CN117858479A - Method for updating weight relation of air conditioner on environmental temperature in real time - Google Patents
Method for updating weight relation of air conditioner on environmental temperature in real time Download PDFInfo
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Abstract
The invention discloses a method for updating the weight relation of an air conditioner on the influence of environmental temperature in real time, which comprises the steps of monitoring and collecting the history regulation strategy of the air conditioner in real time, and screening an effective target strategy window by combining a dead zone of an air conditioner compressor in a sliding window mode; based on the effective target strategy windows, analyzing the change conditions of the temperature sensing temperature and the air conditioner return air temperature after the middle strategy in each effective target strategy window is executed, and combining the historical weight of the air conditioner executing the middle strategy on the influence of the environment temperature, so as to further accurately adjust the weight calculation; utilizing the generated history binding relation record to give out factors such as frequency of binding temperature feeling and the like to correct the binding relation of the air conditioner and the temperature feeling; and introducing binding relation priority, combining temperature sense, the number of air conditioners and standby air conditioners, and finally generating a stable binding relation between the air conditioners and the temperature sense so as to achieve automatic updating and automatic strengthening and improve the safety and stability of energy-saving control.
Description
Technical Field
The invention relates to the technical field of energy-saving control of a data center machine room, in particular to a method for updating a weight relation of an air conditioner on environmental temperature in real time.
Background
Under the current technical conditions, in order to ensure the data safety and equipment safety in the operation process of the data center, a plurality of temperature sensors are often arranged at different point positions of the data center, and analysis and prediction are carried out by monitoring and collecting temperature-sensing real-time data, so that a set of feasible air conditioner tail end adjusting and controlling scheme is finally provided, and the purposes of safety or energy conservation are achieved. In the process, when the temperature sensor data guides the environmental temperature to be reduced or increased, the temperature adjusting efficiency of which air conditioner or air conditioners is the highest, and the air conditioner is practically safe and energy-saving, which is a core problem of the whole energy-saving adjusting and controlling scheme. Namely, only if the binding relation between the air conditioner and the temperature sensing is accurately matched, the effective vector releasing can be realized, and the energy is saved efficiently.
The existing data center applying the energy-saving control scheme is basically directly subjected to relation binding according to the distance between an air conditioner and temperature sensing through expert experience, or subjected to relation binding through the technical means of air conditioner pre-regulation before the energy-saving control scheme is executed. In the following energy-saving regulation scheme, the binding relation between the air conditioner and the temperature sense is kept unchanged, or a great amount of manpower and cost are input to extract and secondarily analyze the acquired data when the energy-saving effect is poor, so that the binding relation is manually modified. In practice, the binding relationship between the air conditioner and the temperature sensing is not constant, for example, the working condition of a data center machine room is greatly changed, the temperature sensing and the position of the air conditioner are changed, or part of the air conditioner is failed to be in an unregulated state, if the binding relationship is not updated and regulated, great deviation is brought to a service side, and even the production safety is threatened. Second, as data centers applying energy-efficient control schemes grow more and more, the manner in which binding relationships are adjusted by means of human analysis becomes impractical.
Disclosure of Invention
In order to solve the problems, the invention provides a weight relation real-time updating method for the influence of an air conditioner on the environmental temperature, which is used for adjusting the binding relation between the air conditioner and the temperature in real time, by considering the possible influence of the actual production working condition and other objective external conditions on the safety and energy conservation of a data center.
In order to achieve the above object, the present invention is realized by the following technical scheme:
the invention relates to a method for updating the weight relation of air conditioner to the environmental temperature in real time, which comprises the following operations:
s1, acquiring relevant configuration parameters of machine room equipment and an energy-saving regulation algorithm, wherein the relevant configuration parameters comprise standby air conditioner information of each air conditioner, whether the air conditioner can regulate and control information, temperature sensing temperature in the previous 24 hours and historical time sequence data of air conditioner return air temperature;
s2, acquiring an initial weight table of the air conditioner on the temperature sensation, an initial binding relation list of the air conditioner and the temperature sensation and a temperature propagation hysteresis matrix based on the pre-regulated air conditioner and temperature sensation weight relation;
s3, according to the principle that each temperature sensing is at least bound with one air conditioner and the air conditioner which cannot be regulated does not carry out temperature sensing binding, reallocating the binding relationship between the air conditioner and the temperature sensing, namely reallocating the binding relationship according to whether the air conditioner of the current machine room can regulate and control information;
s4, acquiring all history regulation policies issued and executed in the past two hours of a machine room, wherein 3 adjacent history regulation policies form a policy window, traversing the whole history regulation policy list in a sliding window mode, screening out a policy window which only has the influence of an air conditioner executing the middle policy on the environmental temperature change from the period from the execution of the middle policy to the execution of the next history regulation policy by combining an air conditioner compressor dead zone based on the middle policy of the policy window, and screening out the obtained policy window as an effective target policy window;
s5, calculating and updating the weight of the air conditioner executing the intermediate strategy on the temperature sense based on the effective target strategy windows which meet the conditions and are screened in the S4, and updating the binding relation corresponding to the air conditioner executing the intermediate strategy in each effective target strategy window to independently generate an updated binding relation;
and S6, after each binding relation with a set number is generated, integrating records of historical binding relations of each air conditioner, and further optimizing the updated binding relation to obtain a stable binding relation.
