating, power supply, and cooling, including the following operation steps:
  • Step S10 The source location acquisition module of the cloud computing control server first acquires the location information of the source system, then accesses the meteorological monitoring module and initiates a request in real time to retrieve the meteorological data at the source system corresponding to the location information (that is, simultaneously The information is sent to the weather monitoring module);
  • Step S20 The meteorological monitoring module of the cloud computing control server retrieves the meteorological data at the source system according to the request, and obtains the establishment based on the change of outdoor meteorological parameters in the future time period (for example, the time range of 3-24 hours in the future) according to the location information Change curve of meteorological data in time series;
  • Step S30 The cloud computing control server supplies the meteorological data change curve to the local intelligent control system for downloading and saving; the intelligent control system saves the meteorological data change curve through the local database; the meteorological data includes the light intensity forecast data and the temperature forecast data; the meteorological data changes The curve includes the predicted change curve of temperature and the predicted change curve of light intensity;
  • Step S40 The intelligent control system coordinates all control nodes to determine an autonomous control strategy based on the temperature forecast change curve and the light intensity forecast change curve (including the specific temperature forecast change curve and the light intensity forecast change curve, and the implementation is based on a predetermined time. According to the control operation of the control node, such as starting a certain device, preparing for heating at a certain time and other autonomous control strategies);
  • Step S50 The intelligent control system should also obtain the actual outdoor temperature data at the source end system of the source temperature sensor in real time; the intelligent control system should also obtain the actual light intensity data at the source end system of the source light sensor in real time; the intelligent control system Obtain the temperature data of the predicted change curve of temperature at the corresponding time in real time; the intelligent control system obtains the light intensity data of the predicted change curve of light intensity at the corresponding time in real time; the intelligent control system judges the actual outdoor temperature data at the current time minus the predicted change of temperature at the corresponding time Whether the difference of the temperature data of the curve exceeds the upper limit threshold, if the judgment is yes, return to the meteorological monitoring module to update the meteorological data change curve, and coordinate to re-determine the autonomous control strategy for all control nodes; at the same time, the intelligent control system judges the current time Whether the difference between the actual outdoor light intensity data minus the light intensity data of the light intensity forecast change curve at the corresponding time exceeds the upper threshold, if the judgment is yes, return to the weather monitoring module to
  • step S40 the intelligent control system coordinates all the control nodes to determine the autonomous control strategy according to the temperature prediction change curve combined with the light intensity prediction change curve. Including the following steps:
  • Step S410 The intelligent control system traverses all control nodes in the local database.
  • the intelligent control system determines the control node that should be started in the source system according to the predicted change curve of temperature and the predicted change curve of light intensity in the future time period, and determines the amount of start-up. Numerical value; determine the control node that should be activated in the energy conversion system, and determine its activation value; determine the control node that should be activated in the energy storage system, and determine its activation value; determine the control node that should be activated in the end system, and determine its activation value Numerical value; determine the control node that should be activated in the thermal insulation water tank system, and determine its activation value;
  • the autonomous control strategy aims at the indoor temperature reaching within a predetermined range, and at the same time which equipment in each system part should be activated, and which equipment control nodes can be activated, specifically involving determining which control nodes in the source system should be activated , What is the starting amount, determining which control nodes in the energy conversion system should be started, how much is the starting amount, determining which control nodes in the energy storage system should be started, what is the starting amount, determining which control nodes in the end system should be started, and starting amount How much is it; for example: to determine which control nodes to start, how much to start is determined based on factors such as outdoor temperature, light intensity, etc., for example, according to weather data (light intensity data), you can know the time of day and the time of night, and then judge When is the proper time to start the cold and hot dual-receiving energy panels of the source system; after predicting the outdoor temperature based on meteorological data, if it can be considered whether the source system should absorb heat well or absorb cold
  • Step S420 The intelligent control system integrates and compiles the current start-up information of all current control nodes in the source system, energy conversion system, energy storage system, and end system at the current moment and the start-up information of all current control nodes.
  • the meteorological data update trigger module of the cloud computing control server further includes an operation to preset a high threshold, which specifically includes the following operation steps;
  • Step S510 The meteorological data update triggering module receives the setting request of the cloud computing control server, and then sets the temperature high limit threshold and the light high limit threshold, and stores them in the local database to facilitate retrieval by the intelligent control system.
  • the aforementioned meteorological data further includes wind speed index forecast data; and the meteorological data change curve also includes a wind speed index forecast change curve;
  • step S40 the intelligent control system also needs to consider predicting the change curve according to the wind speed index at the same time, and coordinate the control strategy of the expansion angle control node of the cooling and heating dual-receiving energy plate, which specifically includes the following operation steps:
  • Step S41 The intelligent control system determines the start-up information and start-up amount of the expansion angle control node of the cooling and heating dual-receiving energy plate in the source end system according to the predicted change curve of the wind speed index in the future time period;
  • the start information of the expansion angle control node is designed to be open at this moment, and the start amount information of the expansion angle control node at this moment is that the expansion angle is 0 (that is, the cold and heat dual-receiving energy plate is completely closed); If the wind speed index value at a certain time in the future time period is less than or equal to the wind pressure threshold of the cold and hot dual-receiving energy panel, then the start information of the design for the expansion angle control node is closed (ie not started) and expanded
  • the start-up information of the angle control node is that the expansion angle is a preset angle (generally, the preset angle is 45 degrees); the predicted timing logic control diagram of the expansion angle control node at all times
  • the above-mentioned meteorological data also includes rainfall forecast data, humidity forecast data, and atmospheric pressure forecast data; and the meteorological data change curve also includes rainfall forecast change curve, humidity forecast change curve, and atmospheric pressure forecast change curve, which will not be repeated one by one.
  • step S50 the operation step of the intelligent control system specifically executing the above control strategy is further included:
  • Step S60 The above-mentioned intelligent control system manages classification and numbering of the control nodes of each equipment system in real time through the management module, and determines the corresponding control node number to be executed according to the time sequence according to the full sequence logic control chart. If the current time comes to the corresponding At the time sequence in the future time period, identify the number of the control node, and call and control it to perform the corresponding control operation;
  • Step S70 The above-mentioned intelligent control system monitors the operating state of the control node through the abnormal control node monitoring module, and analyzes and determines whether the operating state of the control node is abnormal according to the results of the operating state, and if so, obtains a control node monitoring report;
  • Step S80 The above-mentioned intelligent control system uploads the abnormal control node to the local database to be eliminated through the control node update module, and reports the number of the abnormal control node to the cloud computing control server, and provides the cloud computing control server for the disclosure of alarm maintenance information .
  • step S70 the specific identification of the abnormal control node specifically includes the following operation steps:
  • the aforementioned abnormal control node monitoring module includes a testing module and an equipment management module, wherein:
  • test module is used to start the debugging detection instruction within a preset time period, and then detect the operating status of the control node of each equipment system, and determine whether there is an abnormality in the control node, and if there is an abnormality, lock the number information of the abnormal control node;
  • the above-mentioned local database is used to store the number information of the control node of each equipment system and the corresponding position side information, and the type information of the control node to which it belongs;
  • the above-mentioned equipment management module retrieves the location side information of the abnormal control node and the type information of the control node to which it belongs based on the number information, and then remotely sends it to the cloud computing control server for maintenance.
