Disclosure of Invention
The invention aims to provide an energy information integrated management system and method based on multi-source data, 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 information integrated management method based on multi-source data comprises the following steps:
Step S100: collecting all energy equipment information in an energy information supervision platform to form an equipment information set, wherein the energy equipment information comprises equipment names, functions, specification number information, equipment starting power and starting time; setting any energy equipment in the equipment information set as target equipment, collecting a receiving end signal of the target equipment, and confirming all adjacent equipment information of the target equipment to form an adjacent equipment set; collecting a history operation record of target equipment in a working period to form a history record set;
Step S200: acquiring the working content of any adjacent equipment in the adjacent equipment set according to the equipment information set, analyzing the relevance between any adjacent equipment, and analyzing the importance degree of the target equipment according to the relevance; setting a state of a non-working period as a standby state for a target device with an importance degree greater than a threshold value; for target equipment with importance degree smaller than a threshold value, acquiring information quantity sent by all adjacent equipment in a working period according to an adjacent equipment set, and analyzing information processing efficiency and non-working time period length of the target equipment according to a history record set and the information quantity;
step S300: identifying information sent by all current adjacent devices, and calculating the length of a current working period; acquiring all non-working time periods of the target equipment in the current working period, comparing the power consumption of the target equipment in a standby state with the power consumption of the target equipment in a restarting state according to the length of the non-working time periods, and further performing intelligent control on the state of the target equipment according to a comparison result, wherein the purpose is to improve the resource utilization rate and reduce the waste of resources;
Step S400: and displaying the working state and the information processing efficiency of the target equipment in real time, and feeding back the resource saving amount of the target equipment after one working period is finished.
Further, step S100 includes:
Step S110: collecting all energy equipment information in an energy information supervision platform to form an equipment information set A= { a1, a2, …, as }, wherein a1, a2, …, as represent equipment information obtained by collecting the 1 st, 2 nd, … th and s th energy equipment in the energy information supervision platform; any energy source equipment in the equipment information set A is set as target equipment ai, receiving end signals of the target equipment ai, and confirming all equipment information connected with the target equipment ai according to the receiving end signals to form adjacent equipment sets B= { B1, B2, … and bn }, wherein B1, B2, … and bn represent the 1 st, 2 nd, … th and n energy source equipment information adjacent to the target equipment ai;
Step S120: setting the state of any one time of target equipment ai from on to off as a working period Tx, and obtaining a historical working period set T of the target equipment ai according to big data; the historical operation records of the target device ai in any working period Tx in the historical working period set T are collected to form a historical record set C= { C1, C2, …, cm }, wherein C1, C2, …, cm represents the data processing records of the target device ai in the 1 st, 2 nd, … th and m time periods in any working period Tx.
Further, step S200 includes:
Step S210: matching all energy equipment information in the equipment information set A with any adjacent equipment bj in the adjacent equipment set B, and confirming that the working content characteristics of any adjacent equipment bj are ej, so as to form a working characteristic set E= { E1, E2, …, en }, wherein E1, E2, …, en represent the working content characteristics of the 1 st, 2 nd, … th and n adjacent equipment of the target equipment ai; the Li Yongci embedding algorithm maps the working content features ej of any adjacent device bj in the working feature set E to a k-dimensional vector space to form k-dimensional vector data ej=a (ej 1, ej2, …, ejk) of any adjacent device bj, wherein the word embedding algorithm belongs to the conventional technical means of the person skilled in the art, so that excessive redundant description is not made in the application; at this time, the association distance d (j→q) between any neighboring device bj and other neighboring devices bq is obtained:
d(j→q)＝{maxh(|ejh-eqh|),h＝1,2,…,k}，
Wherein q=1, 2, …, n; when the association distance d (j-q) is smaller than the distance threshold alpha, dividing any adjacent equipment bj and other adjacent equipment bq into the same category, otherwise, dividing the adjacent equipment bj and other adjacent equipment bq into different categories; by traversing the adjacent equipment set B, confirming that the category number of all the adjacent equipment is beta, and when the category number beta is larger, the more the target equipment receives the working service, the higher the importance degree of the target equipment in the system is;
by matching the working content characteristics of all adjacent devices, carrying out association comparison on the characteristic vectors of the working content, confirming the information type of the work of the target device, and facilitating the subsequent analysis of the importance degree of the target device in the system;