The invention further improves an air conditioner that: s3, the specific operation comprises the following steps:
s3-1, calculating the average binding number of air conditioners and temperature senses according to the number of the temperature senses of the current machine room and the number of the adjustable air conditioners, and rounding downwards, wherein the expression is as follows:
；
wherein,the number obtained by rounding down the average binding number of air conditioner and temperature sensing is +.>，Representing a positive integer set.
S3-2, traversing each air conditioner in sequence according to an initial weight table of the air conditioner on the temperature sense, arranging the temperature senses corresponding to each air conditioner in reverse order according to weight magnitudes, and selecting the front part with weight magnitude of 0.8 or moreBinding the individual temperature sensations with the corresponding air conditioner;
s3-3, selecting an air conditioner with the largest weight for each temperature sense, and binding the temperature sense with the corresponding air conditioner if one of the following conditions is met:
condition 1: the temperature sensation is not yet in the initial binding relation list of all air conditioners and the temperature sensation;
condition 2: the initial binding relation list of the air conditioner corresponding to the air conditioner with the largest weight and the temperature sense obtained by the S3-2 is currently empty.
The invention further improves that: the valid target policy window in S4 meets the following conditions at the same time:
condition 1: the time interval between the execution of adjacent history regulation strategies is more than or equal to 30 min;
condition 2: after the first 2 historical regulation strategies are executed, the set value of the return air temperature minus the temperature of other air conditioners in the machine room except for the air conditioner executing the intermediate strategy is smaller than or equal to the dead zone of the compressor of the machine room, namely, the condition that the other air conditioners are not started automatically is not caused.
The invention further improves that: s5, the specific operation comprises the following steps:
s5-1, for a single temperature sensor, acquiring the return air lag time of the air conditioner to the temperature sensor based on a temperature propagation lag matrix;
s5-2, acquiring temperature sensing time sequence data within 10 minutes before the air conditioner executes the regulation strategy and temperature sensing time sequence data within 30 minutes after the air conditioner executes the regulation strategy for single temperature sensing;
s5-3, judging whether the temperature sense is bound with the air conditioner in a forced mode according to the conditions, wherein the forced binding meets one of the following conditions:
condition 1: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is at least 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution;
condition 2: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is 0.5 to 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution of the regulation strategy, and the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy exceeds the alarm threshold of the energy-saving regulation algorithm;
s5-4, observing fluctuation of the temperature-sensing time sequence data according to the temperature-sensing time sequence data within 10 minutes before the air conditioner executes the regulation strategy and within 30 minutes after the air conditioner executes the regulation strategy, respectively calculating the variation coefficient of the temperature-sensing time sequence data within 10 minutes after the air conditioner executes the regulation strategy and the variation coefficient of the temperature-sensing time sequence data within 30 minutes after the air conditioner executes the regulation strategy, and if the temperature-sensing time sequence data is expressed asThe coefficient of variation expression is:
；
wherein,is->Temperature-sensitive temperature at moment->The number of temperature points is->Is the average value of the temperature-sensing temperature time sequence data,is the standard deviation of temperature-sensing time sequence data, +.>Is the average value of temperature time sequence data, +.>Is the coefficient of variation;
s5-5, calculating the variation coefficient of the temperature sensing time sequence data within 10 minutes after the regulation strategy is executed and the variation quantity of the variation coefficient of the temperature sensing time sequence data within 30 minutes after the regulation strategy is executedBy variation->Characterizing the variation amplitude of temperature-sensing temperature time sequence data fluctuation;
s5-6, acquiring air conditioner return air temperature time sequence data and temperature sensing time sequence data within 30 minutes after the air conditioner executes a regulation strategy, delaying the temperature sensing time sequence data backwards according to the air conditioner return air time delay time obtained in S5-1, calculating a cosine similarity coefficient between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data, and if the air conditioner return air temperature time sequence data is expressed as a vectorTemperature-sensing time series data considering return delay time of air conditioner to temperature sensing is expressed as vector +.>The cosine similarity calculation expression is:
；
wherein,the larger the value is, the more similar the trend of the air conditioner return air temperature time sequence data and the trend of the temperature sensing time sequence data are, the more the value is, the more the air conditioner return air temperature time sequence data are similar to the trend of the temperature sensing time sequence data are>For vector->Vector->Angle of (1)>The cosine similarity coefficient between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data is considered;
s5-7, repeating S5-1 to S5-6 until all the temperature senses are traversed, and calculating cosine similarity coefficients of all the temperature sensesAnd amount of change->；