  • the above-mentioned integrated natural energy intelligent system for heating, power supply, and cooling can provide independent communities and cities with a unified and pollution-free supply of heating, cooling, hot water and electricity, and solve the problem of urban energy supply in one step;
  • the outdoor weather data can be used for lighting, outdoor environmental temperature prediction, the pursuit of intelligent management and control of control nodes such as heat absorption and cooling, conversion, and storage, and even the pursuit of intelligent indoor temperature control target requirements (some future time Periodic constant temperature control), so as to realize an autonomous control strategy to complete the closed-loop control process forming the system.
  • technical means such as cloud computing, Internet+, and big data applications are used to implement smart heating for the natural energy smart system in this embodiment.
  • the most important thing is that it can use the meteorological big data platform to realize intelligent big data control node management and control, providing a more open, smarter, and safer IoT combined with cloud computing mode Comprehensive management and control solutions.

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Abstract

本发明公开了一种供热、供电、制冷一体自然能源智慧系统及控制方法，其可采集气象数据预测未来气象动态，根据气象数据特性调整控制节点的控制参数并根据物联网特性给出自主式控制策略。本实施例的技术方案，通过室外气象数据等预测信息，辅助智能控制系统对源端系统以及其他各个系统部分的控制节点实施调度和控制计划，从而实现大数据化的智能自主控制。

Description

一种供热、供电、制冷一体自然能源智慧系统及控制方法 技术领域
本发明涉及供热智能数据控制技术领域，尤其涉及一种供热、供电、制冷一体自然能源智慧系统及控制方法。
背景技术
能源，是人类活动的物质基础，是驱动城市发展的强大引擎。纵观历史，人类始终致力于寻找城市能源规划的理想方案，建立低碳、安全、智能、可持续发展的能源系统。
在我公司的技术研发过程中，先后设计了由源端系统、能源转换系统、储能系统、末端系统、保温水箱控制系统、智能控制系统等构成的综合处理系统，该综合处理系统是实现智能管理自然能源的综合解决方案；
但是，研发发现如何将上述各个系统部分进行智能管控是个技术难题，上述各个系统部分控制节点繁多，各自为政，无法实现真正的信息互联，并不是真正的智能大数据逻辑控制系统；上述源端系统等部分常常安装在室外复杂的特定环境中(例如：光照强度较好的白天(气温通常较高)，光照强度基本消失的黑夜(气温通常较低)，寒冷冬季或是高温夏季等等环境中)，其并没有将气象数据参考其中，并不能利用气象大数据实施控制节点的智能管控管理。例如：上述源端系统包括冷热双收能量板、热泵和太阳能集热器等等，其涉及的控制节点一般有以下几种：该源端系统一般包括源端系统与能源转换系统之间管道上的阀门控制节点，包括用于对太阳能集热器的启停进行控制的设备开关控制节点、包括对上述热泵进行控制的设备开关控制节点，对上述热泵进行变频控制的变频器控制节点等等；上述常规的控制策略就是简单根据客户端需求以及根据时间节点，判断是否对上述控制节点的操控需求，很显然这种操控方式过于简单，并不是一种先进的智能管控技术手段。
传统控制节点的控制方法比较简单，而且缺乏系统性的智能化设计，其 不利于科学化，大数据化的管理，也不利于国家科技部门所倡导的科技新能源技术大数据化的发展推广要求。综上，如何克服传统技术中的上述技术缺陷本领域技术人员亟待解决的技术问题。
发明内容
本发明的目的在于提供一种供热、供电、制冷一体自然能源智慧系统及控制方法，解决了上述技术问题。
本发明提供了一种供热、供电、制冷一体自然能源智慧系统，包括源端系统、能源转换系统、储能系统、末端系统、保温水箱系统以及智能控制系统，且还包括与所述智能控制系统建立通信连接的云计算控制服务器；
所述源端系统、所述能源转换系统、所述储能系统、所述末端系统、所述保温水箱系统均包括用于控制各自系统中设备的控制节点；
所述云计算控制服务器包括源端位置获取模块、气象监测模块、本地下载模块，其中；所述源端位置获取模块用于首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取所述位置信息对应的所述源端系统处的气象数据；所述气象监测模块用于根据所述请求调取所述源端系统处的气象数据，并根据所述位置信息获取基于未来时间周期内的室外气象参数变化建立时间序列上的气象数据变化曲线；所述本地下载模块用于将所述气象数据变化曲线传送供给所述智能控制系统的本地数据库供其下载保存；所述本地数据库还用于预存所述智能控制系统设置的温度高限阈值和光照高限阈值；
所述智能控制系统包括本地数据库和控制策略确定模块、气象数据更新触发模块；所述智能控制系统用于通过本地数据库保存所述气象数据变化曲线；所述气象数据包括光照强度预测数据、气温预测数据；所述气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；所述智能控制系统的控制策略确定模块根据所述气温预测变化曲线结合所述光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略；
所述气象数据更新触发模块用于实时获取源端温度传感器的源端系统处 的实际室外温度数据；所述气象数据更新触发模块用于实时获取源端光照传感器的源端系统处的实际光照强度数据；所述气象数据更新触发模块用于预设温度高限阈值，实时获取对应时刻的所述气温预测变化曲线的温度数据；所述气象数据更新触发模块用于预设光照高限阈值，实时获取对应时刻的所述光照强度预测变化曲线的光强数据；所述智能控制系统判断当前时刻的实际室外温度数据的数值减去对应时刻的所述气温预测变化曲线的温度数据的数值的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，通过所述控制策略确定模块协调对所有的控制节点重新确定自主式控制策略；同时所述智能控制系统判断当前时刻的实际室外光强数据的数值减去对应时刻的所述光照强度预测变化曲线的光强数据的数值的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，通过控制策略确定模块协调对所有的控制节点重新确定自主式控制策略。