Step S220: acquiring the working content characteristics ei of the target equipment ai according to the equipment information set A, and then according to the formulaMatching the equipment quantity epsilon consistent with the working content characteristics of the target equipment ai, and further confirming the importance degree gamma (ai) =o [ beta ]/(s-epsilon) of the target equipment ai in the system according to the category quantity beta, wherein o represents the quality index of all energy equipment in the system; when the importance degree gamma (ai) of the target device ai is greater than the importance threshold gamma, setting the state of the target device ai in the non-operating period within any operating period Tx to a standby state; when the importance degree gamma (ai) is smaller than or equal to an importance threshold gamma, acquiring information amounts respectively transmitted by all adjacent devices in the adjacent device set in any working period Tx to form an information amount set Y= { Y1, Y2, …, yn }, wherein Y1, Y2, …, yn represents information amounts transmitted by the 1 st, 2 nd, … th and n adjacent devices in any working period Tx; confirming the total amount of information received by the target device ai as the information amount setAt this time, it is confirmed that the information average processing efficiency of the target device ai is vi=y/(Tx);
The method comprises the steps of confirming the replaceability degree of target equipment through analyzing the number of the equipment consistent with the working content characteristics of the target equipment in the system, further confirming the importance degree of the target equipment in the system, judging and analyzing the working state of the target equipment according to the importance degree, and improving the accuracy of data analysis;
Step S230: acquiring a data processing record ct of a target device ai in any time period tx in a history record set C, and respectively acquiring information quantity characteristics wj and corresponding information quantity duty ratios p (wj) of the information quantity characteristics wj transmitted by any adjacent device bj according to an information quantity set Y to form an information characteristic set W= { W1, W2, …, wn }, wherein W1, W2, …, wn represent 1 st, 2 nd, … th information characteristic and corresponding information quantity duty ratio in the information quantity set Y; based on the data processing records ct and the information feature set W in the history record set C, according to a formula λt= |ct n wj|/|ct u wj|, wherein j=1, 2, …, n, obtaining the similarity between the data processing records ct of the target device ai and any information feature wj in any time period Tx, obtaining the information feature with the maximum similarity and greater than a similarity threshold value eta according to n similarity values, confirming that the information feature processed in the time period Tx is wr, traversing a working period Tx, further obtaining the number g of the time period Tx when the information feature wr is processed, wherein other data can be processed only when the data processing of the information wr is completed, and confirming that the working section corresponding to the information feature wr is Tx to t (x+g); obtaining working sections corresponding to all information features in an information feature set W according to working sections corresponding to the information features wr as Tx-t (x+g), confirming the information sequence of the target equipment ai for processing any adjacent equipment bj and the time interval generated when processing different information features according to the position sequence of the working sections, and taking the time interval as a non-working time interval of the target equipment ai to form an interval length set Ux of the target equipment ai in any working period Tx; the interval length sets of all working periods are sorted by means of a mean algorithm through traversing the history working period set T to form an interval length rule set U= { U1, U2, …, U (n-1) } of non-working time periods, wherein U1, U2, …, U (n-1) represent the non-working time period length when the target equipment ai processes the 1 st, 2 nd, … th and n information features, and the non-working time period length generated after the data processing is unchanged in order to adjust the running mode of the equipment.
The regular time intervals for device conversion when different adjacent devices are processed by the target device are further analyzed according to the data processing sequence of the target identification to all adjacent devices, which is favorable for analyzing the operation rule of the target device.
Further, step S300 includes:
Step S310: identifying information data sent by n adjacent devices of the current target device ai to obtain information total amount as x y, and confirming that the current working period length is T (x+1) = x y/vi; acquiring starting power p1, starting duration tau and standby power p2 of target equipment ai in the equipment information set A, extracting an interval length rule set U of non-working time periods of the target equipment ai, and controlling working states of all the non-working time periods of the target equipment ai in any working period Tx to be standby states when the length uz of any time period in the interval length rule set U is smaller than the starting duration tau;
step S320: when the interval length rule set U has a time period length uz longer than the starting time length tau, comparing the sizes of p1 tau and uz p2, and if p1 tau < uz p2, controlling the working states of the target equipment ai in the time period length uz to be in a shutdown state, otherwise, controlling the target equipment ai to be in a standby state;
The power consumption of the target equipment in the standby state and the power consumption of the target equipment in the restarting state are compared according to the length of the non-working time period by acquiring all non-working time periods of the target equipment in the current working period, the state of the target equipment is further intelligently controlled according to the comparison result, the energy utilization rate is greatly improved, and the energy waste is reduced;
step S330: obtaining the sum of the time period lengths of all the shutdown states in the current working period as d, and confirming the shutdown times as delta, so as to obtain the resource saving quantity in the current working period as Q=p2-d-delta p1 tau.
