CN113086789B - Intelligent building control system and control method - Google Patents
Intelligent building control system and control method Download PDFInfo
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- CN113086789B CN113086789B CN202110353039.1A CN202110353039A CN113086789B CN 113086789 B CN113086789 B CN 113086789B CN 202110353039 A CN202110353039 A CN 202110353039A CN 113086789 B CN113086789 B CN 113086789B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B3/00—Applications of devices for indicating or signalling operating conditions of elevators
- B66B3/002—Indicators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/02—Control systems without regulation, i.e. without retroactive action
- B66B1/06—Control systems without regulation, i.e. without retroactive action electric
- B66B1/14—Control systems without regulation, i.e. without retroactive action electric with devices, e.g. push-buttons, for indirect control of movements
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
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- Elevator Control (AREA)
Abstract
The invention relates to an intelligent control system for a building, which comprises: the first acquisition equipment is used for acquiring and updating first information about the personnel flow condition of each floor; the second acquisition equipment is used for acquiring and updating second information about the use condition of each elevator; and a server configured to: processing third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transportation data acquired by being connected with the building management platform; under the condition that all elevators are put into operation, all floors are dynamically divided to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and combined with third and fourth information; and calling at least one pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulating and controlling the operation strategy of each elevator based on the first and second information and combining the regulation and control rule to dynamically respond to the elevator taking demand calls of different floors.
Description
Technical Field
The invention relates to the technical field of intelligent building control, in particular to an intelligent building control system and a control method.
Background
With the development of urbanization process and the progress of social economy, high-rise buildings are emerging continuously, and elevators are widely applied as main tools for vertical transportation in the high-rise buildings. At present, elevator products are meeting the basic riding requirements of users, and are developing towards the directions of energy conservation, intellectualization and the like, how to carry out more effective optimized dispatching on the elevator, improve the operation efficiency of the elevator and reduce the operation energy consumption of the elevator is a problem to be considered urgently by current elevator manufacturers and relevant research and development mechanisms. In the prior art, the elevator speed is controlled mainly by three methods, i.e. on the time basis, on the relative distance basis and on the absolute distance basis. In all of the three elevator speed control modes, a rated speed is selected to operate according to a destination, the most reasonable operation speed is not selected according to the passenger flow condition, the potential transportation capacity of the elevator cannot be fully exerted, and the transportation efficiency is reduced. Moreover, when the elevator runs at a high speed, passengers easily miss the elevator, so that the waiting time of the passengers is increased, and energy is further wasted and elevator parts are abraded.
In the prior art, patent document CN109534118B provides an intelligent control method for the running speed of an elevator, which intelligently adjusts the running speed of the elevator according to the time interval of a call hot spot of the elevator, and aims to solve the problem that passenger flow is not considered in the speed selection mode of the elevator in the prior art.
However, the above-mentioned technical solution considers only the case of a single elevator run, when multiple elevators run simultaneously: on one hand, when passing through floors with high probability of call occurrence, a plurality of elevators all adopt slow descent, wherein most of the elevators are unnecessary slow descent, so that the total conveying efficiency of the plurality of elevators is reduced, and particularly the influence on passengers at higher floors is obviously enhanced; on the other hand, especially in the peak period of going downstairs, a plurality of floors with high probability of call occurrence on different floors exist in the same time period, according to the technical scheme, namely, a plurality of elevators always slowly descend and cannot rapidly descend, but the transportation capacity of the elevator is reduced in the time period; in addition, the elevator always responds to the call of going downstairs from a higher floor preferentially, so that when the elevator going downstairs arrives at a lower floor, the elevator is fully loaded or has more passengers, and the elevator taking requirement of the lower floor cannot be met.
Furthermore, on the one hand, due to the differences in understanding to the person skilled in the art; on the other hand, since the applicant has studied a great deal of literature and patents when making the present invention, but the disclosure is not limited thereto and the details and contents thereof are not listed in detail, it is by no means the present invention has these prior art features, but the present invention has all the features of the prior art, and the applicant reserves the right to increase the related prior art in the background.
Disclosure of Invention
In order to solve the problem that passenger flow is not considered in the elevator speed selection mode in the prior art, patent document CN109534118B in the prior art provides an intelligent control method for the elevator running speed, which intelligently adjusts the running speed of an elevator according to the elevator call hotspot time interval.
However, the above solution is limited to the case of single elevator operation, when multiple elevators operate synchronously: on one hand, when passing through floors with high probability of call occurrence, a plurality of elevators all adopt slow descent, wherein most of the elevators are unnecessary slow descent, so that the total conveying efficiency of the plurality of elevators is reduced, and particularly the influence on passengers at higher floors is obviously enhanced; on the other hand, especially in the peak period of going downstairs, a plurality of floors with high probability of call occurrence on different floors exist in the same time period, according to the technical scheme, namely, a plurality of elevators always slowly descend and cannot rapidly descend, but the transportation capacity of the elevator is reduced in the time period; in addition, the elevator always responds to the call of going downstairs from a higher floor preferentially, so that when the elevator going downstairs arrives at a lower floor, the elevator is fully loaded or has more passengers, and the elevator taking requirement of the lower floor cannot be met.