优选的，作为一种可实施方案；所述控制节点的种类主要包括设备开关控制节点，阀门控制节点、变频器控制节点、展开角度控制节点。
优选的，作为一种可实施方案；所述控制策略确定模块，具体用于遍历所述本地数据库内所有控制节点，所述智能控制系统具体根据未来所述时间周期内的气温预测变化曲线和光照强度预测变化曲线，确定所述源端系统内应当启动的控制节点，确定其启动量数值；确定所述能源转换系统内应当启动的控制节点，确定其启动量数值；确定所述储能系统内应当启动的控制节点，确定其启动量数值；确定所述末端系统内应当启动的控制节点，确定其启动量数值；确定所述保温水箱系统内应当启动的控制节点，确定其启动量数值；
所述控制策略确定模块，具体还用于根据当前时刻的所述源端系统、所述能源转换系统、所述储能系统、所述末端系统、保温水箱系统中所有的当前控制节点的启动信息和以及当前所有的控制节点的启动量信息，整合汇编出所述当前时刻的所有的控制节点的预测时序逻辑控制图，最终按照时刻顺序汇编出未来所述时间周期内对应的预测时序逻辑控制图，确定其为全时序逻辑控制图，并确定所述全时序逻辑控制图为自主式控制策略；
所述气象数据更新触发模块，具体还用于接收云计算控制服务器的设置请求，然后对温度高限阈值和光照高限阈值进行设置，并存储到本地数据库中，方便所述智能控制系统进行调取。
优选的，作为一种可实施方案；所述控制策略确定模块，还具体用于根据未来所述时间周期内的风速指数预测变化曲线，确定所述源端系统内所述冷热双收能量板的展开角度控制节点的启动信息和启动量；
具体比较未来所述时间周期内的某个时刻的风速指数数值与所述冷热双收能量板的所承受风压阈值的关系；如果未来所述时间周期内的某个时刻的风速指数数值大于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为开启，且该时刻所述展开角度控制节点的启动量信息为展开角度为0；如果未来所述时间周期内的某个时刻的风速指数数值小于或等于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为关闭和所述展开角度控制节点的启动量信息为展开角度为预设角度；整合汇编出所有时刻的展开角度控制节点的预测时序逻辑控制图，从而形成所述展开角度控制节点的控制策略，将所述展开角度控制节点的控制策略更新到所述全时序逻辑控制图中。
优选的，作为一种可实施方案；所述智能控制系统还包括管理模块、异常控制节点监控模块和控制节点更新模块，其中：
所述智能控制系统通过管理模块实时对所述各个设备系统的所述控制节点进行管理分类和编号，根据所述全时序逻辑控制图按照时序确定对应的要执行的所述控制节点的编号，如果当前时刻来到对应未来时间周期内的时序时刻时，识别所述控制节点的编号，调取控制其执行相应控制操作；
所述智能控制系统通过所述异常控制节点监控模块,监测所述控制节点的运行状态，并根据运行状态结果分析判断所述控制节点的运行状态是否存在异常情况，如是则得到控制节点监测报告；
所述智能控制系统通过所述控制节点更新模块,将异常所述控制节点上传到本地数据库中予以剔除，并上报异常所述控制节点的编号到所述云计算控制服务器，供给所述云计算控制服务器进行报警维修信息的公开。
优选的，作为一种可实施方案；所述客户端还包括显示模块和存储模块；
所述存储模块用于实时获取所述智能控制系统中不断更新的气象数据；所述显示模块用于根据所述气象数据变化曲线显示室外的气象数据变化曲线；
所述客户端与所述智能控制系统之间的通信连接通过通讯模块建立；所述智能控制系统与所有的控制节点之间的通信连接也通过所述通信模块建立；所述通信模块包括以太网模块、WIFI模块、蓝牙模块。
相应地，本发明还提供了一种供热、供电、制冷一体自然能源智慧控制方法(简称控制方法)，其利用供热、供电、制冷一体自然能源智慧系统，执行如下操作步骤：
步骤S10:所述云计算控制服务器的所述源端位置获取模块，首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取所述位置信息对应的所述源端系统处的气象数据；
步骤S20:所述云计算控制服务器的所述气象监测模块根据所述请求调取所述源端系统处的气象数据，并根据所述位置信息获取基于未来时间周期内的室外气象参数变化建立时间序列上的气象数据变化曲线；
步骤S30:所述云计算控制服务器将所述气象数据变化曲线供给本地的所述智能控制系统供其下载保存；所述智能控制系统通过本地数据库保存所述气象数据变化曲线；所述气象数据包括光照强度预测数据、气温预测数据；所述气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；
步骤S40:所述智能控制系统根据所述气温预测变化曲线结合所述光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略；
步骤S50:所述智能控制系统还应当实时获取源端温度传感器的源端系统处的实际室外温度数据；所述智能控制系统还应当实时获取源端光照传感器的源端系统处的实际光照强度数据；所述智能控制系统实时获取对应时刻的所述气温预测变化曲线的温度数据；所述智能控制系统实时获取对应时刻的所述光照强度预测变化曲线的光强数据；所述智能控制系统判断当前时刻的实际室外温度数据减去对应时刻的所述气温预测变化曲线的温度数据的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，协调对所有的控制节点重新确定自主式控制策略；同时所述智能控制系统判断当前时刻的实际室外光强数据减去对应时刻的所述光照强 度预测变化曲线的光强数据的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，协调对所有的控制节点重新确定自主式控制策略。
本申请提供的供热、供电、制冷一体自然能源智慧系统及控制方法，具有的技术效果有：
上述供热、供电、制冷一体自然能源智慧系统的工作平台，实际上是一种软件与硬件、控制节点结合的物联网综合控制节点调控平台，其采集气象数据预测未来气象动态，根据气象数据特性调整控制节点的控制参数并根据物联网特性给出自主式控制策略。这是一种基于未来某个时间周期内的室外气象参数变化建立时间序列上的气温变化模型，计算安排未来时间周期内各个系统部分的控制节点的启动状态和启动量，制定一个自主式控制策略。在某个未来时间周期内的气象数据是变化的，本发明实施例可获取该气象变化预测其控制节点的控制方法，并在未来周期内对调整该控制方式，以使其能够适应瞬息万变的工况环境达到智能管控的技术目的；
本实施例的技术方案，通过室外气象数据等预测信息，辅助智能控制系统对源端系统以及其他各个系统部分的控制节点实施调度和控制计划，从而实现大数据化的智能自主控制。
附图说明
为了更清楚地说明本发明具体实施方式或现有技术中的技术方案，下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施方式，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统的部分硬件系统架构图；
图2为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统的 控制原理示意图；