S5-8, for cosine similarity coefficientAnd amount of change->Normalization processing is carried out to lead the cosine similarity coefficientAnd amount of change->The value of (2) is [0,1 ]]Between them, obtain cosine similarity coefficient +.>Matrix and variation->A matrix;
s5-9, the cosine similarity coefficientMatrix and variation->Weighting the matrix to obtain new weight of air conditioner on temperature>；
；
S5-10, based on historical weight before middle policy executionThe influence of the air conditioner on the temperature is weighted newlyAnd historical weight->Weighting to obtain the final weight +.>The expression is:
；
s5-11, rounding down according to the average binding number of the air conditioner and the temperature sensing to obtain the numberRe-selecting the weight->Before the weight of the intermediate is more than or equal to 0.8>Combining the selected temperature sensation with the temperature sensation forcedly bound with the air conditioner in S5-3 to preliminarily obtain a new binding relation between the air conditioner and the temperature sensation;
s5-12, screening the new binding relation obtained in the S5-11 according to the principle that each temperature sense is at least bound with one air conditioner, and adding the temperature sense into the new binding relation if the temperature sense which does not belong to the new binding relation exists in the binding relation obtained in the S3 and the temperature sense is not in the binding relation of other air conditioners obtained in the S3;
s5-13, removing the weight of the temperature sense in the new binding relation according to the priority, wherein the priority order is as follows: the temperature sense is at least bound with one air conditioner, the temperature sense of forced binding of the air conditioner and the temperature sense of weight calculation binding;
s5-14, eliminating the temperature sense in the binding relation obtained in the step S5-13, and avoiding the temperature sense which is the same as the binding of the corresponding standby air conditioner;
s5-15, when the number of air conditioner binding temperature senses is smaller than the average binding number of air conditioners and temperature senses, the number is obtained by rounding downWhen more than two air conditioners are used, on the premise that each temperature sense is at least bound with one air conditioner, redundant temperature senses are removed, and finally updated binding relations are obtained;
s5-16, weight obtained according to S5-10Updating a weight table of the air conditioner for temperature sensing, and updating according to the binding relation in S5-15;
s5-17, repeating the operations of S5-1 to S5-16 until the update of the binding relation of the air conditioner executing the intermediate policies in all the valid target policy windows is completed.
The invention further improves that: s5-14, the specific operation comprises the following steps:
s5-14-1, obtaining a standby air conditioner list of all air conditioners;
s5-14-2, judging whether the air conditioner and the corresponding standby air conditioner bind the same temperature sense, if so, binding only one temperature sense by the air conditioner, and binding at least two temperature senses by the corresponding standby air conditioner, deleting the same temperature sense from the binding relation of the standby air conditioner, if only one temperature sense is bound by the corresponding standby air conditioner, binding at least two temperature senses by the air conditioner, deleting the same temperature sense from the binding relation of the air conditioner, and if at least two temperature senses are bound by the air conditioner and the corresponding standby air conditioner, deleting the same temperature sense from the binding relation of the air conditioner or the corresponding standby air conditioner at random.
The invention further improves that: s6 specifically comprises the following operations:
s6-1, acquiring records of all history binding relations;
s6-2, respectively counting the times of historical binding temperature sensing of each air conditioner;
s6-3, selecting the highest binding frequencyCombining the temperature sensing with the temperature sensing of the latest binding, and finally de-duplicating according to the priority order, wherein the priority order is the temperature sensing with the highest frequency and the temperature sensing of the latest binding;
s6-4, repeating the steps S5-14 and S5-15 to obtain a stable binding relation between the air conditioner and the temperature. The beneficial effects of the invention are as follows: 1. in the intelligent regulation and control process of the data center machine room, the binding relation between the air conditioner and the temperature sensing is dynamically matched in real time according to the history regulation and control strategy, so that the service deviation is reduced, and the safety and energy-saving effect of the data center machine room are further enhanced.
The labor and cost investment for adjusting the influence binding relation by secondary analysis is greatly reduced.
3. The influence binding relation reassignment of the unregulated air conditioner and the processing method for adding the forced binding problem temperature sense are considered, and the situation of excessive binding temperature sense of the air conditioner-temperature sense is optimized through factors such as priority of the influence binding relation and the standby air conditioner, so that the binding relation is more reasonable and is closer to the actual production working condition.
4. The frequency of binding temperature senses through the comprehensive air conditioner history is further improved, the weight of the temperature senses with more binding frequency is further improved, and the influence binding relation of a stable version is calculated after a certain iteration number, so that the safety and the energy-saving effect of a data center machine room are further ensured.
