CN113154518A - Intelligent heat supply control system based on residential electricity load scheduling - Google Patents
Intelligent heat supply control system based on residential electricity load scheduling Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1096—Arrangement or mounting of control or safety devices for electric heating systems
Abstract
The invention discloses an intelligent heat supply control system based on residential electricity load scheduling.A heat supply management acquisition terminal is arranged on a single power distribution branch circuit and is used for acquiring the electric quantity information of the single power distribution branch circuit and the electric quantity information of a single heat supply device corresponding to the electric quantity information; the dynamic load characteristic monitor is connected with all the heat supply management acquisition terminals and is used for collecting and receiving the electric quantity information of all the heat supply management acquisition terminals and calculating the residual capacity of the service line; the AI intelligent heat and power supply load scheduling device is connected with the dynamic load characteristic monitor through a first wireless or wired data transmission device and a second wireless or wired data transmission device, and controls the heat supply mode and the running quantity of the heat supply device according to the electric quantity information. A dynamic load characteristic monitor is arranged in a main loop of the service line, the residual capacity of the service line is calculated in real time, and the service efficiency of the service line capacity is improved; and the heat supply mode of the heat supply device is adjusted in real time, so that closed-loop control is realized.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to an intelligent heat supply control system based on residential electricity load scheduling.
Background
When the existing house is used for installing the heating device, as most houses belong to modified houses, the capacity of the house lead-in line is limited, and the line is laid again under the condition of not influencing the operation of the existing equipment, so that the investment is increased; and the operation load of some houses is influenced by the existing power supply condition, so that the capacity amplification is not facilitated. If the capacity expansion of the power consumption load is not carried out, the power consumption load of the household conventional electrical appliance and the total actual power consumption load of the heating device exceed the power consumption load which can be provided by an inlet wire, the circuit is easy to generate heat and does not have the protection functions of overheat protection, fire alarm, fire control joint control, over-power tripping and the like, the electrical fire is very easy to cause, serious casualty events such as human body electric shock or burn and the like are caused, and the economic loss is caused. When the electric load returns to normal and the heating device can be started, the system can not automatically return to operation. Affecting heating effect and user experience. The existing heating device has a single control mode and low artificial intelligence degree, and has no mechanism for mining, analyzing and learning historical data. Unnecessary energy and personnel waste is caused, and the energy-saving effect cannot be realized
In summary, the problems of the existing heating system include: a circuit is laid again, and investment is increased; the construction is difficult due to the influence of power supply conditions. The control mode and the control system are not strict. The electric fire and personal injury accidents are easily caused without load amplification. The control is single, and energy conservation and emission reduction can not be realized.
Therefore, there is a need to develop an intelligent heating control system based on residential electrical load scheduling to utilize excess load for electrical heating. The invention relates to a closed-loop control system for heat supply, which is characterized in that the specific working content is that according to data information fed back by various information acquisition equipment, the closed-loop control of heat supply is realized by combining AI artificial intelligence at the front edge and through module units such as an AI intelligent heat and power supply load scheduling device, a big data AI algorithm model and the like. The house is perfectly combined with electricity and heat supply, and safe and stable operation is realized. The system has the functions of overheat protection, fire alarm, fire control joint control, over-power trip and the like, and has the function of self-recovery operation of a fault removal system. The method can reduce investment cost, improve economy, improve service efficiency of service line capacity and reduce power utilization accidents.
Disclosure of Invention
The invention aims to provide an intelligent heat supply control system based on residential electric load scheduling, which can calculate the residual capacity of an inlet wire in real time through the setting of a dynamic load characteristic monitor, improve the service efficiency of the inlet wire capacity and realize the closed-loop control of a heat supply device.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides an intelligent heat supply control system based on house power consumption load scheduling, includes heat supply management acquisition terminal, and heat supply management acquisition terminal sets up on single distribution branch for gather the electric quantity information of single distribution branch and rather than the single heating device electric quantity information that corresponds.
The dynamic load characteristic monitor is connected with all the heat supply management acquisition terminals and is used for collecting and receiving the electric quantity information of all the heat supply management acquisition terminals and calculating the residual capacity of the service line.
The AI intelligent heating power load scheduling device is connected with the dynamic load characteristic monitor through a first wireless or wired data transmission device and a second wireless or wired data transmission device to acquire the electric quantity information of the whole house, and controls the heating mode and the running quantity of the heating device according to the electric quantity information.
Preferably, the power information includes: current, voltage, frequency, power, total power, peak-to-valley average total power, and the like.