Further, the energy information integrated management system, the system includes: the system comprises a data acquisition module, a database, an equipment analysis module, a state control module and a data feedback module;
Collecting all energy equipment information in an energy information supervision platform through a data acquisition module to form an equipment information set, wherein the equipment information set comprises equipment name, functions, specification number information, equipment starting power and starting duration; setting any energy equipment in the equipment information set as target equipment, collecting a receiving end signal of the target equipment, and confirming all adjacent equipment information of the target equipment to form an adjacent equipment set; collecting a history operation record of target equipment in a working period to form a history record set;
Storing all acquired data through a database;
Acquiring the working content of any adjacent device in the adjacent device set according to the device information set by a device analysis module, analyzing the relevance between any adjacent devices, and analyzing the importance degree of the target device according to the relevance; setting a state of a non-working period as a standby state for a target device with an importance degree greater than a threshold value; for target equipment with importance degree smaller than a threshold value, acquiring information quantity sent by all adjacent equipment in a working period according to an adjacent equipment set, and analyzing information processing efficiency and non-working time period length of the target equipment according to a history record set and the information quantity;
Identifying information sent by all current adjacent devices through a state control module, and calculating the length of a current working period; acquiring all non-working time periods of the target equipment in the current working period, comparing the power consumption of the target equipment in a standby state with the power consumption of the target equipment in a restarting state according to the length of the non-working time periods, and further performing intelligent control on the state of the target equipment according to a comparison result, wherein the purpose is to improve the resource utilization rate and reduce the waste of resources;
And displaying the working state and the information processing efficiency of the target equipment in real time through a data feedback module, and feeding back the resource saving amount of the target equipment after one working period is finished.
Further, the data acquisition module comprises an equipment information acquisition unit, an adjacent equipment acquisition unit and a history acquisition unit;
The equipment information acquisition unit is used for acquiring all energy equipment information in the energy information supervision platform to form an equipment information set; the adjacent equipment acquisition unit is used for acquiring a receiving end signal of the target equipment, confirming all adjacent equipment information of the target equipment and forming an adjacent equipment set; the history collection unit is used for collecting the history operation records of the target equipment in the working period to form a history record set.
Further, the equipment analysis module comprises an importance degree analysis unit, a state judgment unit and an efficiency analysis unit;
The importance degree analysis unit is used for acquiring the working content of any adjacent device in the adjacent device set according to the device information set, analyzing the relevance between any adjacent devices and analyzing the importance degree of the target device according to the relevance; the state judging unit is used for judging different states of the target equipment according to the main degree; the efficiency analysis unit is used for acquiring information quantity sent by all adjacent devices in the working period according to the adjacent device set, and analyzing the information processing efficiency and the non-working period length of the target device according to the history record set and the information quantity.
Further, the state control module comprises a power consumption comparison unit and an intelligent control unit;
The power consumption comparison unit is used for acquiring all non-working time periods of the target equipment in the working period, and comparing the power consumption of the target equipment in the standby state with the power consumption of the target equipment in the restarting state according to the length of the non-working time periods; the intelligent control unit is used for intelligently controlling the state of the target equipment according to the comparison result.