Drawings
FIG. 1 is a schematic overall flow diagram of a method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an overall framework in an embodiment of the invention;
FIG. 3 is a schematic diagram of an initial weight table of air conditioner to temperature and an initial binding relationship table of air conditioner to temperature in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a binding relationship reassignment flow in an embodiment of the present invention;
FIG. 5 is a schematic diagram of binding relationship reassignment in an embodiment of the present invention;
FIG. 6 is a schematic diagram of a policy window in an embodiment of the invention;
FIG. 7 is a schematic diagram of an effective target policy window in an embodiment of the invention;
FIG. 8 is a schematic flow chart of calculating and updating weights and binding relationships in an embodiment of the invention;
FIG. 9 is a new weight schematic of air conditioning versus temperature in an embodiment of the invention;
FIG. 10 is a schematic diagram of priority of binding relationship between air conditioner and temperature sensing according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of a process for screening bound temperature sensing according to a backup air conditioner in an embodiment of the invention;
FIG. 12 is a schematic diagram showing the comparison of the weight and binding relationship before and after updating in an embodiment of the present invention;
FIG. 13 is a schematic flow chart of a process for determining and calculating a stability influence relationship in an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
As shown in fig. 1-2, the present embodiment is a method for updating the weight relationship of an air conditioner on the influence of ambient temperature in real time, including the following operations:
s1, acquiring relevant configuration parameters of equipment in a machine room and an energy-saving regulation algorithm, wherein the relevant configuration parameters comprise equipment id and signal quantity id of air conditioner and temperature sensing, standby air conditioner information of each air conditioner, whether the air conditioner can regulate and control information, temperature sensing temperature in the first 24 hours and historical time sequence data of air conditioner return air temperature.
S2, acquiring an initial weight table of the air conditioner on the temperature sensation, an initial binding relation list of the air conditioner and the temperature sensation and a temperature propagation hysteresis matrix based on the pre-regulated air conditioner and temperature sensation weight relation; the initial binding relation between the air conditioner and the temperature sensor is calculated by an initial weight table of the air conditioner to the temperature sensor, as shown in fig. 3. The temperature propagation hysteresis matrix can be expressed as: [ AC1: { sr1:2, sr2:4, sr3:1}, … ], means that the temperature sensing sr1 will be affected after 2 minutes of regulation of the air conditioner AC1, and so on.
S3, according to the principle that at least one air conditioner is bound to each temperature sense and the air conditioner which is not regulated does not bind the temperature sense, obtaining an air conditioner list which is not regulated in the current machine room according to whether the air conditioner obtained in the S1 is regulated or not, and reallocating the binding relation between the air conditioner and the temperature sense according to the air conditioner list which is not regulated in the current machine room, namely reallocating the binding relation; as shown in fig. 4, the specific operations include:
s3-1, calculating the average binding number of air conditioners and temperature senses according to the number of the temperature senses of the current machine room and the number of the adjustable air conditioners, and rounding downwards, wherein the expression is as follows:
；
wherein,the number obtained by rounding down the average binding number of the air conditioner and the temperature sensing is +.>，Representing a positive integer set;
s3-2, traversing each air conditioner in sequence according to an initial weight table of the air conditioner on the temperature sense, arranging the temperature senses corresponding to each air conditioner in reverse order according to weight magnitudes, and selecting the front part with weight magnitude of 0.8 or moreBinding the individual temperature sensations with the corresponding air conditioner;
s3-3, selecting an air conditioner with the largest weight for each temperature sense, and binding the temperature sense with the corresponding air conditioner if one of the following conditions is met:
condition 1: the temperature sensation is not yet in the initial binding relation list of all air conditioners and the temperature sensation;
condition 2: the initial binding relation list of the air conditioner corresponding to the air conditioner with the largest weight and the temperature sense obtained by the S3-2 is currently empty;
the binding relationship between air conditioner and temperature sensing is redistributed as shown in fig. 5.
S4, acquiring all history regulation policies issued and executed in the past two hours of a machine room, wherein 3 adjacent history regulation policies form a policy window, a single policy window is shown in fig. 6, traversing the whole history regulation policy list in a sliding window mode, wherein the sliding step length is 1, observing the middle policy of the policy window, combining with an air conditioner compressor dead zone, screening out the policy window which only influences the air conditioner executing the middle policy on the environmental temperature change from the time when the middle policy is executed to the time when the next history regulation policy is executed, wherein the screened policy window is an effective target policy window which is used as a prerequisite condition for updating a binding relation, and the effective target policy window is shown in fig. 7. The effective target policy window meets the following conditions at the same time:
condition 1: the time interval between the execution of adjacent history regulation strategies is more than or equal to 30 min;
condition 2: after the first 2 historical regulation strategies are executed, the set value of the return air temperature minus the temperature of other air conditioners in the machine room except for the air conditioner executing the intermediate strategy is smaller than or equal to the dead zone of the compressor of the machine room, namely, the condition that the other air conditioners are not automatically started, namely, the other air conditioners do not influence the environmental temperature, is avoided.