Therefore, the invention provides an intelligent building control system by using historical elevator conveying data to capture different elevator waiting characteristics of each floor under the current elevator quantity and the current building floor number, not only adaptively adjusts preset thresholds and parameters in the system according to the captured different elevator waiting characteristics of each floor, but also calls proper regulation and control rules by considering the elevator waiting requirements of different floors and the actual residual capacity of each elevator when the elevator is actually put into operation, thereby realizing the aim of dynamically responding to elevator taking requirement calls of different floors based on the scheduling rules. The building intelligent control system comprises: the first acquisition equipment is distributed on each floor in the building and is used for acquiring and updating first information about the personnel flow condition of each floor; the second acquisition equipment is distributed in each elevator and is used for acquiring and updating second information about the service condition of each elevator; and a server configured to: processing and obtaining third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transporting data obtained by connecting with a building management platform; under the condition that all elevators are put into operation, all floors are dynamically divided to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and combined with third and fourth information; and calling at least one pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulating and controlling the operation strategy of each elevator based on the first and second information and combining the regulation and control rule to dynamically respond to the elevator taking demand calls of different floors.
The application also provides a building intelligence control system, includes: the first acquisition equipment is distributed on each floor in the building and is used for acquiring and updating first information about the personnel flow condition of each floor; the second acquisition equipment is distributed in each elevator and is used for acquiring and updating second information about the service condition of each elevator; and a server, wherein the first acquisition device is configured to: judging and obtaining the current elevator waiting demand and the predicted elevator waiting demand in each floor through intelligent visual recognition; generating first information about the flow condition of people on each floor at least based on dynamic travel distance data between at least one predicted elevator waiting person corresponding to the predicted elevator waiting requirement and an elevator waiting area, actively transmitting and updating the first information to a server when the first information meets a trigger condition, and receiving an operation strategy of each elevator responding to elevator taking requirement calls of different floors, wherein the operation strategy is obtained by the server at least based on the first information and the second information; and generating elevator coming information used for pushing the information to at least one intelligent mobile terminal which is positioned on the floor where the first acquisition equipment is positioned and is operated by elevator taking personnel and is in wireless connection with the first acquisition equipment by setting a connection mode based on the second information acquired in real time and the operation strategy.
According to a preferred embodiment, the server is configured to dynamically partition all floors in the following manner: dynamically dividing at least one floor into at least one type of demand floor based on the elevator taking demand call and the fourth information received by the at least one floor; performing distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on distribution statistical results to obtain a distribution form; all floors are dynamically divided into at least two gradients based on at least the determined profile and the third information.
According to a preferred embodiment, the at least one type of demand floor may be one of a first type of demand floor on which an elevator taking demand call occurs, a second type of demand floor on which an elevator taking demand call does not occur but is in a hot spot and on which an elevator taking demand is expected, and a third type of demand floor on which an elevator taking demand call does not occur and is not in a hot spot and on which an elevator taking demand is expected.
According to a preferred embodiment, the server dynamically divides all floors into three high, medium and low gradients, each gradient comprising at least one type of demand floor.
According to a preferred embodiment, the server is configured to invoke the regulation rules in the following manner: counting the floor numbers of first to third demand floors in the three high, medium and low gradients, and counting the elevator waiting number of the first demand floor in the three high, medium and low gradients; and if the floor number of the first type of demand floor in the three high, medium and low gradients exceeds the threshold values of the first to third floor numbers respectively, or the elevator waiting number of the first type of demand floor in the three high, medium and low gradients exceeds the threshold values of the first to third elevator waiting numbers respectively, calling a first regulation and control rule constructed according to the first and second information to regulate and control the operation strategy of each elevator respectively.
According to a preferred embodiment, the server is configured to invoke a first regulation rule constructed by a neural network in deep reinforcement learning according to the first and second information to regulate the operation strategy of each elevator respectively.
The application also provides an intelligent building control method, which comprises the following steps: acquiring and updating first information about the personnel flow condition of each floor through first acquisition equipment distributed on each floor in a building; acquiring and updating second information about the use condition of each elevator through second acquisition equipment distributed in each elevator; processing and obtaining third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transporting data obtained by connecting with a building management platform; under the condition that all elevators are put into operation, all floors are dynamically divided to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and combined with third and fourth information; and calling at least one pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulating and controlling the operation strategy of each elevator based on the first and second information and combining the regulation and control rule to dynamically respond to the elevator taking demand calls of different floors.
The application also provides an intelligent building control method, which comprises the following steps: acquiring and updating first information about the personnel flow condition of each floor through first acquisition equipment distributed on each floor in a building; acquiring and updating second information about the use condition of each elevator through second acquisition equipment distributed in each elevator; judging the current elevator waiting demand and the predicted elevator waiting demand in each floor through intelligent visual recognition; generating first information about the flow condition of people on each floor at least based on dynamic travel distance data between at least one predicted elevator waiting person corresponding to the predicted elevator waiting requirement and an elevator waiting area, actively transmitting and updating the first information to a server when the first information meets a trigger condition, and receiving an operation strategy of each elevator responding to elevator taking requirement calls of different floors, wherein the operation strategy is obtained by the server at least based on the first information and the second information; and generating at least one intelligent mobile terminal which is used for being pushed to the floor where the first acquisition equipment is located and is actively connected with the first acquisition equipment in a wireless manner by setting a connection mode, wherein the floor is operated by the elevator taking personnel based on the second information acquired in real time and the operation strategy.