Compared with the prior art, the invention has the following beneficial effects:
According to the method, the data processing sequence of target identification on all adjacent devices is confirmed by analyzing and processing the working section corresponding to the information of any adjacent device according to the data characteristics processed in each time period in the historical record set, and the regular time interval for device conversion when different adjacent devices are processed by target devices is further analyzed, so that the operation rule of the target devices is analyzed; by acquiring all non-working time periods of the target equipment in the current working period, comparing the power consumption of the target equipment in the standby state with the power consumption of the target equipment in the restarting state according to the length of the non-working time periods, further intelligently controlling the state of the target equipment according to the comparison result, greatly improving the energy utilization rate and reducing the energy waste.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: an energy information integration management system, the system comprising: the system comprises a data acquisition module, a database, an equipment analysis module, a state control module and a data feedback module;
Collecting all energy equipment information in an energy information supervision platform through a data acquisition module to form an equipment information set, wherein the equipment information set comprises equipment name, functions, specification number information, equipment starting power and starting duration; setting any energy equipment in the equipment information set as target equipment, collecting a receiving end signal of the target equipment, and confirming all adjacent equipment information of the target equipment to form an adjacent equipment set; collecting a history operation record of target equipment in a working period to form a history record set;
the data acquisition module comprises an equipment information acquisition unit, an adjacent equipment acquisition unit and a history acquisition unit;
The equipment information acquisition unit is used for acquiring all energy equipment information in the energy information supervision platform to form an equipment information set; the adjacent equipment acquisition unit is used for acquiring a receiving end signal of the target equipment, confirming all adjacent equipment information of the target equipment and forming an adjacent equipment set; the history collection unit is used for collecting the history operation records of the target equipment in the working period to form a history record set.
Storing all acquired data through a database;
Acquiring the working content of any adjacent device in the adjacent device set according to the device information set by a device analysis module, analyzing the relevance between any adjacent devices, and analyzing the importance degree of the target device according to the relevance; setting a state of a non-working period as a standby state for a target device with an importance degree greater than a threshold value; for target equipment with importance degree smaller than a threshold value, acquiring information quantity sent by all adjacent equipment in a working period according to an adjacent equipment set, and analyzing information processing efficiency and non-working time period length of the target equipment according to a history record set and the information quantity;
The equipment analysis module comprises an importance degree analysis unit, a state judgment unit and an efficiency analysis unit;
The importance degree analysis unit is used for acquiring the working content of any adjacent device in the adjacent device set according to the device information set, analyzing the relevance between any adjacent devices and analyzing the importance degree of the target device according to the relevance; the state judging unit is used for judging different states of the target equipment according to the main degree; the efficiency analysis unit is used for acquiring information quantity sent by all adjacent devices in the working period according to the adjacent device set, and analyzing the information processing efficiency and the non-working period length of the target device according to the history record set and the information quantity.
Identifying information sent by all current adjacent devices through a state control module, and calculating the length of a current working period; acquiring all non-working time periods of the target equipment in the current working period, comparing the power consumption of the target equipment in a standby state with the power consumption of the target equipment in a restarting state according to the length of the non-working time periods, and further performing intelligent control on the state of the target equipment according to a comparison result, wherein the purpose is to improve the resource utilization rate and reduce the waste of resources;
The state control module comprises a power consumption comparison unit and an intelligent control unit;
The power consumption comparison unit is used for acquiring all non-working time periods of the target equipment in the working period, and comparing the power consumption of the target equipment in the standby state with the power consumption of the target equipment in the restarting state according to the length of the non-working time periods; the intelligent control unit is used for intelligently controlling the state of the target equipment according to the comparison result.
And displaying the working state and the information processing efficiency of the target equipment in real time through a data feedback module, and feeding back the resource saving amount of the target equipment after one working period is finished.
Referring to fig. 2, the present invention provides the following technical solutions: an energy information integrated management method based on multi-source data comprises the following steps:
Step S100: collecting all energy equipment information in an energy information supervision platform to form an equipment information set, wherein the energy equipment information comprises equipment names, functions, specification number information, equipment starting power and starting time; setting any energy equipment in the equipment information set as target equipment, collecting a receiving end signal of the target equipment, and confirming all adjacent equipment information of the target equipment to form an adjacent equipment set; collecting a history operation record of target equipment in a working period to form a history record set;
The step S100 includes:
Step S110: collecting all energy equipment information in an energy information supervision platform to form an equipment information set A= { a1, a2, …, as }, wherein a1, a2, …, as represent equipment information obtained by collecting the 1 st, 2 nd, … th and s th energy equipment in the energy information supervision platform; any energy source equipment in the equipment information set A is set as target equipment ai, receiving end signals of the target equipment ai, and confirming all equipment information connected with the target equipment ai according to the receiving end signals to form adjacent equipment sets B= { B1, B2, … and bn }, wherein B1, B2, … and bn represent the 1 st, 2 nd, … th and n energy source equipment information adjacent to the target equipment ai;
Step S120: setting the state of any one time of target equipment ai from on to off as a working period Tx, and obtaining a historical working period set T of the target equipment ai according to big data; the historical operation records of the target device ai in any working period Tx in the historical working period set T are collected to form a historical record set C= { C1, C2, …, cm }, wherein C1, C2, …, cm represents the data processing records of the target device ai in the 1 st, 2 nd, … th and m time periods in any working period Tx.