图3为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统中智能控制系统的一部分控制原理示意图；
图4为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统中云计算控制服务器的控制原理示意图；
图5为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统中智能控制系统的另一部分控制原理示意图；
图6为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统中客户端的控制原理示意图；
图7为本发明实施例提供的供热、供电、制冷一体自然能源智慧控制方法的流程图；
标号：
源端系统100；冷热双收能量板101；
能源转换系统200；转换机组201；
储能系统300；储热器301；储冷器302；
末端系统400；客户端401；显示模块4011；存储模块4012；空调输出系统402；地热输出系统403；
保温水箱系统500；储水箱501；
智能控制系统600；本地数据库610；控制策略确定模块620；气象数据更新触发模块630；管理模块640；异常控制节点监控模块650；控制节点更新模块660；
云计算控制服务器700；源端位置获取模块710；气象监测模块720；本地下载模块730。
具体实施方式
下面将结合附图对本发明的技术方案进行清楚、完整地描述，显然，所 描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
在研发过程中，我研发人员设计在常规技术中，设计了上述一种能源控制系统，其主要包括源端系统、末端系统、储能系统、智能控制系统以及能源转换系统，原常规的智能控制系统的控制方式简单，智能性差，因此设计了供热、供电、制冷一体自然能源智慧系统(简称自然能源智慧系统)；图1中智能控制系统与各个系统部分之间较粗的连线为管道，智能控制系统与各个系统部分之间的细线连线为控制信号线(或称控制线)；其中，图1为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统的部分硬件系统架构图；图2为本发明实施例提供的供热、供电、制冷一体自然能源智慧系统的控制原理示意图。
参见图1、图2，本发明实施例提供了一种供热、供电、制冷一体自然能源智慧系统，主要控制对象包括源端系统100、能源转换系统200、储能系统300、末端系统400、保温水箱系统500、智能控制系统600(具体参见图3和图5)以及云计算控制服务器700，具体的系统架构方案如下：
上述智能控制系统600分别与各个系统部分的控制节点建立通信连接，该智能控制系统600可用于在本地控制各个系统部分(包括源端系统100、能源转换系统200、储能系统300、末端系统400、保温水箱系统500的控制节点)，同时云计算控制服务器700与智能控制系统600建立通信连接的云计算控制服务器；源端系统、能源转换系统、储能系统、末端系统、保温水箱系统均包括用于控制各自系统中设备的控制节点；
参见图2和图4，上述云计算控制服务器700包括源端位置获取模块710、气象监测模块720、本地下载模块730，其中；源端位置获取模块710用于首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取位置信息对应的源端系统处的气象数据(即同时将位置信息发送给气象监测模块)；气象监测模块720用于根据请求调取源端系统处的气象数据，并根据位置信息获取基于未来时间周期(例如未来3-24个小时时间范围，在本实施例中优选为3个小时的设定参数)内的室外气象参数变化建立时间序列上的 气象数据变化曲线；本地下载模块730用于将气象数据变化曲线传送供给智能控制系统600的本地数据库610供其下载保存；本地数据库还用于预存智能控制系统设置的温度高限阈值和光照高限阈值；需要说明的是，上述气象监测模块是远程的云计算控制服务器的一个功能部分，其可以与气象卫星装置等接口准入(或是国家气象局的网络数据准入接口)，也可以通过其他方式实时获得全新的气象数据；某种时间上，或是某个时刻上的气象数据是变化的，本发明实施例可获取该气象变化预测其控制节点的控制方法，并在未来周期内对调整该控制方式，以使其能够适应瞬息万变的工况环境达到智能管控的技术目的；
上述智能控制系统600包括本地数据库610和控制策略确定模块620、气象数据更新触发模块630；智能控制系统600用于通过本地数据库保存气象数据变化曲线；气象数据包括光照强度预测数据、气温预测数据；气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；智能控制系统600的控制策略确定模块620根据气温预测变化曲线结合光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略(包括具体根据气温预测变化曲线和光照强度预测变化曲线，实施按照预定某个时刻，按照控制节点的控制操作，例如启动某个设备，某个时刻准备供暖等自主式的控制策略)；注上述自主式控制策略是一种自主式的控制策略，其可以在客户端无指示自行执行源端系统，储能系统，能源转换系统的运作，保障吸热(吸冷)储能顺利完成，该自主式的控制策略可以作为整体控制策略，也可以作为辅助控制策；在作为辅助控制策略时，其也可以在客户端请求指示时按照客户端的请求具体调整某个控制节点的控制方式(可根据客户请求更改控制策略)，上述自主式的控制策略其不影响客户端对温度调整、热水供给调整等方面的控制，并不会对客户端发送的请求冲突；注意客户端的请求优先级可大于上述自主式控制策略的优先级；
上述气象数据更新触发模块630用于实时获取源端温度传感器的源端系统处的实际室外温度数据；气象数据更新触发模块630用于实时获取源端光照传感器的源端系统处的实际光照强度数据；气象数据更新触发模块预设温度高限阈值，实时获取对应时刻的气温预测变化曲线的温度数据；气象数据 更新触发模块预设光照高限阈值，实时获取对应时刻的光照强度预测变化曲线的光强数据；智能控制系统判断当前时刻的实际室外温度数据的数值减去对应时刻的气温预测变化曲线的温度数据的数值的差数是否超过高限阈值，如果判断为是，则返回气象监测模块更新气象数据变化曲线，通过控制策略确定模块协调对所有的控制节点重新确定自主式控制策略；同时智能控制系统判断当前时刻的实际室外光强数据的数值减去对应时刻的光照强度预测变化曲线的光强数据的数值的差数是否超过高限阈值，如果判断为是，则返回气象监测模块更新气象数据变化曲线，然后根据更新后的气象数据变化曲线重新进行计算，最后利用控制策略确定模块协调重新对所有的控制节点重新确定自主式控制策略；需要说明的是，上述气象监测模块是可以获取最新的气象数据变化曲线，然而气象数据更新触发模块则需要进行逻辑计算和判断，最终决定是否对上述气象监测模块进行触发执行后续的控制策略更新操作。
分析本发明实施例的核心技术方案可知，上述供热、供电、制冷一体自然能源智慧系统的工作平台，实际上是一种软件与硬件、控制节点结合的物联网综合控制节点调控平台，其采集气象数据预测未来气象动态，根据气象数据特性调整控制节点的控制参数并根据物联网特性给出自主式控制策略。这是一种基于未来某个时间周期内(例如3-24小时内)的室外气象参数变化建立时间序列上的气温变化模型，计算安排未来时间周期内各个系统部分的控制节点的启动状态和启动量，制定一个自主式控制策略。通过室外气象数据等预测信息，辅助智能控制系统对源端系统以及其他各个系统部分的控制节点实施调度和控制计划，从而实现大数据化的智能自主控制。