According to a preferred embodiment, all floors are dynamically divided according to the following steps: dynamically dividing at least one floor into at least one type of demand floor based on the elevator taking demand call and the fourth information received by the at least one floor; performing distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on distribution statistical results to obtain a distribution form; all floors are dynamically divided into at least two gradients based on at least the determined profile and the third information.
Drawings
Fig. 1 is a schematic diagram of a simplified module connection relationship of an intelligent control system for a building according to the present invention.
List of reference numerals
1: the first collecting device 2: the second collecting apparatus 3: server
4: the intelligent mobile terminal 5: elevator operation control unit 6: building management platform
Detailed Description
The following detailed description is made with reference to the accompanying drawings.
The system adopts a plurality of acquisition devices distributed in each floor and in each elevator, and captures different elevator waiting characteristics of each floor under the current elevator quantity and the current building floor number by utilizing historical elevator conveying data acquired by the acquisition devices so as to enable elevator scheduling to better meet the use requirement under the proportion of the current elevator quantity and the building floor number. Meanwhile, the control system provided by the application does not rely on the call occurrence probability distribution of different floors singly any more, but combines the elevator waiting characteristics and the real-time information acquired by the acquisition equipment to divide the floors under the same elevator waiting characteristics into the same demand gradient, particularly distinguishes the low floors which cannot meet the elevator riding demands by adopting the existing elevator control scheme, so that the operation strategy of each elevator can be controlled more specifically, the elevator is allocated reasonably, the problem that the passenger carrying capacity of the elevator is digested by the higher floors in the peak period to cause the high elevator waiting time of the low floors is solved, and the use experience of elevator personnel in the building is improved while the operation efficiency of the elevator is guaranteed. In addition, the control system provided by the application combines the elevator taking demand call with the multi-floor in the building by means of intelligent visual identification, so that the multi-floor in the building is divided into three types of demand floors to better and accurately reflect all expectable elevator taking demands including the elevator taking demand call, and the corresponding elevator waiting times under different expectable elevator taking demands are different.
The system mainly comprises at least one of a first acquisition device 1, a second acquisition device 2, a server 2 and an intelligent mobile terminal 4 operated by elevator personnel.
The first collecting devices 1 are distributed in each floor of the building and used for acquiring and updating first information about the personnel flow condition of each floor. Aiming at a waiting area where an elevator door is located and a plurality of floor roadways communicated to the waiting area, the first acquisition equipment 1 comprises at least one first camera arranged in the waiting area and at least one second camera arranged in the floor roadways. The first information comprises the information of the elevator waiting personnel who send the call for taking the elevator in the elevator waiting area and collected by the first camera, and the information of the expected elevator waiting personnel who do not arrive at the elevator waiting area and collected by the second camera. The elevator waiting personnel information comprises the number of elevator waiting personnel, the required capacity of taking the elevator corresponding to the number of elevator waiting personnel and the like. The expected ladder waiting personnel information comprises one or more of expected ladder waiting number, expected travelling distance between the expected ladder waiting personnel and the ladder waiting area, the time required for the expected ladder waiting personnel to arrive at the ladder waiting area, the expected ladder waiting number respectively corresponding to different preset grading time, and the like. Based on the preset grading time and the calculated time required for the expected elevator waiting personnel to arrive at the elevator waiting area, the expected elevator waiting number corresponding to different preset grading time can be obtained. The first information is mainly used for indicating the elevator taking demand capacity corresponding to the elevator taking demand call and the elevator taking demand capacity not corresponding to the elevator taking demand call.
At present, there is a technical solution for acquiring the number of people waiting for an elevator by using a visual identification manner in related researches, which at least has the following problems: however, the number of people waiting for the elevator is obtained only unilaterally under the technical scheme, for elevator waiting personnel, the elevator waiting personnel do not know which elevator stops before the elevator arrives, and a plurality of elevator waiting personnel can only dispersedly and randomly stand in an elevator waiting area. Therefore, the control system provided by the application adopts the first acquisition equipment 1 which is different from the existing visual identification equipment, the first acquisition equipment 1 is not only singly arranged in the elevator waiting area for acquiring the number of people waiting for the elevator, the visual identification area of a floor roadway is also added in the control system, the first acquisition equipment 1 respectively carries out visual identification on the two areas and combines the identification results, and the actual elevator taking requirement can be more accurately reflected.
The technical solution of using visual identification to obtain the number of people waiting for the elevator in the related research at present has the following problems: when people wait for the elevator, the people usually consult the mobile phone to wait for the elevator, the people usually pay too much attention to the mobile phone and ignore the photoelectric notification, and the people miss the elevator and need to wait for the next elevator, so that the elevator waiting time of the people waiting for the elevator is prolonged, and unnecessary transportation load is also increased. In contrast, the first acquisition device 1 used in the present application, which is different from the existing visual recognition device, can allow the intelligent mobile terminal 4 operated by the elevator-taking person to be wirelessly connected therewith, and actively push the elevator-coming information responded based on the elevator-taking demand call to the intelligent mobile terminal 4, thereby greatly avoiding the problem that some elevator waiting persons miss the elevator without being concerned with the photoelectric notification.
