CN115685837A - Energy-saving control system and method based on intelligent power supply - Google Patents
Energy-saving control system and method based on intelligent power supply Download PDFInfo
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Abstract
The invention relates to the technical field of energy-saving control, in particular to an energy-saving control system and method based on an intelligent power supply, which comprises the following steps: the intelligent power control system comprises a data acquisition module, a database, a data analysis module, an energy-saving control regulation module and a power consumption equipment control module, historical data and control authority data of an intelligent power control power consumption equipment switch are acquired and utilized through the data acquisition module, all the acquired data are stored through the database, the historical data and the control authority data are called through the data analysis module, the difficulty of controlling the power consumption equipment in the past is analyzed, a control difficulty threshold value is set through the energy-saving control regulation module, the control authority is adjusted when the control difficulty exceeds the threshold value, the power consumption equipment is centrally controlled through the power consumption equipment control module after the control authority is adjusted, the probability of abnormal problems of energy-saving control is reduced, the centralized control of the power consumption equipment switch is realized, and the efficiency of energy-saving control is improved.
Description
Technical Field
The invention relates to the technical field of energy-saving control, in particular to an energy-saving control system and method based on an intelligent power supply.
Background
The intelligent power supply generally refers to a remote power supply manager, and has power supply distribution and management functions, the intelligent power supply can realize a remote control function, can control a power switch of electric equipment in the authority of the intelligent power supply on any networked computer only by connecting a local area network or the Internet, inquires, connects, disconnects or restarts the power supply of each equipment of a downstream port of the intelligent power supply, and can control the equipment to be shut down to play a role in energy-saving control when monitoring that the equipment in a building is not used;
however, the existing energy-saving control method still has some problems: firstly, in the prior art, when too many electric devices are used in a building, the on-off of all the electric devices is controlled by only one networking computer, so that the problem of abnormal control is easily caused, and the prior art cannot reduce the probability of the abnormal control problem; secondly, use many networking computer control consumer switch in the authority, if the time that equipment is not used is too dispersed, can't realize the centralized control of consumer switch, reduced control efficiency, prior art can't control for the consumer in the networking computer distribution suitable authority, can't effectively improve energy-conserving control efficiency.
Therefore, an energy-saving control system and method based on an intelligent power supply are needed to solve the above problems.
Disclosure of Invention
The invention aims to provide an energy-saving control system and method based on an intelligent power supply, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an energy-saving control system based on an intelligent power supply, the system comprising: the system comprises a data acquisition module, a database, a data analysis module, an energy-saving control and regulation module and an electric equipment control module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the energy-saving control and regulation module, and the output end of the energy-saving control and regulation module is connected with the input end of the electric equipment control module;
the data acquisition module is used for acquiring historical data and control authority data for controlling the on-off of the electric equipment by using the intelligent power supply and transmitting all acquired data to the database;
the database is used for storing all collected data;
the data analysis module is used for calling historical data and control authority data and analyzing the difficulty of controlling the electric equipment in the past;
the energy-saving control adjusting module is used for setting a control difficulty threshold value and adjusting the control authority when the control difficulty exceeds the threshold value;
and the electric equipment control module is used for performing centralized control on the electric equipment after the control authority is adjusted.
Furthermore, the data acquisition module comprises an equipment data acquisition unit and a control authority acquisition unit;
the output ends of the equipment data acquisition unit and the control authority acquisition unit are connected with the input end of the database;
the equipment data acquisition unit is used for acquiring historical data of controlling the power switch of the electric equipment on a networked computer after the intelligent power supply is connected with the Internet;
the control authority acquisition unit is used for acquiring control authority data of different networked computers.
Further, the data analysis module comprises a control data analysis unit and a control difficulty analysis unit;
the input end of the control data analysis unit is connected with the output end of the database, and the output end of the control data analysis unit is connected with the input end of the control difficulty analysis unit;
the control data analysis unit is used for calling and analyzing the time data for controlling the power supply of the electric equipment to be turned off in the past;
the control difficulty analysis unit is used for analyzing the difficulty of controlling the power supply of the electric equipment in the past.