下面对供热、供电、制冷一体自然能源智慧系统的具体功能以及具体技术效果做一下详细说明：
优选的，作为一种可实施方案：上述控制节点的种类主要包括设备开关控制节点，阀门控制节点、变频器控制节点、展开角度控制节点等等。上述源端系统、末端系统、储能系统、能源转换系统各个系统中的控制节点并不完全局限于此，对于其他控制节点可以根据需要添加；一般来讲，上述控制节点的种类主要包括设备开关控制节点，阀门控制节点，设备急停控制节点、变频器控制节点等等；下面对上述各个系统(即源端系统、末端系统、储能 系统、能源转换系统)所涉及的控制节点进行如下说明。
其中，上述源端系统100，其主要由包括含有冷热双收能量板101(图1中简称为能量板)的太阳能集热器、热泵(图中未示出)以及源端光照传感器(图中未示出)等设备部分组成；该源端系统用于通过冷热双收能量板进行源端的太阳能吸热，并通过太阳能集热器将吸收的太阳能转化为热能，传递给能源转换系统；源端系统用于通过冷热双收能量板进行源端的空气冷能吸收，并将空气冷能传递给能源转换系统；通常来讲，该源端系统的控制节点主要涉及：源端系统与能源转换系统之间管道上的阀门控制节点，对上述冷热双收能量板的展开角度进行控制的展开角度控制节点，用于对太阳能集热器的启停进行控制的设备开关控制节点、对上述热泵进行控制的设备开关控制节点，对上述热泵进行变频控制的变频器控制节点等等；
上述能源转换系统200，主要的设备包括转换机组201；上述能源转换系统用于在获取第一控制指令时，接收源端系统供给的热能或是空气冷能，传送给储能系统或传送给末端系统；上述能源转换系统还用于在获取第二控制指令时，接收储能系统供给的热能或是空气冷能，传送给末端系统；通常来讲，上述能源转换系统200的控制节点还包括有：用于对转换机组内的输送泵进行切换控制的ARM嵌入式控制节点(图中未示出)，对转换机组的输送泵进行控制的设备开关控制节点(图中未示出)，对上述转换机组的输送泵进行变频控制的变频器控制节点(图中未示出)等等；
上述储能系统300，包括储热器301和储冷器302等其他设备(图中未示出)；该储能系统用于接收能源转换系统传送的热能储存到储热器中，待需要时调用；储能系统还用于接收能源转换系统传送的空气冷能储存到储冷器中，待需要时调用；通常来讲，该储能系统一般包括储能系统与能源转换系统之间管道上的阀门控制节点(图中未示出)，还包括对上述储热器的启停进行控制的设备开关控制节点(图中未示出)，包括对上述储冷器的启停进行控制的设备开关控制节点，储能系统包括对上述热泵进行控制的设备开关控制节点，对上述热泵进行变频控制的变频器控制节点(图中未示出)；另外上述储能系统300也可以是包括相变光伏储能系统以及跨季节储热储冷系统的储能系统的综合储能系统，关于储能系统的架构对此不再详述。
上述末端系统400，包括客户端401(即安装在每个用户家内部的客户端)、空调输出系统402(主要设备包括风机盘管或称风机管盘)和地热输出系统403(主要设备包括地暖盘管)；空调输出系统402用于接收能源转换系统调用传输过来的热能或是空气冷能以空调出风方式供热或供冷；地热输出系统403用于接收能源转换系统调用传输过来的热能以地暖方式实现供热；通常来讲，该空调输出系统一般包括空调输出系统与能源转换系统之间管道上的阀门控制节点(图中未示出)，还包括对上述空调输出系统中的输送泵的启停进行控制的设备开关控制节点(图中未示出)，包括对上述空调输出系统中的输送泵进行变频控制的变频器控制节点(图中未示出)；包括对上述空调输出系统中的风机进行启停控制的设备开关控制节点，对上述空调输出系统中的风机进行变频控制的变频器控制节点(图中未示出)；该地热输出系统一般包括地热输出系统与能源转换系统之间管道上的阀门控制节点，还包括对上述地热输出系统中的输送泵的启停进行控制的设备开关控制节点，包括对上述地热输出系统中的输送泵进行变频控制的变频器控制节点(上述控制节点图中未示出)；
上述保温水箱系统500，包括储水箱501和热水输送泵(图中未示出)；保温水箱系统用于接收能源转换系统传送的供热热水储存到储水箱并进行释放供水；热水输送泵可用于将储水箱中热水输送至淋浴喷头等处；通常来讲，该保温水箱系统一般包括保温水箱系统与能源转换系统之间管道上的阀门控制节点，以及对热水输送泵实施启停控制的设备开关控制节点，对上述热水输送泵进行变频控制的变频器控制节点等(上述控制节点图中未示出)。
需要说明的是，上述阀门控制节点是一种网络互联的流量控制阀控制节点；且设备开关控制节点，阀门控制节点、变频器控制节点、展开角度控制节点、ARM嵌入式控制节点均为可进行通信的网络控制节点，另外关于其他控制节点可能还有空调机组变频器控制节点等，地热机组变频器控制节点等等对此本发明不再一一赘述；
优选的，作为一种可实施方案：上述控制策略确定模块620，具体用于遍历本地数据库610内所有控制节点，智能控制系统(该智能控制系统的主控制设备为高性能运算处理芯片)具体根据未来时间周期内的气温预测变化 曲线和光照强度预测变化曲线，确定源端系统内应当启动的控制节点，确定其启动量数值；确定能源转换系统内应当启动的控制节点，确定其启动量数值；确定储能系统内应当启动的控制节点，确定其启动量数值；确定末端系统内应当启动的控制节点，确定其启动量数值；确定保温水箱系统内应当启动的控制节点，确定其启动量数值；
上述控制策略确定模块620，具体还用于根据当前时刻的源端系统、能源转换系统、储能系统、末端系统、保温水箱系统中所有的当前控制节点的启动信息(包括具体是否启动信息，例如启动或不启动)和以及当前所有的控制节点的启动量信息，整合汇编出当前时刻的所有的控制节点的预测时序逻辑控制图，最终按照时刻顺序汇编出未来时间周期内对应的预测时序逻辑控制图，确定其为全时序逻辑控制图，并确定全时序逻辑控制图为自主式控制策略。
上述气象数据更新触发模块630，具体还接收云计算控制服务器的设置请求，然后对温度高限阈值和光照高限阈值进行设置，并存储到本地数据库中，方便智能控制系统进行调取。
需要说明的是，上述控制节点的启动信息一般包括具体是否启动信息的(例如启动或不启动)，另外控制节点的启动量信息，一般包括控制参数，例如：一般设备开关控制节点的启动量信息为无，阀门控制节点的启动量可涉及流量控制，阀门开度控制等；在具体实施时，以源端系统为例，计算得到某个室外温度预测值且光照强度预测值，确定源端系统某个设备应不应该启动，启动量是多少，从而确定某个时刻该设备的控制节点的控制策略，确定多个设备的控制节点的启动信息和启动量，最终汇编成全时序逻辑控制图；预测某个时刻温度预测值(温度较高)且光照强度预测值(光照强度较高)，基本通过大数据可以分析判定当前时刻为白天正午时间，此时该源端系统的冷热双收能量板向外输热水管道的阀门控制节点的启动信息应当是启动，启动量也可以根据其他因素确定；同样，该源端系统的展开角度控制节点的启动信息应当为启动，启动量信息应当为完全展开或是展开一定角度例如30度-45度等，以方便冷热双收能量板可以及时吸收太阳能。
优选的，作为一种可实施方案：上述控制策略确定模块620，还具体用 于根据未来时间周期内的风速指数预测变化曲线，确定源端系统内冷热双收能量板的展开角度控制节点的启动信息和启动量；
具体比较未来时间周期内的某个时刻的风速指数数值与冷热双收能量板的所承受风压阈值的关系；如果未来时间周期内的某个时刻的风速指数数值大于冷热双收能量板的所承受风压阈值，则设计该时刻为展开角度控制节点的启动信息为开启，且该时刻展开角度控制节点的启动量信息为展开角度为0(即冷热双收能量板被控制完全关闭状态，避免其遭到强风吹动损坏)；如果未来时间周期内的某个时刻的风速指数数值小于或等于冷热双收能量板的所承受风压阈值，则设计该时刻为展开角度控制节点的启动信息为关闭(即不启动)和展开角度控制节点的启动量信息为展开角度为预设角度(一般来说预设角度为45度夹角)；整合汇编出所有时刻的展开角度控制节点的预测时序逻辑控制图，从而形成展开角度控制节点的控制策略，将展开角度控制节点的控制策略更新到全时序逻辑控制图中。该控制策略确定模块还可以对展开角度控制节点进行相应的控制，从而实现将其更新到全时序逻辑控制图中，实现该展开角度控制节点的添加控制操作。