S5, calculating and updating the weight of the air conditioner executing the intermediate strategy to the temperature sense and the binding relation of the air conditioner executing the intermediate strategy to the temperature sense based on the effective target strategy window which meets the conditions and is screened in the S4; the intermediate strategy is the historical regulation strategy marked in fig. 7. As shown in fig. 8, the specific operations include:
s5-1, obtaining an air conditioner for single temperature senseReturn air lag time for temperature sensing;
s5-2, obtaining the air conditioner for single temperature senseTemperature sensing time sequence data within 10 minutes before the regulation strategy is executed and temperature sensing time sequence data within 30 minutes after the regulation strategy is executed;
s5-3, judging whether the temperature sense is equal to that of the air conditioner according to the conditionsAnd (3) performing forced binding, wherein the forced binding meets one of the following conditions:
condition 1: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is at least 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution;
condition 2: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is 0.5 to 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution of the regulation strategy, and the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy exceeds the alarm threshold of the energy-saving regulation algorithm;
s5-4 according to the airTemperature sensing time sequence data within 10 minutes before and within 30 minutes after executing the regulation strategy are regulated, fluctuation of the temperature sensing time sequence data is observed, and a variation coefficient of the temperature sensing time sequence data within 10 minutes after executing the regulation strategy and the temperature sensing time sequence data within 30 minutes after executing the regulation strategy are calculated respectivelyCoefficient of variation of temperature-sensitive time series data, if the temperature-sensitive time series data is expressed as +>The coefficient of variation expression is:
；
wherein,is->Temperature-sensitive temperature at moment->The number of temperature points is->Is the average value of the temperature-sensing temperature time sequence data,is the standard deviation of temperature-sensing time sequence data, +.>Is the average value of temperature time sequence data, +.>Is the coefficient of variation;
s5-5, calculating the variation coefficient of the temperature sensing time sequence data within 10 minutes after the regulation strategy is executed and the variation quantity of the variation coefficient of the temperature sensing time sequence data within 30 minutes after the regulation strategy is executedBy variation->Characterizing the variation amplitude of temperature-sensing temperature time sequence data fluctuation;
s5-6, obtaining an air conditionerAnd (3) after the regulation strategy is executed, air conditioner return air temperature time sequence data and temperature sensing time sequence data within 30 minutes are delayed backwards according to the return air delay time of the air conditioner to the temperature sense obtained in S5-1, cosine similarity coefficients between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data are calculated, and the similarity degree of the temperature sensing time sequence data and the temperature sensing time sequence data is represented by cosine values of included angles of two vectors, namely, the product of the inner product of the vectors divided by the respective modular length of the vectors is used. If the time sequence data of the return air temperature of the air conditioner is expressed as a vector +.>Temperature-sensing time series data considering return delay time of air conditioner to temperature sensing is expressed as vector +.>The cosine similarity calculation expression is:
；
wherein,the larger the value is, the more similar the trend of the air conditioner return air temperature time sequence data and the trend of the temperature sensing time sequence data are, the more the value is, the more the air conditioner return air temperature time sequence data are similar to the trend of the temperature sensing time sequence data are>For vector->Vector->Angle of (1)>The cosine similarity coefficient between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data is considered;
S5-7，repeating S5-1 to S5-6 until all the temperature senses are traversed, and calculating cosine similarity coefficients of all the temperature sensesAnd amount of change->；
S5-8, for cosine similarity coefficientAnd amount of change->Normalization processing is carried out to lead the cosine similarity coefficientAnd amount of change->The value of (2) is [0,1 ]]Between them, obtain cosine similarity coefficient +.>Matrix and variation->A matrix;
s5-9, the cosine similarity coefficientMatrix and variation->Weighting the matrix to obtain new weight of air conditioner on temperature>；
；
S5-10, based on historical weight before middle policy executionWherein, history weight +.>For the last weight of air conditioner to temperature, new weight of air conditioner to temperature is added>And historical weight->Weighting to obtain the final weight +.>The expression is:
；
for example: updating the binding relation between the air conditioner 6# and the temperature sense, and calculating the new weight of the air conditioner 6# to all the temperature senses, wherein the result is shown in fig. 9;
s5-11, rounding down according to the average binding number of the air conditioner and the temperature sensing to obtain the numberRe-selecting the weight->Before the weight of the intermediate is more than or equal to 0.8>Temperature sensing, and S5-3 medium and air conditionerCombining the forced binding temperature sense (if any) to obtain air conditioner>Binding relation with temperature sensing is new; the following is described in detail with reference to fig. 9:
if it isThe temperature sensing of the air conditioner 6# with the maximum weight of 0.8 or more is S7, and the air conditioner 6# is re-bound with the temperature sensing S7 under the condition that the forced binding temperature sensing does not exist;
s5-12, screening the new binding relation obtained in the S5-11 according to the principle that each temperature sense is at least bound with one air conditioner, and adding the temperature sense into the new binding relation between the air conditioner and the temperature sense if the temperature sense which does not belong to the new binding relation exists in the binding relation obtained in the S3 and the temperature sense is not in the binding relation of other air conditioners obtained in the S3; the following is illustrated in connection with fig. 3:
it can be seen from the figure that the temperature sense S5 bound last time by the air conditioner 6# exists in the binding relationship between the air conditioner and the temperature sense of the air conditioner 8#, so that the temperature sense S5 needs to be deleted from the binding relationship between the air conditioner and the temperature sense of the air conditioner 6 #.