The elevator waiting personnel only know the position of the stopped elevator temporarily when the elevator stops at the floor and sends the photoelectric notification, and a plurality of elevator waiting personnel move towards the stopped elevator, so that the moving process actually prolongs the elevator waiting time of other floor personnel. Therefore, the first acquisition device 1 which is different from the existing visual recognition device and used in the system actively pushes the coming elevator information responded by calling the taking elevator to the intelligent mobile terminal 4, the coming elevator information not only indicates the coming elevator position but also reflects the remaining capacity in the coming elevator, and the elevator waiting personnel can actively judge the elevator waiting position based on the coming elevator information and the distribution situation of the elevator waiting personnel on the floor, especially the elevator waiting personnel can observe the personnel distribution and actively select the elevator waiting position under the situation of coming two elevators, so that the elevator waiting personnel can actively finish the reasonable dispersion of the elevator waiting without external guidance.
According to part of technical schemes, a method that a plurality of intelligent mobile terminals 4 operated by each elevator taking person request resource data to a server 2 to learn the running conditions of a plurality of elevators in advance is adopted, however, under the arrangement, as the plurality of intelligent mobile terminals 4 request resources to the server 2, the data traffic of the server 2 with large data processing capacity is overlarge, and even if the running conditions of the plurality of elevators are learned in advance, the problem of elevator conveying capacity cannot be effectively solved, the elevator waiting dysphoria psychology of the elevator taking person is easily enhanced. To this end, the control system provided in the present application adopts a method in which the intelligent mobile terminals 4 on different layers are respectively connected with the first acquisition devices 1 on the layer where the intelligent mobile terminals are located, thereby avoiding a situation that the data traffic of the server 2 is too large due to the requirement that the intelligent mobile terminals 4 request resources from the server 2 in the prior art, that is, the first acquisition devices 1 replace the server 2 to bear the resource request of the intelligent mobile terminals 4 in the present application.
In order to achieve the above object, the first collection device 1 in the present application is configured to generate, based on the second information acquired in real time and the operation policy, incoming call information for pushing to at least one smart mobile terminal 4 located on a floor where the first collection device 1 is located. The intelligent mobile terminal 4 is actively in wireless connection with the first acquisition device 1 in a set connection mode, so that mutual information interaction can be carried out. The connection setting method mentioned here may refer to long-distance wireless transmission technology or short-distance wireless transmission technology such as WiFi, NB-IOT, lora, zigbee, bluetooth, etc. For example, the smart mobile terminal 4 is connected with the first acquisition device 1 by scanning a two-dimensional code, and the two-dimensional code can be displayed by a vertical display screen device arranged in a waiting area of each floor.
The operation strategy is determined by the server 2 based on at least the first and second information processing, and each elevator responds to the elevator taking demand call of different floors.
The first information is obtained by processing the flow condition of the people on each floor, which is generated by the first acquisition equipment 1 at least based on the dynamic travel distance data between at least one predicted elevator waiting person corresponding to the predicted elevator waiting demand and the elevator waiting area.
And judging the current elevator waiting demand and the predicted elevator waiting demand in each floor through intelligent visual recognition. The current elevator waiting demand can refer to the number of elevator waiting persons in an elevator waiting area when an elevator taking demand call is sent in the elevator waiting area, and/or the number of elevator waiting persons in a first part which is not the elevator waiting area but meets the expected elevator waiting condition is predicted. The predicted ladder waiting demand can be the predicted number of people waiting for the second elevator part which does not meet the expected ladder waiting condition in the non-ladder waiting area. The sum of the predicted elevator waiting numbers of the first part and the second part is the predicted elevator waiting number which is visually recognized by the second acquisition equipment 2 and does not reach the elevator waiting area. The expected ladder waiting condition can be whether the time required for waiting ladder personnel to reach the ladder waiting area meets a preset ladder waiting distance threshold value or not.
When the first information processed by the first acquisition device 1 meets the trigger condition, the first acquisition device 1 actively transmits and updates the first information processed in real time to the server 2. The triggering condition mentioned here may refer to that the current elevator waiting demand exceeds a first preset threshold corresponding to the current elevator waiting demand or the predicted elevator waiting demand exceeds a second preset threshold corresponding to the predicted elevator waiting demand. The first and second preset thresholds referred to herein may be preset parameter values. The first and second preset thresholds may also be determined by the server 2 updating to the first collection device 1 in real time.
When at least one elevator is not put into operation, the data processing amount is small, and the first acquisition equipment 1 can actively update the first information to the server 2 according to a preset period instead of being determined by a trigger condition. When all elevators are put into operation, the server 2 updates the parameter values with smaller values to the first acquisition equipment 1 as the first and second preset threshold values, so that the first acquisition equipment 1 actively transmits and updates the first information obtained at present to the server 2 for the first time. The server 2 analyzes and processes the acquired information to obtain a new parameter value, and feeds the new parameter value back to the first acquisition device 1 in real time to update the first and second preset thresholds. The server 2 may process the parameter value based on the total remaining elevator riding capacity of at least one elevator staying at the floor at the next time point.