Furthermore, the energy-saving control adjusting module comprises a control object grouping unit and a control authority dividing unit;
the input end of the control object grouping unit is connected with the output end of the control difficulty analysis unit, and the output end of the control object grouping unit is connected with the input end of the control authority dividing unit;
the control object grouping unit is used for setting a control difficulty threshold, comparing the difficulty of controlling the power supply of the electric equipment to be closed with the threshold in the prior art, grouping the electric equipment in the control authority when the control difficulty exceeds the threshold, and selecting the optimal grouping mode;
the control authority dividing unit is used for setting the control authorities of different networked computers according to the optimal grouping mode.
Furthermore, the electric equipment control module comprises a building environment monitoring unit and a closing centralized control unit;
the input end of the building environment monitoring unit is connected with the output end of the control authority dividing unit, and the output end of the building environment monitoring unit is connected with the input end of the closing centralized control unit;
the building environment monitoring unit is used for monitoring the electric equipment in the building environment in real time after the control authority is adjusted;
the closing centralized control unit is used for verifying the monitored use condition of the electric equipment in the control authority by using a networking computer after the intelligent power supply is connected with the Internet, and controlling to close the electric equipment when the electric equipment is not used by people.
An energy-saving control method based on an intelligent power supply comprises the following steps:
s1: collecting historical data and control authority data for controlling the on-off of electric equipment by using an intelligent power supply;
s2: calling historical data and control authority data, and analyzing the difficulty of controlling the electric equipment in the past;
s3: setting a control difficulty threshold, and grouping the electric equipment when the control difficulty exceeds the threshold;
s4: selecting an optimal grouping mode, and adjusting the control authority according to the optimal grouping mode;
s5: and after the control authority is adjusted, the electric equipment is controlled in a centralized manner.
Further, in step S1: the method comprises the steps of collecting time data of closing all equipment controlled in the control authority by different networked computers for m days, obtaining the time of closing all the equipment controlled in the control authority by one random networked computer in the past one random day after an intelligent power supply is connected with the Internet, and arranging the time in the sequence from front to back to obtain a time set of a = { a = 1 ，a 2 ，…，a n Where n represents the number of devices within the control authority of the corresponding networked computer;
in step S2: calculating the time difference wi of the control of all the equipment in the control authority of a random networking computer in one day according to the following formula:
wherein, a j+1 And a j Respectively representing the time for controlling the j +1 th equipment and the j equipment to be closed in one day corresponding to the computer in the past, obtaining a time difference set of closing all the equipment in the control authority of one networking computer in the past for m days as w = { w1, w 2., wi.,. Wm }, and obtaining the difficulty Qv of controlling the electric equipment in the past by one networking computer according to the following formula:
the difficulty set of the networked computers for controlling the electric equipment in the past is obtained through the same calculation mode and is Q = { Q1, Q2., qv.,. And Qk }, wherein k represents the number of computers for controlling the electric equipment in the same building, and the comprehensive difficulty coefficient for controlling the electric equipment in the corresponding building in the past is obtained as Q:
through collecting historical data, the control centralization of each computer is judged by analyzing the time difference of the conventional control electric equipment, and the higher the difference isThe more dispersed the control time, the worse the control centralization, the more difficulty in analyzing the networked computers to realize centralized control of the electric equipment, and the large amount of time data are collected by a big data analysis technology, so that the accuracy of the analysis result is improved, and meanwhile, the plurality of networked computers are used for respectively controlling different electric equipment in the authority, so that the probability of abnormal control is reduced.