参见图5，上述智能控制系统600还包括管理模块640、异常控制节点监控模块650和控制节点更新模块660，其中：
上述智能控制系统通过管理模块640实时对各个设备系统的控制节点进行管理分类和编号，根据全时序逻辑控制图按照时序确定对应的要执行的控制节点的编号，如果当前时刻来到对应未来时间周期内的时序时刻时，识别控制节点的编号，调取控制其执行相应控制操作；
上述智能控制系统通过异常控制节点监控模块650,监测控制节点的运行状态，并根据运行状态结果分析判断控制节点的运行状态是否存在异常情况，如是则得到控制节点监测报告；
上述智能控制系统通过控制节点更新模块660,将异常控制节点上传到本地数据库中予以剔除，并上报异常控制节点的编号到云计算控制服务器，供给云计算控制服务器进行报警维修信息的公开。
参见图6，上述客户端401还包括显示模块4011和存储模块4012；
上述存储模块4012用于实时获取智能控制系统中不断更新的气象数据； 上述显示模块4011用于根据气象数据变化曲线显示室外的气象数据变化曲线(注意：这里是一种预测曲线变化，上述智能控制系统更新，客户端就会更新，另外本地调取传输更稳定更快捷)；
上述客户端与智能控制系统之间的通信连接通过通讯模块建立；智能控制系统与所有的控制节点之间的通信连接也通过通信模块建立；上述通信模块(即物联网通讯模块)包括以太网模块、WIFI模块、蓝牙模块。
基于同样的原理，如图7所示，本发明实施例还设计了一种供热、供电、制冷一体自然能源智慧控制方法，包括操作步骤如下：
步骤S10:云计算控制服务器的源端位置获取模块，首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取位置信息对应的源端系统处的气象数据(即同时将位置信息发送给气象监测模块)；
步骤S20:云计算控制服务器的气象监测模块根据请求调取源端系统处的气象数据，并根据位置信息获取基于未来时间周期(例如未来3-24个小时时间范围)内的室外气象参数变化建立时间序列上的气象数据变化曲线；
步骤S30:云计算控制服务器将气象数据变化曲线供给本地的智能控制系统供其下载保存；智能控制系统通过本地数据库保存气象数据变化曲线；气象数据包括光照强度预测数据、气温预测数据；气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；
步骤S40:智能控制系统根据气温预测变化曲线结合光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略(包括具体根据气温预测变化曲线和光照强度预测变化曲线，实施按照预定某个时刻，按照控制节点的控制操作，例如启动某个设备，某个时刻准备供暖等自主式的控制策略)；
步骤S50:智能控制系统还应当实时获取源端温度传感器的源端系统处的实际室外温度数据；智能控制系统还应当实时获取源端光照传感器的源端系统处的实际光照强度数据；智能控制系统实时获取对应时刻的气温预测变化曲线的温度数据；智能控制系统实时获取对应时刻的光照强度预测变化曲线的光强数据；智能控制系统判断当前时刻的实际室外温度数据减去对应时刻 的气温预测变化曲线的温度数据的差数是否超过高限阈值，如果判断为是，则返回气象监测模块更新气象数据变化曲线，协调对所有的控制节点重新确定自主式控制策略；同时智能控制系统判断当前时刻的实际室外光强数据减去对应时刻的光照强度预测变化曲线的光强数据的差数是否超过高限阈值，如果判断为是，则返回气象监测模块更新气象数据变化曲线，协调对所有的控制节点重新确定自主式控制策略。
优选的，作为一种可实施方案：在步骤S40中的具体技术方案中，步骤S40:智能控制系统根据气温预测变化曲线结合光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略，具体包括如下操作步骤：
步骤S410:智能控制系统遍历本地数据库内所有控制节点，智能控制系统具体根据未来时间周期内的气温预测变化曲线和光照强度预测变化曲线，确定源端系统内应当启动的控制节点，确定其启动量数值；确定能源转换系统内应当启动的控制节点，确定其启动量数值；确定储能系统内应当启动的控制节点，确定其启动量数值；确定末端系统内应当启动的控制节点，确定其启动量数值；确定保温水箱系统内应当启动的控制节点，确定其启动量数值；
需要说明的是，自主式控制策略是以室内温度达到预定范围内为目的，同时各个系统部分哪些设备应当启动，哪些设备的控制节点能当开启，具体涉及确定源端系统内哪些控制节点应当启动，启动量是多少，确定能源转换系统内哪些控制节点应当启动，启动量是多少，确定储能系统内哪些控制节点应当启动，启动量是多少，确定末端系统内哪些控制节点应当启动，启动量是多少；举例说明：确定哪些控制节点启动，启动量多少的确定是根据室外温度，光照强度等因素判断的，例如根据气象数据(光强数据)可知道白天的时间，入夜的时间，进而判断源端系统的冷热双收能量板什么时间启动合适；根据气象数据预测室外温度后，如果可以考虑源端系统是应该吸热好，还是吸冷能更合适，上述这些控制节点则会被计算，同时由于源端系统的控制节点被判定后，后续的储能系统，能源转换系统，末端系统的控制节点也应当进行启动和气动量的判断，最终才能确定了未来某个时刻所有的系统部分的控制节点的响应情况；
步骤S420:智能控制系统，根据当前时刻的源端系统、能源转换系统、储能系统、末端系统中所有的当前控制节点的启动信息和以及当前所有的控制节点的启动量信息，整合汇编出当前时刻的所有的控制节点的预测时序逻辑控制图，最终按照时刻顺序汇编出未来时间周期内对应的预测时序逻辑控制图，确定其为全时序逻辑控制图，并确定全时序逻辑控制图为自主式控制策略；
在步骤S50中的具体技术方案中，云计算控制服务器的气象数据更新触发模块还包括预设高限阈值的操作，具体包括如下操作步骤；
步骤S510:气象数据更新触发模块接收云计算控制服务器的设置请求，然后对温度高限阈值和光照高限阈值进行设置，并存储到本地数据库中，方便智能控制系统进行调取。
优选的，作为一种可实施方案：上述气象数据还包括风速指数预测数据；且气象数据变化曲线还包括风速指数预测变化曲线；
在执行步骤S40之后，智能控制系统还需要同时考虑根据风速指数预测变化曲线，协调冷热双收能量板的展开角度控制节点的控制策略，具体包括如下操作步骤：
步骤S41:智能控制系统具体根据未来时间周期内的风速指数预测变化曲线，确定源端系统内冷热双收能量板的展开角度控制节点的启动信息和启动量；
具体比较未来时间周期内的某个时刻的风速指数数值与冷热双收能量板的所承受风压阈值的关系；如果未来时间周期内的某个时刻的风速指数数值大于冷热双收能量板的所承受风压阈值，则设计该时刻为展开角度控制节点的启动信息为开启，且该时刻展开角度控制节点的启动量信息为展开角度为0(即冷热双收能量板完全关闭)；如果未来时间周期内的某个时刻的风速指数数值小于或等于冷热双收能量板的所承受风压阈值，则设计该时刻为展开角度控制节点的启动信息为关闭(即不启动)和展开角度控制节点的启动量信息为展开角度为预设角度(一般来说预设角度为45度夹角)；整合汇编出所有时刻的展开角度控制节点的预测时序逻辑控制图，从而形成展开角度控制节点的控制策略，将展开角度控制节点的控制策略更新到全时序逻辑控制 图中。