Preferably, the AI intelligent heating power load scheduling device includes: the system comprises an AI artificial intelligence big data intelligent cloud platform, wherein a database is arranged in the AI artificial intelligence big data intelligent cloud platform; the database has a block chain encryption technology, data are also stored in a fragmentized mode at the cloud end of the server, multiple data are backed up, the safety of the data is guaranteed, different storage strategies are adopted for different data types, and the database is established based on the electric quantity information received by the dynamic load characteristic monitor;
the algorithm model unit is an AI intelligent heat supply algorithm model with statistics, time series analysis principle, machine learning, matrix decomposition and self-learning deviation rectifying functions;
the voice recognition and infrared human body induction unit interacts with the AI intelligent heating and power load scheduling device through the voice recognition unit, and the infrared human body induction unit detects that no people are in a room and the equipment is not started in an intelligent mode, and the equipment is started by combining residual load conditions, sensed human body temperature, model algorithm and other control elements to realize energy-saving control.
The logic processing unit is in communication connection with the AI big data intelligent cloud platform and calculates to obtain a control instruction according to an automation control principle and the data information of the database; the internal protection function has the functions of overheat protection, fire alarm, fire control joint control, over-power trip and the like, and the fault removing system has the function of self-recovery operation.
The execution unit is in communication connection with the logic processing unit, receives the control instruction of the logic processing unit and executes the control instruction; according to the set room temperature, the system has the function of temperature compensation and deviation rectification feedback.
And the human-computer interaction unit is used for scheduling and controlling the equipment by utilizing a multi-channel interaction technology and through human-computer interaction according to the established human-computer cooperation model.
Preferably, the establishing process of the database in the AI artificial intelligence big data intelligent cloud platform comprises load type division, load size calculation, house lead residual capacity calculation and heating device starting capacity calculation.
Preferably, the remaining subscriber line capacity = total subscriber line capacity — occupied capacity of each distribution branch.
Preferably, the number of the heat supply management acquisition terminals is matched with that of the heat supply devices.
Preferably, the heat supply device is powered by the terminal power distribution branch.
Compared with the prior art, the invention has the beneficial effects that: a dynamic load characteristic monitor is arranged in a main loop of the service line, the residual capacity of the service line is calculated in real time, the service efficiency of the service line capacity is improved, the investment cost is reduced, and the economical efficiency of enterprises is improved; and the heat supply mode of the heat supply device is adjusted in real time, so that closed-loop control is realized.
Drawings
FIG. 1 is a schematic structural view of the present invention;
fig. 2 is a schematic structural diagram of an AI intelligent heating and power load scheduling device according to the present invention.
In the figure: a heat supply management acquisition terminal 1; a dynamic load characteristic monitor 2; a first wireless or wired data transmission device 3; a second wireless or wired data transmission device 4; an AI intelligent heating and power load scheduling device 5; a heating device 6; a distribution branch 7.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: the utility model provides an intelligent heat supply control system based on house power consumption load scheduling, includes heat supply management acquisition terminal 1, and heat supply management acquisition terminal 1 sets up on single distribution branch 7 for gather the electric quantity information of single distribution branch 7 and rather than the 6 electric quantity information of single heating device that correspond.
The dynamic load characteristic monitor 2 is connected with all the heat supply management acquisition terminals 1 and is used for collecting and receiving the electric quantity information of all the heat supply management acquisition terminals 1 and calculating the residual capacity of the service line.
The AI intelligent heating power load scheduling device 5 is connected with the dynamic load characteristic monitor 2 through the first wireless or wired data transmission device 3 and the second wireless or wired data transmission device 4 to obtain the electric quantity information of the whole house, and the AI intelligent heating power load scheduling device 5 controls the heating mode and the running quantity of the heating device 6 according to the electric quantity information.
The power supply of the heat supply device 6 is supplied by the power distribution branch 7, and in this embodiment, there are four power distribution branches 7, and 4 heat supply devices 6 are provided.
The dynamic load characteristic monitor 2 collects the electric quantity information of all the heat supply management acquisition terminals 1, the collected information is transmitted to the AI intelligent heat supply electric load scheduling device 5 through a wireless or wired data transmission device, the AI intelligent heat supply electric load scheduling device 5 performs data analysis on the transmitted electric quantity information, and an operation instruction and a starting mode are issued to the heat supply device 6 according to the analysis result.
Wherein the start-up mode of the heating device 6 comprises: the self-defining mode can set the operating power percentage on the AI intelligent heating and power load scheduling device 5; and in the intelligent mode, the input running power is equal to the residual capacity of the subscriber line by combining the information of the infrared human body induction unit, wherein the residual capacity of the subscriber line = the rated capacity of the subscriber line-the occupied capacity of all the power distribution branches 7, and the intelligent mode is not started when the residual capacity of the subscriber line is equal to zero.