Further, setting a control difficulty threshold value as F, and comparing q with F: if q is less than or equal to F, the control difficulty is low; if q is greater than F, the control difficulty is high, extracting the electric equipment in the control authority of k networking computers, randomly dividing the electric equipment in the same building into k groups, obtaining the time of controlling and closing the random group of electric equipment in the past at random one day after the electric equipment is grouped according to a random grouping formula, arranging the time of controlling and closing the random group of electric equipment in the past at random one day according to the sequence from front to back, obtaining the time set of controlling and closing the random group of electric equipment in the past at random one day as t = { t1, t2,. Once, tf }, wherein F represents the number of the random group of electric equipment, and calculating the time difference degree of controlling and closing the random group of electric equipment in the past at random one day as Ge according to the following formula:
wherein, t j+1 And t j Respectively representing the time of controlling and closing the j +1 th device and the j-th device in the past at random one day, calculating a time difference set of controlling and closing the random group of electric devices in the past m days in the same way to be G = { G1, G2,.., ge,.., gm }, and obtaining a comprehensive time difference Wz of controlling and closing the random group of electric devices in the past m days,
after the electric equipment in each group is grouped according to a random grouping formula through the same calculation mode, the comprehensive time difference set of the electric equipment in each group which is controlled to be closed in the past m days is W = { W1, W2,. Farewer, wz,. Farewer, wk }, and the comprehensive difficulty coefficient of the electric equipment in the corresponding building which is grouped according to the random grouping formula is Yu:
the method comprises the steps of obtaining a comprehensive difficulty coefficient set for controlling electric equipment in a corresponding building after grouping according to different grouping modes through the same calculation mode, wherein the comprehensive difficulty coefficient set is Y = { Y1, Y2, ·, yu., yx }, wherein x grouping modes are available, comparing the comprehensive difficulty coefficients, selecting a grouping mode with the lowest comprehensive difficulty coefficient as an optimal grouping mode, judging that the control time of the electric equipment in the corresponding building is too dispersed if the control difficulty is lower than a threshold value, needing to readjust the control authority of each computer, randomly grouping the electric equipment, analyzing the time difference degree of the controlled electric equipment after grouping, further analyzing the control difficulty, selecting the grouping mode with the lowest control difficulty, handing the equipment in the same group to the same computer for control, adjusting the control authority of the computer, facilitating the realization of the centralized control of the switch of the electric equipment and further improving the control efficiency of energy conservation.
Further, in step S5: acquiring the electric equipment of each group after grouping according to the optimal grouping mode, and adjusting the control authority of the k networked computers: and adjusting that each computer has the control authority of a random group of electric equipment after being grouped according to the optimal grouping mode, and after the control authority is adjusted, performing centralized control on the electric equipment in the control authority by using the networked computers.
Compared with the prior art, the invention has the following beneficial effects:
the invention reduces the probability of abnormal control problem by using a plurality of networked computers to respectively control different electric equipment in the authority limit; the control centralization of each computer is judged by collecting historical data and analyzing the time difference of the conventional control electric equipment, the difficulty of realizing centralized control of the electric equipment by networking computers is further analyzed, and a large amount of time data is collected as a basis by a big data analysis technology, so that the accuracy of an analysis result is improved; when the control difficulty is lower than the threshold value, the control time of the electric equipment in the corresponding building is judged to be too dispersed, the control authority of each computer is readjusted, the electric equipment is randomly grouped, the time difference degree of the electric equipment to be controlled after grouping is analyzed, the control difficulty is further analyzed, the grouping mode with the lowest control difficulty is selected, the equipment in the same group is handed to the same computer for control, the control authority of the computer is adjusted, the centralized control of the switch of the electric equipment is realized, and the efficiency of energy-saving control is further improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram of an intelligent power supply based energy saving control system of the present invention;
fig. 2 is a flow chart of an energy-saving control method based on an intelligent power supply.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The invention will be further described with reference to fig. 1-2 and the specific embodiments.
The first embodiment is as follows:
as shown in fig. 1, the present embodiment provides an energy saving control system based on an intelligent power supply, and the system includes: the system comprises a data acquisition module, a database, a data analysis module, an energy-saving control and regulation module and an electric equipment control module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the energy-saving control and regulation module, and the output end of the energy-saving control and regulation module is connected with the input end of the electric equipment control module;
the data acquisition module is used for acquiring historical data and control authority data for controlling the on-off of the electric equipment by using the intelligent power supply and transmitting all the acquired data to the database;
the database is used for storing all the acquired data;
the data analysis module is used for calling historical data and control authority data and analyzing the difficulty of controlling the electric equipment in the past;
the energy-saving control adjusting module is used for setting a control difficulty threshold value and adjusting the control authority when the control difficulty exceeds the threshold value;
and the electric equipment control module is used for performing centralized control on the electric equipment after adjusting the control authority.