不仅如此，上述气象数据还包括雨量预测数据、湿度预测数据、气压预测数据；且气象数据变化曲线还包括雨量预测变化曲线、湿度预测变化曲线、气压预测变化曲线，对此不再一一赘述。
优选的，作为一种可实施方案：在步骤S50之后，还包括智能控制系统具体执行上述控制策略的操作步骤：
步骤S60:上述智能控制系统，通过管理模块实时对各个设备系统的控制节点进行管理分类和编号，根据全时序逻辑控制图按照时序确定对应的要执行的控制节点的编号，如果当前时刻来到对应未来时间周期内的时序时刻时，识别控制节点的编号，调取控制其执行相应控制操作；
步骤S70:上述智能控制系统，通过异常控制节点监控模块,监测控制节点的运行状态，并根据运行状态结果分析判断控制节点的运行状态是否存在异常情况，如是则得到控制节点监测报告；
步骤S80:上述智能控制系统，通过控制节点更新模块,将异常控制节点上传到本地数据库中予以剔除，并上报异常控制节点的编号到云计算控制服务器，供给云计算控制服务器进行报警维修信息的公开。
需要说明的是，在上述步骤S70中，具体识别出异常的控制节点，具体包括如下操作步骤：
上述异常控制节点监控模块包括测试模块、设备管理模块，其中；
上述测试模块，用于在预设时间周期内启动调试检测指令，然后检测各个设备系统的控制节点运行状态，判断其是否存在控制节点的异常，如果存在异常，则锁定异常控制节点的编号信息；
上述本地数据库用于存储各个设备系统的控制节点的编号信息以及对应的位置侧信息、所属控制节点类型信息；
上述设备管理模块根据编号信息，调取异常控制节点的位置侧信息，所属控制节点类型信息，然后远程发送给云计算控制服务器，供给服务器维修。
本发明实施例提供的上述供热、供电、制冷一体自然能源智慧系统，可为独立社区、城市提供统一无污染的供暖、制冷、热水和电力供应，一步解 决城市供能问题；同时在综合考虑客户端需求的基础上，可利用室外气象数据进行光照，室外环境温度预测，追求吸热能冷能，转换，存储等控制节点的智能管控，甚至追求室内温度智能控制目标要求(某未来时间周期恒温控制)，从而实现一种自主的控制策略完成形成系统的闭环控制流程。本实施例，利用云计算、互联网+、大数据应用等技术手段，为本实施例中的自然能源智慧系统实现智能供热。
在本申请实施例中，最为重要的是其可利用气象大数据平台实现了智能大数据的控制节点管控，提供了一种更为开放、更为智慧、更为安全的物联网结合云计算模式的综合管控解决方案。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (10)

  1. 一种供热、供电、制冷一体自然能源智慧系统，其特征在于，包括源端系统、能源转换系统、储能系统、末端系统、保温水箱系统以及智能控制系统，且还包括与所述智能控制系统建立通信连接的云计算控制服务器；
    所述源端系统、所述能源转换系统、所述储能系统、所述末端系统、所述保温水箱系统均包括用于控制各自系统中设备的控制节点；
    所述云计算控制服务器包括源端位置获取模块、气象监测模块、本地下载模块，其中；所述源端位置获取模块用于首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取所述位置信息对应的所述源端系统处的气象数据；所述气象监测模块用于根据所述请求调取所述源端系统处的气象数据，并根据所述位置信息获取基于未来时间周期内的室外气象参数变化建立时间序列上的气象数据变化曲线；所述本地下载模块用于将所述气象数据变化曲线传送供给所述智能控制系统的本地数据库供其下载保存；所述本地数据库还用于预存所述智能控制系统设置的温度高限阈值和光照高限阈值；
    所述智能控制系统包括所述本地数据库和控制策略确定模块、气象数据更新触发模块；所述智能控制系统用于通过本地数据库保存所述气象数据变化曲线；所述气象数据包括光照强度预测数据、气温预测数据；所述气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；所述智能控制系统的控制策略确定模块根据所述气温预测变化曲线结合所述光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略；
    所述气象数据更新触发模块用于实时获取源端温度传感器的源端系统处的实际室外温度数据；所述气象数据更新触发模块用于实时获取源端光照传感器的源端系统处的实际光照强度数据；所述气象数据更新触发模块用于预设温度高限阈值，实时获取对应时刻的所述气温预测变化曲线的温度数据；所述气象数据更新触发模块用于预设光照高限阈值，实时获取对应时刻的所述光照强度预测变化曲线的光强数据；所述智能控制系统判断当前时刻的实际室外温度数据的数值减去对应时刻的所述气温预测变化曲线的温度数据的 数值的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，通过所述控制策略确定模块协调对所有的控制节点重新确定自主式控制策略；同时所述智能控制系统判断当前时刻的实际室外光强数据的数值减去对应时刻的所述光照强度预测变化曲线的光强数据的数值的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，通过控制策略确定模块协调对所有的控制节点重新确定自主式控制策略。
  2. 如权利要求1所述的供热、供电、制冷一体自然能源智慧系统，其特征在于，所述控制节点的种类包括设备开关控制节点，阀门控制节点、变频器控制节点、展开角度控制节点。
  3. 如权利要求2所述的供热、供电、制冷一体自然能源智慧系统，其特征在于，所述控制策略确定模块，具体用于遍历所述本地数据库内所有控制节点，所述智能控制系统具体根据未来所述时间周期内的气温预测变化曲线和光照强度预测变化曲线，确定所述源端系统内应当启动的控制节点，确定其启动量数值；确定所述能源转换系统内应当启动的控制节点，确定其启动量数值；确定所述储能系统内应当启动的控制节点，确定其启动量数值；确定所述末端系统内应当启动的控制节点，确定其启动量数值；确定所述保温水箱系统内应当启动的控制节点，确定其启动量数值；
    所述控制策略确定模块，具体还用于根据当前时刻的所述源端系统、所述能源转换系统、所述储能系统、所述末端系统、保温水箱系统中所有的当前控制节点的启动信息和以及当前所有的控制节点的启动量信息，整合汇编出所述当前时刻的所有的控制节点的预测时序逻辑控制图，最终按照时刻顺序汇编出未来所述时间周期内对应的预测时序逻辑控制图，确定其为全时序逻辑控制图，并确定所述全时序逻辑控制图为自主式控制策略；
    所述气象数据更新触发模块，具体还用于接收云计算控制服务器的设置请求，然后对温度高限阈值和光照高限阈值进行设置，并存储到本地数据库中，方便所述智能控制系统进行调取。
  4. 如权利要求3所述的供热、供电、制冷一体自然能源智慧系统，其特征在于，所述控制策略确定模块，还具体用于根据未来所述时间周期内的风速指数预测变化曲线，确定所述源端系统内所述冷热双收能量板的展开角度控制节点的启动信息和启动量；
    具体比较未来所述时间周期内的某个时刻的风速指数数值与所述冷热双收能量板的所承受风压阈值的关系；如果未来所述时间周期内的某个时刻的风速指数数值大于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为开启，且该时刻所述展开角度控制节点的启动量信息为展开角度为0；如果未来所述时间周期内的某个时刻的风速指数数值小于或等于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为关闭和所述展开角度控制节点的启动量信息为展开角度为预设角度；整合汇编出所有时刻的展开角度控制节点的预测时序逻辑控制图，从而形成所述展开角度控制节点的控制策略，将所述展开角度控制节点的控制策略更新到所述全时序逻辑控制图中。