The server 2 is connected with the building management platform 6 to obtain historical elevator transportation data, and the server 2 processes the historical elevator transportation data to obtain third information about elevator conditions for each floor and fourth information about elevator demands for each floor.
The historical elevator delivery data includes the daily total elevator waiting time of each floor according to the ratio of the current floor number to the current elevator number. The total elevator waiting time length can be the sum of the elevator waiting time lengths of the elevator passengers in each floor in the peak period by statistics. It should be noted that, in the non-down peak period, that is, in the case that at least one elevator is not operating, the elevator-taking requirements of different floors can be better met, and in the down peak period, better scheduling cannot be achieved, so that the elevator-taking requirements are difficult to solve.
The elevator taking requirements of the upper floor are preferentially met in a common elevator regulation mode, so that the elevator taking requirements of the higher floor can be timely and sufficiently met, the lower floor always faces longer elevator taking time and insufficient elevator taking space, and obvious elevator taking difference exists in the high, medium and low floors. In contrast, in the application, in order to better and accurately divide high, medium and low floors with obvious elevator riding differences, and considering that the ratio of the number of floors to the number of elevators in different buildings is different, the application captures and processes data from historical elevator conveying data closely related to the buildings, and can obtain a technical scheme which is personalized and can better adapt to the requirements of different buildings. Specifically, according to the distribution statistical result of the total elevator waiting time lengths respectively corresponding to different floors in the peak period, the third information about the elevator using condition of each floor in the ratio of the number of the floors to the number of the elevators can be obtained. The third information is the division result of the high, medium and low floors matched with the current building. The third information can accurately indicate the number range of the first boundary floor between the high and middle floors and the number range of the second boundary floor between the low and middle floors.
The historical elevator transportation data includes the occurrence time t1 of each floor call every day and the load variation Δ w corresponding to each elevator. The server 2 determines a hot spot time period t2 of each day call according to the occurrence time t1 and the load variation quantity delta w. The hot spot time t2 is mainly a time period in which the number of elevator taking demand calls occurring in the time period is large and the integrated value of the load variation Δ w is also high, and is fourth information about elevator demands for each floor.
For example, 24 hours a day is divided into N time periods, each time period has a width δ =24/N, if a total of N calls occur in the ith time period on one floor f, the load variation of all calls is accumulated as W f,i Then the i time period heat is CH i ＝n×W f,i On the floor, the time period corresponding to the highest CH value is a hot spot period t2. The top few CHi values may also be taken as the hot spot period t2.
The server 2 determines the slope k and the vertex height H of the hotspot time t2 according to the number of calls and the call time in the hotspot time t2.
Slope k = l/. DELTA.t of daily hotspot period t2, vertex height H = k × δ, wherein: and delta t is the time interval of the first call and the last call in the hot spot time period, and l is the total number of calls in the hot spot time period.
The hot spot period t2 is a decay period of a certain number of days, typically three days, and each decay period falls by 10% of the height of the highest vertex if no new call occurs within the decay period. That is, the time interval selected as a floor hot spot time interval is continuously without calling for several days in the time interval of the floor, so that the peak height is adjusted by 10% downward, the original peak height is H, and the peak height is adjusted to 0.9H.
If the elevator is not used for a long time (e.g. more than a month), the hot spot periods and the slopes, vertices are all recalculated when reused.
The first activation threshold is a fixed value and is taken as an average multiple. The second activation threshold is also a fixed value, an average multiple is taken, and the first activation threshold is more than or equal to the second activation threshold. The server 2 performs normalization processing on all hotspot time periods t2.
And under the condition that all elevators are monitored to be put into operation, the server 2 dynamically divides all floors to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and by combining the third information and the fourth information.
The server 2 dynamically divides at least one floor into at least one type of demand floor based on the landing demand call and the third and fourth information (or hot spot periods) received by the at least one floor.
The at least one type of demand floor may be one of a first type of demand floor on which an elevator taking demand call occurs, at least one second type of demand floor on which an elevator taking demand call does not occur but is in a hot spot and there is an expected elevator taking demand, and a third type of demand floor on which an elevator taking demand call does not occur and is not in a hot spot but there is an expected elevator taking demand.
If there is an expected elevator riding demand, the server 2 processes the information based on the third information. And considering that the expected elevator taking demand exists under the condition that the first part of the predicted elevator waiting number in the third information is not zero.
The second type of demand floor is used for indicating that although no people call the elevator at the floor, part of people in the corridor of the floor move towards the elevator taking area, and the current time interval is a hot spot time interval with high probability of more people taking the elevator, namely the elevator taking demand increment corresponding to the floor at the next moment is large. The third type of demand floor is used for indicating that although no people call the elevator at the floor, the current time interval is not the hot spot time interval corresponding to the floor, but part of people in the corridor of the floor move towards the elevator taking area, namely, the elevator taking demand increment corresponding to the next time of the floor is smaller.