S5-13, removing the weight of the temperature sensation in the new binding relation between the air conditioner and the temperature sensation according to the priority, wherein the priority order is as shown in fig. 10: the temperature sensing is at least bound with an air conditioner, the temperature sensing of the forced binding of the air conditioner and the temperature sensing of the weight calculation binding, namely, the temperature sensing is at least bound with an air conditioner, the temperature sensing of the forced binding of the air conditioner and the temperature sensing of the weight calculation binding;
s5-14, in order to avoid air conditionerAnd its spare air conditioner->When the same temperature sense is bound and the refrigerating capacity redundancy or high temperature threat is led, the air conditioner is required to be subjected to +.>The rejecting operation is performed on the corresponding temperature sense in the binding relation with the temperature sense, as shown in fig. 11, and specifically includes the following operations:
s5-14-1, obtaining a standby air conditioner list of all air conditioners;
s5-14-2, statistics air conditionerAnd a method for manufacturing the sameSpare air conditioner->Bound temperature sense and judgment of air conditionerAnd its spare air conditioner->Whether the same temperature sensation is bound or not;
s5-14-3, in air conditionerAnd its spare air conditioner->On the premise of binding the same temperature sensation: if the air conditioner is->Only one temperature sense is bound, and the standby air conditioner is provided with +.>Binding at least two temperature senses, and then using the standby air conditionerDeleting the same temperature sensation in the binding relation with the temperature sensation;
if standby air conditionerOnly one temperature sense is bound, and the air conditioner is air-conditioned>Binding at least two temperature senses, and then air-conditioning the air>Deleting the same temperature sensation in the binding relation with the temperature sensation;
if air conditionerAnd spare air conditioner->At least two temperature senses are bound, so that the air conditioner is randomly operatedAnd spare air conditioner->The same temperature sensation is deleted from the binding relation with the temperature sensation.
S5-15, when the air conditionerThe number of the binding temperature senses is less than the number obtained by rounding down the average binding number of the air conditioner and the temperature senses>When more than two air conditioners are used, on the premise that each temperature sense is at least bound with one air conditioner, redundant temperature senses are removed, and finally updated air conditioners are obtained>Binding relation with temperature sensation;
s5-16, weight obtained according to S5-10Updating the weight table and according to the air conditioner in S5-15The binding relation with the temperature sensation updates the binding relation updated last time for the energy-saving regulation algorithm to call. The updated weight of air conditioner 6# and the binding relationship between air conditioner 6# and temperature sensation in this embodiment are shown in fig. 12.
S6, repeating the operations from S5-1 to S5-16, traversing each effective target strategy window, updating the weight of the air conditioner executing the intermediate strategy in each effective target strategy window, and generating an updated binding relation.
And S7, after 50 updated binding relations are generated, integrating records of historical binding relations of each air conditioner, and further optimizing the updated binding relations to obtain stable binding relations. As shown in fig. 13, the specific operations include:
s7-1, acquiring records of all history binding relations;
s7-2, respectively counting the times of historical binding temperature sensing of each air conditioner;
s7-3, selecting the highest binding frequencyCombining the temperature sensing with the temperature sensing of the latest binding, and finally de-duplicating according to the priority order, wherein the priority order is the temperature sensing of the highest frequency and the temperature sensing of the latest binding, namely the temperature sensing of the highest frequency is more than the temperature sensing of the latest binding;
s7-4, repeating the steps S5-14 and S5-15 to obtain a stable binding relationship.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
While the foregoing is directed to embodiments of the present invention, other and further details of the invention may be had by the present invention, it should be understood that the foregoing description is merely illustrative of the present invention and that no limitations are intended to the scope of the invention, except insofar as modifications, equivalents, improvements or modifications are within the spirit and principles of the invention.
Claims (6)
1. A method for updating the weight relation of air conditioner to the influence of ambient temperature in real time is characterized in that: the method comprises the following operations:
s1, acquiring relevant configuration parameters of machine room equipment and an energy-saving regulation algorithm, wherein the relevant configuration parameters comprise standby air conditioner information of each air conditioner, whether the air conditioner can regulate and control information, temperature sensing temperature in the previous 24 hours and historical time sequence data of air conditioner return air temperature;
s2, acquiring an initial weight table of the air conditioner on the temperature sensation, an initial binding relation list of the air conditioner and the temperature sensation and a temperature propagation hysteresis matrix based on the pre-regulated air conditioner and temperature sensation weight relation;
s3, according to the principle that each temperature sensing is at least bound with one air conditioner and the air conditioner which cannot be regulated does not carry out temperature sensing binding, reallocating the binding relationship between the air conditioner and the temperature sensing, namely reallocating the binding relationship according to whether the air conditioner of the current machine room can regulate and control information;
s4, acquiring all history regulation policies issued and executed in the past two hours of a machine room, wherein 3 adjacent history regulation policies form a policy window, traversing the whole history regulation policy list in a sliding window mode, screening out a policy window which only has the influence of an air conditioner executing the middle policy on the environmental temperature change from the period from the execution of the middle policy to the execution of the next history regulation policy by combining an air conditioner compressor dead zone based on the middle policy of the policy window, and screening out the obtained policy window as an effective target policy window;
s5, calculating and updating the weight of the air conditioner executing the intermediate strategy on the temperature sense based on the effective target strategy windows which meet the conditions and are screened in the S4, and updating the binding relation corresponding to the air conditioner executing the intermediate strategy in each effective target strategy window to independently generate an updated binding relation;
and S6, after each binding relation with a set number is generated, integrating records of historical binding relations of each air conditioner, and further optimizing the updated binding relation to obtain a stable binding relation.