  5. 如权利要求4所述的供热、供电、制冷一体自然能源智慧系统，其特征在于，所述智能控制系统还包括管理模块、异常控制节点监控模块和控制节点更新模块，其中：
    所述智能控制系统通过管理模块实时对所述各个设备系统的所述控制节点进行管理分类和编号，根据所述全时序逻辑控制图按照时序确定对应的要执行的所述控制节点的编号，如果当前时刻来到对应未来时间周期内的时序时刻时，识别所述控制节点的编号，调取控制其执行相应控制操作；
    所述智能控制系统通过所述异常控制节点监控模块,监测所述控制节点的运行状态，并根据运行状态结果分析判断所述控制节点的运行状态是否存在异常情况，如是则得到控制节点监测报告；
    所述智能控制系统通过所述控制节点更新模块,将异常所述控制节点上传到本地数据库中予以剔除，并上报异常所述控制节点的编号到所述云计算控制服务器，供给所述云计算控制服务器进行报警维修信息的公开。
  6. 如权利要求5所述的供热、供电、制冷一体自然能源智慧系统，其特 征在于，所述客户端还包括显示模块和存储模块；
    所述存储模块用于实时获取所述智能控制系统中不断更新的气象数据；所述显示模块用于根据所述气象数据变化曲线显示室外的气象数据变化曲线；
    所述客户端与所述智能控制系统之间的通信连接通过通讯模块建立；所述智能控制系统与所有的控制节点之间的通信连接也通过所述通信模块建立；所述通信模块包括以太网模块、WIFI模块、蓝牙模块。
  7. 一种供热、供电、制冷一体自然能源智慧控制方法，其特征在于，其利用如权利要求6所述的供热、供电、制冷一体自然能源智慧系统，执行如下操作步骤：
    步骤S10:所述云计算控制服务器的所述源端位置获取模块，首先获取源端系统的位置信息，然后访问气象监测模块并实时发起请求调取所述位置信息对应的所述源端系统处的气象数据；
    步骤S20:所述云计算控制服务器的所述气象监测模块根据所述请求调取所述源端系统处的气象数据，并根据所述位置信息获取基于未来时间周期内的室外气象参数变化建立时间序列上的气象数据变化曲线；
    步骤S30:所述云计算控制服务器将所述气象数据变化曲线供给本地的所述智能控制系统供其下载保存；所述智能控制系统通过本地数据库保存所述气象数据变化曲线；所述气象数据包括光照强度预测数据、气温预测数据；所述气象数据变化曲线包括气温预测变化曲线和光照强度预测变化曲线；
    步骤S40:所述智能控制系统根据所述气温预测变化曲线结合所述光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略；
    步骤S50:所述智能控制系统还应当实时获取源端温度传感器的源端系统处的实际室外温度数据；所述智能控制系统还应当实时获取源端光照传感器的源端系统处的实际光照强度数据；所述智能控制系统实时获取对应时刻的所述气温预测变化曲线的温度数据；所述智能控制系统实时获取对应时刻的所述光照强度预测变化曲线的光强数据；所述智能控制系统判断当前时刻的实际室外温度数据减去对应时刻的所述气温预测变化曲线的温度数据的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象 数据变化曲线，协调对所有的控制节点重新确定自主式控制策略；同时所述智能控制系统判断当前时刻的实际室外光强数据减去对应时刻的所述光照强度预测变化曲线的光强数据的差数是否超过所述高限阈值，如果判断为是，则返回所述气象监测模块更新气象数据变化曲线，协调对所有的控制节点重新确定自主式控制策略。
  8. 如权利要求7所述的供热、供电、制冷一体自然能源智慧控制方法，其特征在于，
    在步骤S40中的具体技术方案中，步骤S40:所述智能控制系统根据所述气温预测变化曲线结合所述光照强度预测变化曲线，协调所有的控制节点确定自主式控制策略，具体包括如下操作步骤：
    步骤S410:所述智能控制系统遍历所述本地数据库内所有控制节点，所述智能控制系统具体根据未来所述时间周期内的气温预测变化曲线和光照强度预测变化曲线，确定所述源端系统内应当启动的控制节点，确定其启动量数值；确定所述能源转换系统内应当启动的控制节点，确定其启动量数值；确定所述储能系统内应当启动的控制节点，确定其启动量数值；确定所述末端系统内应当启动的控制节点，确定其启动量数值；确定所述保温水箱系统内应当启动的控制节点，确定其启动量数值；
    步骤S420:所述智能控制系统，根据当前时刻的所述源端系统、所述能源转换系统、所述储能系统、所述末端系统中所有的当前控制节点的启动信息和以及当前所有的控制节点的启动量信息，整合汇编出所述当前时刻的所有的控制节点的预测时序逻辑控制图，最终按照时刻顺序汇编出未来所述时间周期内对应的预测时序逻辑控制图，确定其为全时序逻辑控制图，并确定所述全时序逻辑控制图为自主式控制策略；
    在步骤S50中的具体技术方案中，所述云计算控制服务器的气象数据更新触发模块还包括预设高限阈值的操作，具体包括如下操作步骤；
    步骤S510:所述气象数据更新触发模块接收云计算控制服务器的设置请求，然后对温度高限阈值和光照高限阈值进行设置，并存储到本地数据库中，方便所述智能控制系统进行调取。
  9. 如权利要求8所述的供热、供电、制冷一体自然能源智慧控制方法，其特征在于，所述气象数据还包括风速指数预测数据；且所述气象数据变化曲线还包括风速指数预测变化曲线；
    在执行步骤S40之后，所述智能控制系统还需要同时考虑根据所述风速指数预测变化曲线，协调所述冷热双收能量板的展开角度控制节点的控制策略，具体包括如下操作步骤：
    步骤S41:所述智能控制系统具体根据未来所述时间周期内的风速指数预测变化曲线，确定所述源端系统内所述冷热双收能量板的展开角度控制节点的启动信息和启动量；
    具体比较未来所述时间周期内的某个时刻的风速指数数值与所述冷热双收能量板的所承受风压阈值的关系；如果未来所述时间周期内的某个时刻的风速指数数值大于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为开启，且该时刻所述展开角度控制节点的启动量信息为展开角度为0；如果未来所述时间周期内的某个时刻的风速指数数值小于或等于所述冷热双收能量板的所承受风压阈值，则设计该时刻为所述展开角度控制节点的启动信息为关闭和所述展开角度控制节点的启动量信息为展开角度为预设角度；整合汇编出所有时刻的展开角度控制节点的预测时序逻辑控制图，从而形成所述展开角度控制节点的控制策略，将所述展开角度控制节点的控制策略更新到所述全时序逻辑控制图中。
  10. 如权利要求9所述的供热、供电、制冷一体自然能源智慧控制方法，其特征在于，
    在步骤S50之后，还包括智能控制系统具体执行上述控制策略的操作步骤：
    步骤S60:所述智能控制系统,通过管理模块实时对所述各个设备系统的所述控制节点进行管理分类和编号，根据所述全时序逻辑控制图按照时序确定对应的要执行的所述控制节点的编号，如果当前时刻来到对应未来时间周期内的时序时刻时，识别所述控制节点的编号，调取控制其执行相应控制操作；
    步骤S70:所述智能控制系统,监测所述控制节点的运行状态，并根据运行状态结果分析判断所述控制节点的运行状态是否存在异常情况，如是则得到控制节点监测报告；
    步骤S80:所述智能控制系统,将异常所述控制节点上传到本地数据库中予以剔除，并上报异常所述控制节点的编号到所述云计算控制服务器，供给所述云计算控制服务器进行报警维修信息的公开。
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