Step S200: acquiring the working content of any adjacent equipment in the adjacent equipment set according to the equipment information set, analyzing the relevance between any adjacent equipment, and analyzing the importance degree of the target equipment according to the relevance; setting a state of a non-working period as a standby state for a target device with an importance degree greater than a threshold value; for target equipment with importance degree smaller than a threshold value, acquiring information quantity sent by all adjacent equipment in a working period according to an adjacent equipment set, and analyzing information processing efficiency and non-working time period length of the target equipment according to a history record set and the information quantity;
Step S200 includes:
Step S210: matching all energy equipment information in the equipment information set A with any adjacent equipment bj in the adjacent equipment set B, and confirming that the working content characteristics of any adjacent equipment bj are ej, so as to form a working characteristic set E= { E1, E2, …, en }, wherein E1, E2, …, en represent the working content characteristics of the 1 st, 2 nd, … th and n adjacent equipment of the target equipment ai; the Li Yongci embedding algorithm maps the working content features ej of any adjacent device bj in the working feature set E to a k-dimensional vector space to form k-dimensional vector data ej=a (ej 1, ej2, …, ejk) of any adjacent device bj, wherein the word embedding algorithm belongs to the conventional technical means of the person skilled in the art, so that excessive redundant description is not made in the application; at this time, the association distance d (j→q) between any neighboring device bj and other neighboring devices bq is obtained:
d(j→q)＝{maxh(|ejh-eqh|),h＝1,2,…,k}，
Wherein q=1, 2, …, n; when the association distance d (j-q) is smaller than the distance threshold alpha, dividing any adjacent equipment bj and other adjacent equipment bq into the same category, otherwise, dividing the adjacent equipment bj and other adjacent equipment bq into different categories; by traversing the adjacent equipment set B, confirming that the category number of all the adjacent equipment is beta, and when the category number beta is larger, the more the target equipment receives the working service, the higher the importance degree of the target equipment in the system is;
Step S220: acquiring the working content characteristics ei of the target equipment ai according to the equipment information set A, and then according to the formulaMatching the equipment quantity epsilon consistent with the working content characteristics of the target equipment ai, and further confirming the importance degree gamma (ai) =o [ beta ]/(s-epsilon) of the target equipment ai in the system according to the category quantity beta, wherein o represents the quality index of all energy equipment in the system; when the importance degree gamma (ai) of the target device ai is greater than the importance threshold gamma, setting the state of the target device ai in the non-operating period within any operating period Tx to a standby state; when the importance degree gamma (ai) is smaller than or equal to an importance threshold gamma, acquiring information amounts respectively transmitted by all adjacent devices in the adjacent device set in any working period Tx to form an information amount set Y= { Y1, Y2, …, yn }, wherein Y1, Y2, …, yn represents information amounts transmitted by the 1 st, 2 nd, … th and n adjacent devices in any working period Tx; confirming the total amount of information received by the target device ai as the information amount setAt this time, it is confirmed that the information average processing efficiency of the target device ai is vi=y/(Tx);
Step S230: acquiring a data processing record ct of a target device ai in any time period tx in a history record set C, and respectively acquiring information quantity characteristics wj and corresponding information quantity duty ratios p (wj) of the information quantity characteristics wj transmitted by any adjacent device bj according to an information quantity set Y to form an information characteristic set W= { W1, W2, …, wn }, wherein W1, W2, …, wn represent 1 st, 2 nd, … th information characteristic and corresponding information quantity duty ratio in the information quantity set Y; based on the data processing records ct and the information feature set W in the history record set C, according to a formula λt= |ct n wj|/|ct u wj|, wherein j=1, 2, …, n, obtaining the similarity between the data processing records ct of the target device ai and any information feature wj in any time period Tx, obtaining the information feature with the maximum similarity and greater than a similarity threshold value eta according to n similarity values, confirming that the information feature processed in the time period Tx is wr, traversing a working period Tx, further obtaining the number g of the time period Tx when the information feature wr is processed, wherein other data can be processed only when the data processing of the information wr is completed, and confirming that the working section corresponding to the information feature wr is Tx to t (x+g); obtaining working sections corresponding to all information features in an information feature set W according to working sections corresponding to the information features wr as Tx-t (x+g), confirming the information sequence of the target equipment ai for processing any adjacent equipment bj and the time interval generated when processing different information features according to the position sequence of the working sections, and taking the time interval as a non-working time interval of the target equipment ai to form an interval length set Ux of the target equipment ai in any working period Tx; the interval length sets of all working periods are sorted by means of a mean algorithm through traversing the history working period set T to form an interval length rule set U= { U1, U2, …, U (n-1) } of non-working time periods, wherein U1, U2, …, U (n-1) represent the non-working time period length when the target equipment ai processes the 1 st, 2 nd, … th and n information features, and the non-working time period length generated after the data processing is unchanged in order to adjust the running mode of the equipment.