2. The method for updating the weight relation of the air conditioner on the environmental temperature in real time according to claim 1, wherein the method comprises the following steps: the specific operation of S3 includes:
s3-1, calculating the average binding number of air conditioners and temperature senses according to the number of the temperature senses of the current machine room and the number of the adjustable air conditioners, and rounding downwards, wherein the expression is as follows:
；
wherein,the number obtained by rounding down the average binding number of air conditioner and temperature sensing is +.>，/>Representing a positive integer set;
s3-2, traversing each air conditioner in sequence according to an initial weight table of the air conditioner on the temperature sense, arranging the temperature senses corresponding to each air conditioner in reverse order according to weight magnitudes, and selecting the front part with weight magnitude of 0.8 or moreBinding the individual temperature sensations with the corresponding air conditioner;
s3-3, selecting an air conditioner with the largest weight for each temperature sense, and binding the temperature sense with the corresponding air conditioner if one of the following conditions is met:
condition 1: the temperature sensation is not yet in the initial binding relation list of all air conditioners and the temperature sensation;
condition 2: the initial binding relation list of the air conditioner corresponding to the air conditioner with the largest weight and the temperature sense obtained by the S3-2 is currently empty.
3. The method for updating the weight relation of the air conditioner on the environmental temperature in real time according to claim 1, wherein the method comprises the following steps: the effective target policy window in S4 meets the following conditions at the same time:
condition 1: the time interval between the execution of adjacent history regulation strategies is more than or equal to 30 min;
condition 2: after the first 2 historical regulation strategies are executed, the set value of the return air temperature minus the temperature of other air conditioners in the machine room except for the air conditioner executing the intermediate strategy is smaller than or equal to the dead zone of the compressor of the machine room, namely, the condition that the other air conditioners are not started automatically is not caused.
4. The method for updating the weight relation of the air conditioner on the environmental temperature in real time according to claim 1, wherein the method comprises the following steps: the specific operation of S5 includes:
s5-1, for a single temperature sensor, acquiring the return air lag time of the air conditioner to the temperature sensor based on a temperature propagation lag matrix;
s5-2, acquiring temperature sensing time sequence data within 10 minutes before the air conditioner executes the regulation strategy and temperature sensing time sequence data within 30 minutes after the air conditioner executes the regulation strategy for single temperature sensing;
s5-3, judging whether the temperature sense is bound with the air conditioner in a forced mode according to the conditions, wherein the forced binding meets one of the following conditions:
condition 1: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is at least 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution;
condition 2: the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy is 0.5 to 1 ℃ higher than the maximum value of the temperature sensing temperature within 10 minutes before the execution of the regulation strategy, and the maximum value of the temperature sensing temperature within 30 minutes after the execution of the regulation strategy exceeds the alarm threshold of the energy-saving regulation algorithm;
s5-4, observing fluctuation of the temperature-sensing time sequence data according to the temperature-sensing time sequence data within 10 minutes before the air conditioner executes the regulation strategy and within 30 minutes after the air conditioner executes the regulation strategy, respectively calculating the variation coefficient of the temperature-sensing time sequence data within 10 minutes after the air conditioner executes the regulation strategy and the variation coefficient of the temperature-sensing time sequence data within 30 minutes after the air conditioner executes the regulation strategy, and if the temperature-sensing time sequence data is expressed asThe coefficient of variation expression is:
；
wherein,is->Temperature-sensitive temperature at moment->The number of temperature points is->Is the average value of temperature time sequence data, +.>Is the standard deviation of temperature-sensing time sequence data, +.>Is the average value of temperature time sequence data, +.>Is the coefficient of variation;
s5-5, calculating the variation coefficient of the temperature sensing time sequence data within 10 minutes after the regulation strategy is executed and the variation quantity of the variation coefficient of the temperature sensing time sequence data within 30 minutes after the regulation strategy is executedBy variation->Characterizing the variation amplitude of temperature-sensing temperature time sequence data fluctuation;
s5-6, acquiring air conditioner return air temperature time sequence data and temperature sensing time sequence data within 30 minutes after the air conditioner executes a regulation strategy, delaying the temperature sensing time sequence data backwards according to the air conditioner return air time delay time obtained in S5-1, calculating a cosine similarity coefficient between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data, and if the air conditioner return air temperature time sequence data is expressed as a vectorTemperature-sensing time series data considering return delay time of air conditioner to temperature sensing is expressed as vector +.>The cosine similarity calculation expression is:
；
wherein,the larger the value is, the more similar the trend of the air conditioner return air temperature time sequence data and the trend of the temperature sensing time sequence data are, the more the value is, the more the air conditioner return air temperature time sequence data are similar to the trend of the temperature sensing time sequence data are>For vector->Vector->Angle of (1)>The cosine similarity coefficient between the temperature sensing time sequence data and the air conditioner return air temperature time sequence data is considered;