And carrying out distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on a distribution statistical result to obtain a distribution form. The distribution form at least comprises different distribution form data respectively corresponding to the three types of demand floors. The distribution form can be the number of people and the floor according to the horizontal and vertical coordinates. The distribution of the elevator taking calls at the current moment and the distribution of the number of people corresponding to the elevator taking calls can be clearly reflected under the distribution form data of the first-class demand floors. The expected distribution of elevator riding calls with expected large demand variation in the next moment and the expected distribution of the number of people corresponding to the elevator riding calls can be clearly reflected under the distribution form data of the second type of demand floors. The expected distribution of elevator taking calls with less expected change of demand in the next moment and the expected distribution of the number of people corresponding to the elevator taking calls can be clearly reflected under the distribution form data of the third type of demand floors.
Based on the first and second boundary floor numbering ranges determined in the third information, the local distribution form can be obtained by corresponding floors in the first and second boundary floor numbering ranges to the distribution form corresponding to the first type of demand floors obtained through real-time distribution statistics. If the local distribution form has a form inflection point, the upper end or the lower end of the form inflection point is used as a specific boundary floor. For example, based on the first boundary floor number range, floors i to j (i > j) can be specified, and if there are more floors close to floor i where no call is made than there are few floors close to floor j where no call is made, the floor where the maximum change value occurs in the distribution density statistical data for floors i to j of no call floor is used as the specific boundary floor for defining the high-medium gradient. The same process can result in specific boundary floors for the division of medium to low gradients. Based on this, the server 2 dynamically divides all floors into three high, medium and low gradients, each gradient may contain at least one type of demand floor.
The server 2 can obtain a pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulate and control the operation strategies of the elevators based on the first and second information and in combination with the regulation and control rule so as to dynamically respond to the elevator taking demand calls of different floors. The dynamic response means that the server 2 confirms the regulation and control rule in real time based on the updated information under the condition that at least one of the first information, the second information, the third information and the fourth information is updated in real time, so that the elevator taking demand calling of different floors is dynamically responded.
The server 2 counts the floor numbers of first to third demand floors in the three high, medium and low gradients, and counts the elevator waiting number of the first demand floor in the three high, medium and low gradients.
And if the total elevator waiting number of the first type of demand floors in the low gradient is lower than a first person number threshold value, or the elevator waiting numbers respectively corresponding to all the first type of demand floors in the low gradient are lower than a second person number threshold value, calling a first regulation and control rule established by a neural network in deep reinforcement learning according to the first information and the second information to respectively regulate and control the operation strategy of each elevator.
Preferably, the basic process of reinforcement learning is a Markov decision process. The Markov decision process may form a quadruple representation { s, a, p, r } with state s, action a, state transition probability p, state transition reward or reward r. For the discrete-time markov decision process, the set of states and actions is referred to as the state space S and the action space a. Is specifically represented as state s i ∈S，a i E.g. A. According to the action selected in step t, the state is according to the probability P(s) t+1 ，s t ，a t ) From s t Is transferred to s t+1 . At the same time of state transition, the decision-making body gets 1 instant reward R(s) t+1 ，s t ，a t ). S in the above expression t Shown as the state at time t. a is t Shown as the action at time t. The accumulated rewards at the end of the above process are:
G t ＝R t +γR t+1 +γ 2 R t+2 +…+γ k R t+k ＝∑ k＝0 γ k R t+k
r in the formula (1) t Is the accumulated prize in time t. Gamma is a discount factor, and the value range is between 0 and 1. The discount factor is used to reduce the reward weight corresponding to the forward decision. The ultimate goal of the decision is to achieve maximization of the jackpot while reaching the goal state. Parameter S in the state space S t Can be constructed by the floor number of the elevator calling, the elevator operation parameters and the like. Parameter a in motion space A t Can be the dispatch of the elevator by the server and the control related actions such as the number of stops of the elevator, the running speed of the elevator, etc. Preferably, the cost function can be evaluated by constraints. The optimization target in the algorithm for constructing the deep reinforcement learning is as follows: the waiting time of the floor where the elevator taking demand call occurs is minimum and is distributed to all the electricity where the elevator taking demand call occursThe total residual capacity of the elevator is not less than the elevator taking demand of the stopped floor. The constraint conditions are as follows: the elevator operation efficiency is not lower than a preset threshold value, and at least two elevators are allocated to stop to the floor when the elevator taking demand of the floor where the elevator taking demand call occurs exceeds the residual capacity of a single elevator. The policy variables are: the number of stops of the elevator in high, medium and low gradients and the remaining elevator capacity. Preferably, the reinforcement learning update strategy is based on a cost function.
Preferably, in the deep reinforcement learning/reinforcement learning, the update function is as follows:
Q(s t+1 ，a t+1 )＝Q o (s t ，a t )+loss
q(s) in the formula (2) t+1 ，a t+1 ) Is the value of the updated cost function. Q o (s t ，a t ) Previous value in previous state. The previous value is the value stored in the value table. loss is a loss function.
loss＝α[Q r (S t+1 ，a t+1 )-Q o (S t ，a t )]
Q in formula (3) r (s t+1 ，a t+1 ) Is a practical value. α is the learning rate. Alpha is between O and 1. Alpha determines the rate of value table updates.