Step S300: identifying information sent by all current adjacent devices, and calculating the length of a current working period; acquiring all non-working time periods of the target equipment in the current working period, comparing the power consumption of the target equipment in a standby state with the power consumption of the target equipment in a restarting state according to the length of the non-working time periods, and further performing intelligent control on the state of the target equipment according to a comparison result, wherein the purpose is to improve the resource utilization rate and reduce the waste of resources;
step S300 includes:
Step S310: identifying information data sent by n adjacent devices of the current target device ai to obtain information total amount as x y, and confirming that the current working period length is T (x+1) = x y/vi; acquiring starting power p1, starting duration tau and standby power p2 of target equipment ai in the equipment information set A, extracting an interval length rule set U of non-working time periods of the target equipment ai, and controlling working states of all the non-working time periods of the target equipment ai in any working period Tx to be standby states when the length uz of any time period in the interval length rule set U is smaller than the starting duration tau;
step S320: when the interval length rule set U has a time period length uz longer than the starting time length tau, comparing the sizes of p1 tau and uz p2, and if p1 tau < uz p2, controlling the working states of the target equipment ai in the time period length uz to be in a shutdown state, otherwise, controlling the target equipment ai to be in a standby state;
step S330: obtaining the sum of the time period lengths of all the shutdown states in the current working period as d, and confirming the shutdown times as delta, so as to obtain the resource saving quantity in the current working period as Q=p2-d-delta p1 tau.
Step S400: and displaying the working state and the information processing efficiency of the target equipment in real time, and feeding back the resource saving amount of the target equipment after one working period is finished.
For example: the step S100 includes:
Step S110: collecting all energy equipment information in the energy information supervision platform to form an equipment information set A= { a1, a2, …, a500}, wherein a1, a2, …, a500 represent equipment information obtained by collecting the 1 st, 2 nd, … th and 500 th energy equipment in the energy information supervision platform; any energy source equipment in the equipment information set A is set as target equipment ai, receiving end signals of the target equipment ai, and confirming all equipment information connected with the target equipment ai according to the receiving end signals to form adjacent equipment sets B= { B1, B2, … and B10}, wherein B1, B2, … and B10 represent the 1 st, 2 nd, … th and 10 th energy source equipment information adjacent to the target equipment ai;
Step S120: setting the state of opening-closing the target equipment ai at any time as a working period Tx=24h, and obtaining a historical working period set T of the target equipment ai according to big data; the historical operation records of the target device ai in any working period Tx in the historical working period set T are collected to form a historical record set C= { C1, C2, …, C720}, wherein C1, C2, …, C720 represent the data processing records of the target device ai in the 1 st, 2 nd, … nd 720 th time period in any working period Tx.