The data acquisition module comprises an equipment data acquisition unit and a control authority acquisition unit;
the output ends of the equipment data acquisition unit and the control authority acquisition unit are connected with the input end of the database;
the equipment data acquisition unit is used for acquiring historical data of controlling the power switch of the electric equipment on a networked computer after the intelligent power supply is connected with the Internet;
the control authority acquisition unit is used for acquiring control authority data of different networked computers.
The data analysis module comprises a control data analysis unit and a control difficulty analysis unit;
the input end of the control data analysis unit is connected with the output end of the database, and the output end of the control data analysis unit is connected with the input end of the control difficulty analysis unit;
the control data analysis unit is used for calling and analyzing the time data for controlling the power supply of the electric equipment in the past;
the control difficulty analysis unit is used for analyzing the difficulty of controlling the power supply of the electric equipment in the past.
The energy-saving control adjusting module comprises a control object grouping unit and a control authority dividing unit;
the input end of the control object grouping unit is connected with the output end of the control difficulty analysis unit, and the output end of the control object grouping unit is connected with the input end of the control authority dividing unit;
the control object grouping unit is used for setting a control difficulty threshold, comparing the difficulty of controlling the power supply of the electric equipment to be closed with the threshold in the prior art, grouping the electric equipment in the control authority when the control difficulty exceeds the threshold, and selecting the optimal grouping mode;
the control authority dividing unit is used for setting the control authorities of different networked computers according to the optimal grouping mode.
The electric equipment control module comprises a building environment monitoring unit and a closing centralized control unit;
the input end of the building environment monitoring unit is connected with the output end of the control authority dividing unit, and the output end of the building environment monitoring unit is connected with the input end of the closing centralized control unit;
the building environment monitoring unit is used for monitoring the electric equipment in the building environment in real time after the control authority is adjusted;
and the closing centralized control unit is used for verifying the monitored use condition of the electric equipment in the control authority by using a networking computer after the intelligent power supply is connected with the Internet, and controlling to close the electric equipment when the electric equipment is not used by people.
The second embodiment:
as shown in fig. 2, the present embodiment provides an energy saving control method based on an intelligent power supply, which is implemented based on a control system in the embodiment, and specifically includes the following steps:
s1: the method comprises the steps of collecting historical data and control authority data of controlling the switch of electric equipment by using an intelligent power supply, collecting time data of controlling all equipment in the control authority by different networked computers for m =3 days, obtaining the time of controlling all equipment in the control authority to be closed by one random networked computer one day in the past after the intelligent power supply is connected with the Internet, and arranging the time in the sequence from front to back to obtain a time set of a = { a = 1 ，a 2 ，a 3 }＝{8：00，8：20，8：30}；
S2: calling historical data and control authority data, analyzing the difficulty of controlling the electric equipment in the past, and obtaining the control authority data according to a formula
Calculating the time difference wi of closing all the equipment controlled in the control authority by one random networking computer in one random day, wherein the time difference wi is approximately equal to 22.4, obtaining the time difference set of closing all the equipment controlled in the control authority by one random networking computer in m =3 days by the same calculation mode, wherein the time difference set is w = { w1, w2, w3} = {22.4, 23.5, 18.8}, and controlling all the equipment in the control authority in m =3 days according to a formula
The difficulty Qv of a random networking computer for controlling the electric equipment in the past is approximately equal to 21.6, the difficulty set of the networking computer for controlling the electric equipment in the past is Q = { Q1, Q2} = {21.6, 20.6} through the same calculation mode, and the comprehensive difficulty coefficient for controlling the electric equipment in the corresponding building in the past is Q:
s3: setting a control difficulty threshold, grouping the electric equipment when the control difficulty exceeds the threshold, setting the control difficulty threshold to be F =20, and comparing q with F: q. q.s>And F, explaining that the control difficulty is high, extracting the electric equipment in the control authority of k =2 networking computers, randomly dividing the electric equipment in the same building into 2 groups, obtaining grouping according to a random grouping formula, arranging the time of controlling to close the random group of electric equipment in the past at random one day in the sequence from front to back, and obtaining the time set of controlling to close the random group of electric equipment in the past at random one day, wherein the time set is t = { t1, t2} = {8:00,8:10} according to the formula
Calculating the time difference degree of the random group of electric equipment controlled to be closed at random one day in the past as Ge =10, calculating the time difference degree set of the random group of electric equipment controlled to be closed at m =3 days in the same way as G = { G1, G2, G3} = {10,5,8}, and obtaining the comprehensive time difference degree of the random group of electric equipment controlled to be closed at m =3 days in the past as Wz,
after grouping is performed according to a random grouping mode in the same calculation mode, the comprehensive time difference set of each group of electric equipment controlled to be closed in the past m =3 days is W = { W1, W2} = {7.6,8.2}, and the comprehensive difficulty coefficient for controlling the electric equipment in the corresponding building after grouping according to the random grouping mode is Yu:
the comprehensive difficulty coefficient set for controlling the electric equipment in the corresponding building after grouping according to different grouping modes is obtained through the same calculation mode, wherein Y = { Y1, Y2, Y3, Y4, Y5} = {7.9, 10.2,6.9,7.5, 12}, and x =5 grouping modes are total;
s4: selecting an optimal grouping mode, adjusting control authority according to the optimal grouping mode, and comparing comprehensive difficulty coefficients, wherein the lowest comprehensive difficulty coefficient is as follows: y3=6.9, selecting a grouping mode with the lowest comprehensive difficulty coefficient as an optimal grouping mode;
s5: after the control authority is adjusted, the electric equipment is controlled in a centralized mode, the electric equipment of each group grouped according to the optimal grouping mode is obtained, and the control authority of k =2 networked computers is adjusted: and adjusting that each computer has the control authority of a random group of electric equipment after being grouped according to the optimal grouping mode, and after the control authority is adjusted, performing centralized control on the electric equipment in the control authority by using the networked computers.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides an energy-saving control system based on intelligent power supply which characterized in that: the system comprises: the system comprises a data acquisition module, a database, a data analysis module, an energy-saving control and regulation module and an electric equipment control module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the energy-saving control and regulation module, and the output end of the energy-saving control and regulation module is connected with the input end of the electric equipment control module;
the data acquisition module is used for acquiring historical data and control authority data for controlling the switch of the electric equipment by using the intelligent power supply and transmitting all the acquired data to the database;
the database is used for storing all collected data;
the data analysis module is used for calling historical data and control authority data and analyzing the difficulty of controlling the electric equipment in the past;
the energy-saving control adjusting module is used for setting a control difficulty threshold value and adjusting the control authority when the control difficulty exceeds the threshold value;
and the electric equipment control module is used for performing centralized control on the electric equipment after the control authority is adjusted.
2. The energy-saving control system based on the intelligent power supply as claimed in claim 1, wherein: the data acquisition module comprises an equipment data acquisition unit and a control authority acquisition unit;
the output ends of the equipment data acquisition unit and the control authority acquisition unit are connected with the input end of the database;
the equipment data acquisition unit is used for acquiring historical data of controlling the power switch of the electric equipment on a networked computer after the intelligent power supply is connected with the Internet;
the control authority acquisition unit is used for acquiring control authority data of different networked computers.
3. The energy-saving control system based on the intelligent power supply as claimed in claim 1, wherein: the data analysis module comprises a control data analysis unit and a control difficulty analysis unit;
the input end of the control data analysis unit is connected with the output end of the database, and the output end of the control data analysis unit is connected with the input end of the control difficulty analysis unit;
the control data analysis unit is used for calling and analyzing the time data for controlling the power supply of the electric equipment to be turned off in the past;
the control difficulty analysis unit is used for analyzing the difficulty of controlling the power supply of the electric equipment in the past.