At present, there is a technical scheme for acquiring the number of people waiting for an elevator by adopting a visual identification mode in related researches, and the following problems still exist: when a call is made on a certain floor, an elevator nearest to the floor is often allocated to the floor, and the rest of elevators do not stop to the floor, the actual passenger capacity in the elevator is not considered under the arrangement, so that the people on the floor cannot be delivered under the condition that the elevator people are fully loaded, and the elevator waiting people on the floor are not considered, so that the rest of elevators with the residual load capacity are already descended under the condition that the elevator waiting people exceed the residual load capacity of the elevator, thereby greatly influencing the transportation capacity, further prolonging the elevator waiting time of the elevator waiting people who do not take the elevator, and seriously influencing the use experience of the elevator.
Therefore, the control system provided by the application not only further provides a regulation and control strategy which is favorable for solving the problems on the basis of the scheme, and not only can the problem that the elevator waiting influence is aggravated due to the fact that the elevator without enough capacity is allocated in the prior art be avoided by considering the residual load capacity of the elevator in different gradients and the elevator taking demand of different floors in real time, but also the lifting and transporting capacity is favorably improved, and the elevator waiting time of elevator waiting personnel is shortened to the greatest extent so that the elevator using experience is improved.
And if the total elevator waiting number of the first-class demand floors in the low gradient is not less than a first person number threshold, or the elevator waiting number corresponding to at least one first-class demand floor in the low gradient is not less than a second person number threshold, calling a second regulation and control rule established by a neural network in deep reinforcement learning according to the first and second information to respectively regulate and control the operation strategy of each elevator. The second regulation and control rule is basically the same as the first regulation and control rule, the difference is that an optimization target in the deep reinforcement learning algorithm is constructed, and the optimization target corresponding to the second regulation and control rule can be: the total remaining capacity allocated to all elevators with elevator taking demand calls is not less than the elevator taking demand of the stopped floors, and the elevator waiting time of the first type of demand floors in the low gradient does not exceed the preset elevator waiting time. The constraint conditions are as follows: the elevator operation efficiency is not lower than a preset threshold value, and at least two elevators are allocated to stop to the floor when the elevator taking demand of the floor where the elevator taking demand calling exceeds the residual capacity of a single elevator.
According to a preferred embodiment, for the elevators located in the high gradient area, if the sum of the elevator in the high gradient and the elevator going upwards is less than the floor number of the elevator having the elevator taking demand call in the high gradient, and if the floor number of the elevator in the medium gradient, which is the first type of demand floor, exceeds the second floor number threshold value or the floor number of the elevator in the third type of demand floor, exceeds the fourth floor number threshold value, the elevator located in the high gradient is regulated to be in accelerated downwards movement. Conversely, the elevator in the high gradient is controlled to slow down. When the elevator taking demand of the floor in which the elevator taking demand call occurs in the middle gradient exceeds the residual capacity of the single elevator closest to the floor, at least two elevators are allocated to stop to the floor at the same time or in a way that the stop time difference does not exceed the preset stop time difference threshold value.
According to a preferred embodiment, for the elevators located in the middle gradient area, if the sum of the elevators in the high and middle gradients is less than the number of floors in the middle gradient where the elevator taking demand call has occurred, the elevator located in the middle gradient area is controlled to accelerate the downward movement if the number of floors of the first type of demand floors exceeds the third number threshold or the number of floors of the third type of demand floors exceeds the fifth number threshold. Otherwise, the elevator in the middle gradient is controlled to slow down. When the elevator taking demand of the floor where the elevator taking demand call occurs in the low gradient exceeds the residual capacity of the single elevator closest to the floor, at least two elevators are allocated to stop to the floor at the same time.
Preferably, the fast speed V of the elevator in the accelerating operation can be preset up ＝V*H n /H e In which H is e V is the peak height average and is the elevator rated speed. The slow speed of the elevator for slowing down is V which is the rated running speed dn ＝V*H e /H n . Average value mentioned here if the height of the vertex of the hot spot period of a certain floor f is H f A total of M floors, then the average value E (H) is calculated as:
it should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and figures are illustrative only and are not intended to be limiting on the claims. The scope of the invention is defined by the claims and their equivalents. The present description contains several inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", each indicating that the respective paragraph discloses a separate concept, the applicant reserves the right to submit divisional applications according to each inventive concept.
Claims (9)
1. An intelligent building control system, comprising:
the first acquisition equipment (1) is distributed on each floor in the building and is used for acquiring and updating first information about the personnel flow condition of each floor;
the second acquisition equipment (2) is distributed in each elevator and is used for acquiring and updating second information about the service condition of each elevator; and
a server (3) configured to:
processing third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transportation data acquired by being connected with a building management platform (6);
under the condition that all elevators are put into operation, all floors are dynamically divided to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and combined with third and fourth information;
and calling at least one pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulating and controlling the operation strategy of each elevator based on the first and second information and combining the regulation and control rule to dynamically respond to the elevator taking demand calls of different floors.