s5-7, repeating S5-1 to S5-6 until all the temperature senses are traversed, and calculating cosine similarity coefficients of all the temperature sensesAnd amount of change->；
S5-8, for cosine similarity coefficientAnd amount of change->Normalization processing is carried out to enable cosine similarity coefficient +.>And amount of change->The value of (2) is [0,1 ]]Between them, obtain cosine similarity coefficient +.>Matrix and variation->A matrix;
s5-9, the cosine similarity coefficientMatrix and variation->Weighting the matrix to obtain new weight of air conditioner on temperature>；
；
S5-10, based on historical weight before middle policy executionIs to weigh the air conditioner with new weight for temperature sensing->And historical weight->Weighting to obtain the final weight +.>The expression is:
；
s5-11, rounding down according to the average binding number of the air conditioner and the temperature sensing to obtain the numberRe-selecting weightsBefore the weight of the intermediate is more than or equal to 0.8>Combining the selected temperature sensation with the temperature sensation forcedly bound with the air conditioner in S5-3 to preliminarily obtain a new binding relation between the air conditioner and the temperature sensation;
s5-12, screening the new binding relation obtained in the S5-11 according to the principle that each temperature sense is at least bound with one air conditioner, and adding the temperature sense into the new binding relation if the temperature sense which does not belong to the new binding relation exists in the binding relation obtained in the S3 and the temperature sense is not in the binding relation of other air conditioners obtained in the S3;
s5-13, removing the weight of the temperature sense in the new binding relation according to the priority, wherein the priority order is as follows: the temperature sense is at least bound with one air conditioner, the temperature sense of forced binding of the air conditioner and the temperature sense of weight calculation binding;
s5-14, eliminating the temperature sense in the binding relation obtained in the step S5-13, and avoiding the temperature sense which is the same as the binding of the corresponding standby air conditioner;
s5-15, when the number of air conditioner binding temperature senses is smaller than the average binding number of air conditioners and temperature senses, the number is obtained by rounding downWhen more than two air conditioners are used, on the premise that each temperature sense is at least bound with one air conditioner, redundant temperature senses are removed, and finally updated binding relations are obtained;
s5-16, weight obtained according to S5-10Updating a weight table of the air conditioner for temperature sensing, and updating according to the binding relation in S5-15;
s5-17, repeating the operations of S5-1 to S5-16 until the update of the binding relation of the air conditioner executing the intermediate policies in all the valid target policy windows is completed.
5. The method for updating the weight relation of the air conditioner on the environmental temperature in real time according to claim 4, wherein the method comprises the following steps: the specific operation of S5-14 comprises the following steps:
s5-14-1, obtaining a standby air conditioner list of all air conditioners;
s5-14-2, judging whether the air conditioner and the corresponding standby air conditioner bind the same temperature sense, if so, binding only one temperature sense by the air conditioner, and binding at least two temperature senses by the corresponding standby air conditioner, deleting the same temperature sense from the binding relation of the standby air conditioner, if only one temperature sense is bound by the corresponding standby air conditioner, binding at least two temperature senses by the air conditioner, deleting the same temperature sense from the binding relation of the air conditioner, and if at least two temperature senses are bound by the air conditioner and the corresponding standby air conditioner, deleting the same temperature sense from the binding relation of the air conditioner or the corresponding standby air conditioner at random.
6. The method for updating the weight relation of the air conditioner on the environmental temperature in real time according to claim 4, wherein the method comprises the following steps: the step S6 specifically comprises the following operations:
s6-1, acquiring records of all history binding relations;
s6-2, respectively counting the times of historical binding temperature sensing of each air conditioner;
s6-3, selecting the most frequent bindingHigh and highCombining the temperature sensing with the temperature sensing of the latest binding, and finally de-duplicating according to the priority order, wherein the priority order is the temperature sensing with the highest frequency and the temperature sensing of the latest binding;
s6-4, repeating the steps S5-14 and S5-15 to obtain a stable binding relationship.
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| CN114923268A (en) * | 2022-07-11 | 2022-08-19 | 南京群顶科技有限公司 | Machine room air conditioner regulation and control method and device based on air conditioner load and regional temperature evaluation |
| CN116358107A (en) * | 2023-05-10 | 2023-06-30 | 南京群顶科技股份有限公司 | Temperature-sensing air conditioner weight relation calculation method based on pre-regulation and control |
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| CN117479496A (en) * | 2023-10-30 | 2024-01-30 | 中国南方电网有限责任公司 | Computer lab temperature regulation economizer system based on thing networking |
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| CN114923268A (en) * | 2022-07-11 | 2022-08-19 | 南京群顶科技有限公司 | Machine room air conditioner regulation and control method and device based on air conditioner load and regional temperature evaluation |
| CN116406137A (en) * | 2023-04-23 | 2023-07-07 | 南京群顶科技股份有限公司 | Differential pressure self-adaptive adjustment method, system and equipment based on temperature sensing change |
| CN116358107A (en) * | 2023-05-10 | 2023-06-30 | 南京群顶科技股份有限公司 | Temperature-sensing air conditioner weight relation calculation method based on pre-regulation and control |
| CN117479496A (en) * | 2023-10-30 | 2024-01-30 | 中国南方电网有限责任公司 | Computer lab temperature regulation economizer system based on thing networking |
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