4. The energy-saving control system based on the intelligent power supply as claimed in claim 3, wherein: the energy-saving control adjusting module comprises a control object grouping unit and a control authority dividing unit;
the input end of the control object grouping unit is connected with the output end of the control difficulty analysis unit, and the output end of the control object grouping unit is connected with the input end of the control authority dividing unit;
the control object grouping unit is used for setting a control difficulty threshold, comparing the difficulty of controlling the power supply of the electric equipment to be closed with the threshold in the prior art, grouping the electric equipment in the control authority when the control difficulty exceeds the threshold, and selecting the optimal grouping mode;
the control authority dividing unit is used for setting the control authorities of different networked computers according to the optimal grouping mode.
5. The energy-saving control system based on the intelligent power supply as claimed in claim 4, wherein: the electric equipment control module comprises a building environment monitoring unit and a closing centralized control unit;
the input end of the building environment monitoring unit is connected with the output end of the control authority dividing unit, and the output end of the building environment monitoring unit is connected with the input end of the closing centralized control unit;
the building environment monitoring unit is used for monitoring the electric equipment in the building environment in real time after the control authority is adjusted;
the closing centralized control unit is used for verifying the monitored use condition of the electric equipment in the control authority by using a networking computer after the intelligent power supply is connected with the Internet, and controlling to close the electric equipment when the electric equipment is not used by people.
6. An energy-saving control method based on an intelligent power supply is characterized in that: the method comprises the following steps:
s1: collecting historical data and control authority data for controlling the switch of the electric equipment by using the intelligent power supply;
s2: calling historical data and control authority data, and analyzing the difficulty of controlling the electric equipment in the past;
s3: setting a control difficulty threshold, and grouping the electric equipment when the control difficulty exceeds the threshold;
s4: selecting an optimal grouping mode, and adjusting the control authority according to the optimal grouping mode;
s5: and after the control authority is adjusted, the electric equipment is controlled in a centralized manner.
7. The energy-saving control method based on the intelligent power supply as claimed in claim 6, wherein: in step S1: the method comprises the steps of collecting time data of closing all equipment controlled in the control authority by different networked computers for m days, obtaining the time of closing all the equipment controlled in the control authority by one random networked computer in the past one random day after an intelligent power supply is connected with the Internet, and arranging the time in the sequence from front to back to obtain a time set of a = { a = 1 ，a 2 ，…，a n Where n represents the number of devices within the control authority of the corresponding networked computer;
in step S2: calculating the time difference degree wi of closing all the equipment controlled in the control authority in one day randomly by one networking computer according to the following formula:
wherein, a j+1 And a j Respectively representing the time for controlling the j +1 th equipment and the j equipment to be closed in one day corresponding to the computer in the past, obtaining a time difference set of closing all the equipment in the control authority of one networking computer in the past for m days as w = { w1, w 2., wi.,. Wm }, and obtaining the difficulty Qv of controlling the electric equipment in the past by one networking computer according to the following formula:
the difficulty set of the networked computers for controlling the electric equipment in the past is obtained through the same calculation mode and is Q = { Q1, Q2., qv.,. And Qk }, wherein k represents the number of computers for controlling the electric equipment in the same building, and the comprehensive difficulty coefficient for controlling the electric equipment in the corresponding building in the past is obtained as Q:
8. the energy-saving control method based on the intelligent power supply as claimed in claim 7, wherein: in step S3: setting a control difficulty threshold value as F, and comparing q with F: if q is less than or equal to F, the control difficulty is low; if q is greater than F, the control difficulty is high, extracting the electric equipment in the control authority of k networking computers, randomly dividing the electric equipment in the same building into k groups, obtaining the time of controlling and closing the random group of electric equipment in the past at random one day after the electric equipment is grouped according to a random grouping formula, arranging the time of controlling and closing the random group of electric equipment in the past at random one day according to the sequence from front to back, obtaining the time set of controlling and closing the random group of electric equipment in the past at random one day as t = { t1, t2,. Once, tf }, wherein F represents the number of the random group of electric equipment, and calculating the time difference degree of controlling and closing the random group of electric equipment in the past at random one day as Ge according to the following formula:
wherein, t j+1 And t j Respectively representing the time of the j +1 th device and the time of the j device which are controlled to be closed in the past at random one day, calculating a time difference set of a random group of electric devices which are controlled to be closed in the past m days in the same mode to be G = { G1, G2,. Once, ge,. Once, gm }, and obtaining a comprehensive time difference Wz of the random group of electric devices which are controlled to be closed in the past m days,
after the electric equipment in each group is grouped according to a random grouping formula through the same calculation mode, the comprehensive time difference set of the electric equipment in each group which is controlled to be closed in the past m days is W = { W1, W2,. Farewer, wz,. Farewer, wk }, and the comprehensive difficulty coefficient of the electric equipment in the corresponding building which is grouped according to the random grouping formula is Yu:
obtaining a comprehensive difficulty coefficient set for controlling the electric equipment in the corresponding building after grouping according to different grouping modes in the same calculation mode, wherein the comprehensive difficulty coefficient set is Y = { Y1, Y2,. Once, yu.. Once, yx }, and x grouping modes are shared;
in step S4: and comparing the comprehensive difficulty coefficients, and selecting a grouping mode with the lowest comprehensive difficulty coefficient as an optimal grouping mode.