Preferably, the AI intelligent heating and power load scheduling device 5 includes: the system comprises an AI artificial intelligence big data intelligent cloud platform 5-1, wherein a database is arranged in the AI artificial intelligence big data intelligent cloud platform 5-1; the database has a block chain encryption technology, data are also stored in a fragmentized mode at the cloud end of the server, multiple data are backed up, the safety of the data is guaranteed, different storage strategies are adopted for different data types, and the database is established based on the electric quantity information received by the dynamic load characteristic monitor;
the algorithm model unit 5-2 is an AI intelligent heat supply algorithm model with statistics, time series analysis principle, machine learning, matrix decomposition and self-learning deviation rectifying functions;
the voice recognition and infrared human body induction unit 5-3 interacts with the AI intelligent heating and power load scheduling device through the voice recognition unit, and the infrared human body induction unit detects that no people are in the room to open the equipment and people are in the room in an intelligent mode, and opens the equipment by combining the residual load condition, the sensed human body temperature, the model algorithm and other control elements to realize energy-saving control.
The logic processing unit 5-4 is in communication connection with the AI artificial intelligence big data intelligent cloud platform 5-1 and calculates and obtains a control instruction according to an automation control principle and the data information of the database; the internal protection function has the functions of overheat protection, fire alarm, fire control joint control, over-power trip and the like, and the fault removing system has the function of self-recovery operation.
The execution unit 5-5 is in communication connection with the logic processing unit 5-4, receives the control instruction of the logic processing unit and executes the control instruction; according to the set room temperature, the system has the function of temperature compensation and deviation rectification feedback.
And the human-computer interaction unit 5-6 is used for scheduling and controlling the equipment by utilizing a multi-channel interaction technology and human-computer interaction according to the established human-computer cooperation model.
Wherein the database is established based on the power information received by the dynamic load characteristic monitor 2.
Further, the establishment process of the database comprises load type division, load size calculation, house lead residual capacity calculation, heating device 6 starting capacity calculation and the like;
the logic processing unit 5-4 adopts a microcontroller, further operation is carried out by the microcontroller on the basis of the AI artificial intelligence big data intelligent cloud platform operation result, and a control instruction is issued to the execution unit according to the logic operation result;
the execution unit 5-5 cuts off or closes the corresponding heating loop in the heating device 6 according to the control instruction, thereby reducing or increasing the operation power of the heating device 6.
The heat supply management acquisition terminal 1 monitors the running state of the heat supply device 6 in real time and acquires electric quantity information. The AI intelligent heat supply power load scheduling device 5 compares the electric quantity information of the dynamic load characteristic monitor 2 with the operation result of the AI artificial intelligent big data intelligent cloud platform, and adjusts the operation state of the heat supply device 6 in real time, thereby realizing closed-loop control.
Further, subscriber line residual capacity = subscriber line total capacity — capacity occupied by each distribution branch 7.
Before the heating device 6 is started to operate, an operator firstly selects a starting mode on the AI intelligent heating power load scheduling device 5, wherein the starting mode comprises a user-defined mode and an intelligent mode, the operating power of the heating device 6 in the user-defined mode is not influenced by the residual capacity of a subscriber line, and the operating power is a value preset by the operator. When the operator selects the intelligent mode before starting, the operating power of the heating installation 6 is influenced by the remaining capacity of the service line. The above instructions can be completed by the voice recognition module unit.
Wherein, according to the remaining capacity of the service line, the heating device 6 is started as follows: when the operating personnel selects the intelligent mode, at first set up the initial power, the meaning of initial power is: in the intelligent mode, the intelligent power supply system operates at the initial power during starting, and then gradually inputs power to the residual power of the subscriber line so as to prevent the impact of high-power starting on the subscriber line.
When the intelligent mode is started, an AI artificial intelligence big data intelligent cloud platform in the AI intelligent heating and power load scheduling device 5 calculates the remaining capacity of the service line by utilizing the electric quantity information uploaded by the dynamic load characteristic monitor 2, the logic processing unit controls the switching-off and switching-on of each unit in the execution unit according to the remaining capacity of the service line, and the operating power of the heating device is reduced or increased by switching-off and switching-on of the execution unit.
When the capacity of the service line is increased, the operation power of the heat supply device 6 is increased, and when the capacity of the service line is reduced, the operation power of the heat supply device 6 is reduced, and the operation power of the heat supply device 6 is always smaller than or equal to the residual capacity of the service line.
When the capacity of the service line is fixed, the operation of the heating device 6 has no influence on the existing equipment.
Preferably, the first wireless or wired data transmission device 3 is installed on the side of the dynamic load characteristic monitor 2, the second wireless or wired data transmission device 4 is installed on the side of the AI intelligent heating and power load dispatching device 5, and the first wireless or wired data transmission device 3 transmits data information to the second wireless or wired data transmission device 4 by wireless communication.