Step S200 includes:
Step S210: matching all energy equipment information in the equipment information set A with any adjacent equipment bj in the adjacent equipment set B, and confirming that the working content characteristics of any adjacent equipment bj are ej, so as to form a working characteristic set E= { E1, E2, …, E10}, wherein E1, E2, …, E10 represent the working content characteristics of the 1 st, 2 nd, … th and 10 th adjacent equipment of the target equipment ai; the Li Yongci embedding algorithm maps the working content feature ej of any adjacent device bj in the working feature set E to a 10-dimensional vector space to form k-dimensional vector data ej=a (ej 1, ej2, …, ej 10) of any adjacent device bj, wherein the word embedding algorithm belongs to the conventional technical means of the person skilled in the art, so that excessive redundant description is not made in the application; at this time, the association distance d (j→q) between any neighboring device bj and other neighboring devices bq is obtained:
d(j→q)＝{maxh(|ejh-eqh|),h＝1,2,…,10}，
Wherein q=1, 2, …,10; when the association distance d (j-q) is smaller than the distance threshold alpha, dividing any adjacent equipment bj and other adjacent equipment bq into the same category, otherwise, dividing the adjacent equipment bj and other adjacent equipment bq into different categories; by traversing the neighboring device set B, confirming that the category number of all neighboring devices is β=3;
Step S220: acquiring the working content characteristics ei of the target equipment ai according to the equipment information set A, and then according to the formulaMatching the number of devices 100 consistent with the working content characteristics of the target device ai, and further confirming the importance degree gamma (ai) =o of the target device ai in the system according to the category number beta, wherein the importance degree gamma/(s-epsilon) =50x3/400=3/8; when the importance degree gamma (ai) is less than or equal to an importance threshold gamma=1/8, acquiring information amounts respectively transmitted by all adjacent devices in the adjacent device set in any working period Tx to form an information amount set y= { Y1, Y2, …, Y10}, wherein Y1, Y2, …, Y10 represents information amounts transmitted by the 1 st, 2 nd, … th and 10 th adjacent devices in any working period Tx; confirming that the total amount of information received by the target device ai is/>, according to the information amount setAt this time, it is confirmed that the information average processing efficiency of the target device ai is/>
Step S230: acquiring a data processing record ct of a target device ai in any time period tx in a history record set C, and respectively acquiring information quantity characteristics wj and corresponding information quantity duty ratios p (wj) of the information quantity characteristics wj transmitted by any adjacent device bj according to an information quantity set Y to form an information characteristic set W= { W1, W2, …, W10}, wherein W1, W2, …, W10 represent 1,2, …,10 information characteristics and corresponding information quantity duty ratios in the information quantity set Y; based on the data processing records ct and the information feature set W in the history record set C, according to a formula λt= |ct n wj|/|ct u wj|, wherein j=1, 2, …,10, obtaining the similarity between the data processing records ct of the target device ai and any information feature wj in any time period Tx, obtaining the information feature with the maximum similarity and greater than a similarity threshold value eta=0.8 according to 10 similarity values, confirming that the information feature processed in the time period tx=t50 is W6, traversing the working period Tx, further obtaining the number g=20 of the time periods Tx when the information feature W6 is processed, wherein only when the data processing of the information wr is completed, processing other data, and confirming that the working section corresponding to the information feature wr is t 50-t 70; obtaining working sections corresponding to all information features in an information feature set W according to working sections corresponding to the information features wr being t 50-t 70, confirming the information sequence sent by any adjacent device bj to be processed by a target device ai and the time interval generated when different information features are processed according to the position sequence of the working sections, and taking the time interval as a non-working time interval of the target device ai to form an interval length set Ux of the target device ai in any working period Tx; the interval length sets of all working periods are arranged by means of a mean algorithm through traversing the history working period set T to form an interval length rule set U= { U1, U2, …, U9} of a non-working period, wherein U1, U2, …, U9 represents the non-working period length when the target device ai processes the 1 st, 2 nd and … th information features, and the non-working period length generated after the data processing is unchanged so as to adjust the operation mode of the device.
Step S300 includes:
Step S310: identifying information data sent by 10 adjacent devices of the current target device ai to obtain information total amount as x y, and confirming that the current working period length is T (x+1) = x y/vi=26h; acquiring starting power p1=70 kw, starting time tau=5s and standby power p2=1 kw of the target equipment ai in the equipment information set a, extracting an interval length rule set U of a non-working time period of the target equipment ai, comparing the sizes of p1×τ and uz×p2 when the interval length uz=10min in the interval length rule set U is greater than the starting time tau=5s, and controlling the working states of the target equipment ai to be in a shutdown state when the interval length uz is greater than the starting time tau=5s;
Step S330: obtaining the sum of the time period lengths of all the shutdown states in the current working period to be d=1h, and confirming the shutdown times to be delta=6, so as to obtain the resource saving quantity in the current working period to be Q=p2 x d-delta x p1 x tau=3600-6 x 70 x 5=1500.
Step S400: and displaying the working state and the information processing efficiency of the target equipment in real time, and feeding back the resource saving amount of the target equipment after one working period is finished.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.