9. The energy-saving control method based on the intelligent power supply as claimed in claim 8, wherein: in step S5: acquiring the electric equipment of each group after grouping according to the optimal grouping mode, and adjusting the control authority of the k networked computers: and adjusting that each computer has the control authority of a random group of electric equipment after being grouped according to the optimal grouping mode, and after the control authority is adjusted, performing centralized control on the electric equipment in the control authority by using the networked computers.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017042783A1 (en) * | 2016-07-20 | 2017-03-16 | Universidad Tecnológica De Panamá | System for controlling the electrical energy for a group of buildings |
| CN106682763A (en) * | 2016-11-25 | 2017-05-17 | 云南电网有限责任公司昆明供电局 | Power load optimization and prediction method for massive sample data |
| CN107341562A (en) * | 2017-05-25 | 2017-11-10 | 杭州赫智电子科技有限公司 | A kind of building energy management system and energy management method for merging demand response |
| CN111293786A (en) * | 2020-03-27 | 2020-06-16 | 四川虹美智能科技有限公司 | Intelligent power supply management method, device and system |
| CN111770479A (en) * | 2020-06-29 | 2020-10-13 | 吴义魁 | Grouping management method based on wireless Internet of things and related device |
| CN112232863A (en) * | 2020-10-13 | 2021-01-15 | 北京邮电大学 | Virtual resource management method and system based on cloud edge-side cooperation |
| CN113961303A (en) * | 2020-07-20 | 2022-01-21 | 瞻博网络公司 | Data center resource monitoring for managing message load balancing with reordering considerations |
| CN115169426A (en) * | 2022-02-22 | 2022-10-11 | 国网山东省电力公司信息通信公司 | Anomaly detection method and system based on similarity learning fusion model |
-
2022
- 2022-11-01 CN CN202211357996.2A patent/CN115685837B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017042783A1 (en) * | 2016-07-20 | 2017-03-16 | Universidad Tecnológica De Panamá | System for controlling the electrical energy for a group of buildings |
| CN106682763A (en) * | 2016-11-25 | 2017-05-17 | 云南电网有限责任公司昆明供电局 | Power load optimization and prediction method for massive sample data |
| CN107341562A (en) * | 2017-05-25 | 2017-11-10 | 杭州赫智电子科技有限公司 | A kind of building energy management system and energy management method for merging demand response |
| CN111293786A (en) * | 2020-03-27 | 2020-06-16 | 四川虹美智能科技有限公司 | Intelligent power supply management method, device and system |
| CN111770479A (en) * | 2020-06-29 | 2020-10-13 | 吴义魁 | Grouping management method based on wireless Internet of things and related device |
| CN113961303A (en) * | 2020-07-20 | 2022-01-21 | 瞻博网络公司 | Data center resource monitoring for managing message load balancing with reordering considerations |
| CN112232863A (en) * | 2020-10-13 | 2021-01-15 | 北京邮电大学 | Virtual resource management method and system based on cloud edge-side cooperation |
| CN115169426A (en) * | 2022-02-22 | 2022-10-11 | 国网山东省电力公司信息通信公司 | Anomaly detection method and system based on similarity learning fusion model |
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