2. An intelligent building control system, comprising:
the first acquisition equipment (1) is distributed on each floor in the building and is used for acquiring and updating first information about the personnel flow condition of each floor;
the second acquisition equipment (2) is distributed in each elevator and is used for acquiring and updating second information about the service condition of each elevator; and
a server (3), wherein the first acquisition device (1) is configured to:
judging the current elevator waiting demand and the predicted elevator waiting demand in each floor through intelligent visual recognition;
generating first information about the flow condition of people on each floor at least based on dynamic travel distance data between at least one predicted elevator waiting person corresponding to the predicted elevator waiting requirement and an elevator waiting area, actively transmitting and updating the first information to a server (3) when the first information meets a trigger condition, and receiving an operation strategy of each elevator responding to elevator taking requirement calls of different floors, which is obtained by the server (3) at least based on first and second information processing;
generating incoming call information based on the second information acquired in real time and the operation strategy,
the elevator coming information is used for being pushed to at least one intelligent mobile terminal (4) which is positioned on the floor where the first acquisition equipment (1) is positioned and is operated by elevator taking personnel and is in wireless connection with the first acquisition equipment (1) actively in a set connection mode,
the server (3) is configured to dynamically partition all floors in the following manner:
processing third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transportation data acquired by being connected with a building management platform (6);
dynamically dividing at least one floor into at least one type of demand floor based on the elevator taking demand call and the third and fourth information received by the at least one floor;
performing distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on distribution statistical results to obtain a distribution form;
all floors are dynamically divided into at least two gradients based on at least the determined profile and the third information.
3. The intelligent building control system of claim 2, wherein the at least one type of demand floor is one of a first type of demand floor on which an elevator boarding demand call occurs, a second type of demand floor on which an elevator boarding demand call does not occur but is in a hot spot and there is an expected elevator boarding demand, and a third type of demand floor on which an elevator boarding demand call does not occur and is not in a hot spot and there is an expected elevator boarding demand.
4. The building intelligent control system according to any one of claims 2-3, characterized in that the server (3) dynamically divides all floors into three high, medium and low gradients, each gradient comprising at least one type of demand floor.
5. Intelligent building control system according to claim 4, characterized in that the server (3) is configured to invoke regulatory rules in the following way:
counting the floor numbers of first to third demand floors in the three high, medium and low gradients, and counting the elevator waiting number of the first demand floor in the three high, medium and low gradients;
and if the floor number of the first type of demand floor in the three high, medium and low gradients exceeds the threshold values of the first to third floor numbers respectively, or the elevator waiting number of the first type of demand floor in the three high, medium and low gradients exceeds the threshold values of the first to third elevator waiting numbers respectively, calling a first regulation and control rule constructed according to the first and second information to regulate and control the operation strategy of each elevator respectively.
6. Intelligent building control system according to claim 5, characterized in that the server (3) is configured to invoke a first regulation rule constructed using a neural network in deep reinforcement learning from the first and second information to regulate the operation strategy of each elevator separately.
7. An intelligent building control method, comprising:
acquiring and updating first information about the personnel flow condition of each floor through first acquisition equipment (1) distributed on each floor in a building;
second information about the use condition of each elevator is obtained and updated through second acquisition equipment (2) distributed in each elevator;
processing third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transportation data acquired by being connected with a building management platform (6);
under the condition that all elevators are put into operation, all floors are dynamically divided to obtain at least one demand gradient based on elevator taking demand calls received by at least one floor and combined with third and fourth information;
and calling at least one pre-stored regulation and control rule corresponding to the current demand gradient distribution, and respectively regulating and controlling the operation strategy of each elevator based on the first and second information and combining the regulation and control rule to dynamically respond to the elevator taking demand calls of different floors.
8. An intelligent building control method, comprising:
acquiring and updating first information about the personnel flow condition of each floor through first acquisition equipment (1) distributed on each floor in a building;
second information about the use condition of each elevator is obtained and updated through second acquisition equipment (2) distributed in each elevator;
judging and obtaining the current elevator waiting demand and the predicted elevator waiting demand in each floor through intelligent visual recognition;
generating first information about the flow condition of people on each floor at least based on dynamic travel distance data between at least one predicted elevator waiting person corresponding to the predicted elevator waiting requirement and an elevator waiting area, actively transmitting and updating the first information to a server (3) when the first information meets a trigger condition, and receiving an operation strategy of each elevator responding to elevator taking requirement calls of different floors, which is obtained by the server (3) at least based on first and second information processing;
generating incoming call information based on the second information acquired in real time and the operation strategy,
the elevator coming information is used for being pushed to at least one intelligent mobile terminal (4) which is positioned on the floor where the first acquisition equipment (1) is positioned and is operated by elevator taking personnel and is in wireless connection with the first acquisition equipment (1) actively in a set connection mode,
the server (3) is configured to dynamically partition all floors in the following manner:
processing third information about elevator using conditions of each floor and fourth information about elevator using requirements of each floor at least based on historical elevator transportation data acquired by being connected with a building management platform (6);
dynamically dividing at least one floor into at least one type of required floor based on the elevator taking demand call and the third and fourth information received by the at least one floor;
performing distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on distribution statistical results to obtain a distribution form;
all floors are dynamically divided into at least two gradients based on at least the determined profile and the third information.
9. The intelligent building control method according to claim 7, wherein all floors are dynamically divided according to the following steps:
dynamically dividing at least one floor into at least one type of required floor based on the elevator taking demand call and the third and fourth information received by the at least one floor;
performing distribution statistics on at least two types of demand floors in all floors, and dynamically matching in a preset distribution form based on distribution statistical results to obtain a distribution form;
all floors are dynamically divided into at least two gradients based on at least the determined profile and the third information.
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