The two wireless or wired data transmission devices can be respectively arranged on different sites and transmit data information in a wireless communication mode.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The utility model provides an intelligence heat supply control system based on house power consumption load scheduling which characterized in that: the system comprises a heat supply management acquisition terminal (1), wherein the heat supply management acquisition terminal (1) is arranged on a single power distribution branch (7) and is used for acquiring the electric quantity information of the single power distribution branch (7) and the electric quantity information of a single heat supply device (6) corresponding to the electric quantity information;
the dynamic load characteristic monitor (2) is connected with all the heat supply management acquisition terminals (1) and is used for collecting and receiving the electric quantity information of all the heat supply management acquisition terminals (1) and calculating the residual capacity of the service line;
the AI intelligent heat supply power load scheduling device (5) is connected with the dynamic load characteristic monitor (2) through a first wireless or wired data transmission device (3) and a second wireless or wired data transmission device (4) to obtain the electric quantity information of the whole house, and the AI intelligent heat supply power load scheduling device (5) controls the heat supply mode and the running quantity of the heat supply device (6) according to the electric quantity information.
2. An intelligent heating control system based on residential electrical load scheduling according to claim 1, characterized in that: the first wireless or wired data transmission device (3) is arranged on one side of the dynamic load characteristic monitor (2), the second wireless or wired data transmission device (4) is arranged on one side of the AI intelligent heat supply power load dispatching device (5), and the first wireless or wired data transmission device (3) transmits data information to the second wireless or wired data transmission device (4) in a wireless communication mode.
3. An intelligent heating control system based on residential electrical load scheduling according to claim 1, characterized in that: the electric quantity information includes: current, voltage, frequency, power, total power, peak-to-valley average total power, and the like.
4. An intelligent heating control system based on residential electrical load scheduling according to claim 1, characterized in that: the AI intelligent power supply load scheduling device (5) comprises: the system comprises an AI artificial intelligence big data intelligent cloud platform (5-1), wherein a database is arranged in the AI artificial intelligence big data intelligent cloud platform (5-1); the database has a block chain encryption technology, data are also stored in a fragmentized mode at the cloud end of the server, multiple data are backed up, the safety of the data is guaranteed, different storage strategies are adopted for different data types, and the database is established based on the electric quantity information received by the dynamic load characteristic monitor;
the algorithm model unit (5-2) is an AI intelligent heat supply algorithm model with statistics, time series analysis principle, machine learning, matrix decomposition and self-learning deviation rectifying functions;
the voice recognition and infrared human body induction unit (5-3) interacts with the AI intelligent heating and power load scheduling device through the voice recognition unit, and the infrared human body induction unit detects that no person is in a room and the equipment is not started and people is in the room in an intelligent mode, and starts the equipment by combining the residual load condition, the sensed human body temperature, the model algorithm and other control elements to realize energy-saving control;
the logic processing unit (5-4) is in communication connection with the AI artificial intelligence big data intelligent cloud platform (5-1) and calculates and obtains a control instruction according to an automation control principle and data information of the database; the internal protection function has the functions of overheat protection, fire alarm, fire control joint control, over-power trip and the like, and the fault removing system has the function of self-recovery operation;
the execution unit (5-5) is in communication connection with the logic processing unit (5-4), receives the control instruction of the logic processing unit (5-4), and executes the control instruction; according to the set room temperature, the temperature compensation and correction feedback function is realized;
and the human-computer interaction unit (5-6) is used for scheduling and controlling the equipment through human-computer interaction by utilizing a multi-channel interaction technology according to the established human-computer cooperation model.
5. An intelligent heating control system based on residential electrical load scheduling according to claim 4, wherein: the establishing process of the database in the AI artificial intelligence big data intelligent cloud platform (5-1) comprises load type division, load size calculation, subscriber line residual capacity calculation and heating device starting capacity calculation.
6. An intelligent heating control system based on residential electrical load scheduling according to claim 5, wherein: the remaining subscriber line capacity = total subscriber line capacity-capacity occupied by each distribution branch.
7. An intelligent heating control system based on residential electrical load scheduling according to claim 1, characterized in that: the number of the heat supply management acquisition terminals (1) is matched with that of the heat supply devices (6).
8. An intelligent heating control system based on residential electrical load scheduling according to claim 1, characterized in that: the heating device (6) supplies power through the power distribution branch (7) at the tail end.
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| CN111555275A (en) * | 2020-05-12 | 2020-08-18 | 全球能源互联网研究院有限公司 | Method and system for processing remaining electric quantity of active power distribution network |
| CN111795426A (en) * | 2020-07-17 | 2020-10-20 | 哈电发电设备国家工程研究中心有限公司 | Novel indoor intelligent heating system and method |
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| CN113608486A (en) * | 2021-08-20 | 2021-11-05 | 沈阳世杰电器有限公司 | Distributed load equipment centralized control system and method using existing power grid |
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