CN115437876A - Data center management method and device, electronic equipment and storage medium - Google Patents
Data center management method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a management method and a management device of a data center, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring historical monitoring information aiming at a plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment; predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information; when the predicted PUE exceeds a PUE threshold value, obtaining predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information; and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period. Through the embodiment of the invention, when the PUE of the data center possibly exceeds the preset value, the electric equipment of the data center is controlled, so that the PUE of the data center is prevented from exceeding the preset value; thus, the energy efficiency of the data center is improved.
Description
Technical Field
The present invention relates to the technical field of energy consumption management, and in particular, to a management method and apparatus for a data center, an electronic device, and a storage medium.
Background
With the wide use of technologies such as cloud computing and big data mining, the demand of users on computing capacity is rapidly increased, the rapid development of large-scale data centers is promoted, and various telecommunication operators vigorously develop the data centers.
A data center may be deployed with multiple consumers of electricity, for example: IT equipment (Internet Technology), refrigeration equipment, etc.; for a data center, the energy consumption utilization can be represented by PUE (Power Usage efficiency); wherein PUE = total energy consumption of the data center/energy consumption of IT equipment; when the PUE is closer to 1, IT indicates that the non-IT equipment consumes less energy, i.e., the level of efficiency is better.
In order to improve the energy efficiency of the data center, it is necessary to ensure that the PUE of the data center is always at a value close to 1; how to effectively control the PUE of the data center becomes one of the problems which need to be solved aiming at the data center at present.
Disclosure of Invention
In view of the above problems, it is proposed to provide a management method, apparatus, electronic device and storage medium of a data center that overcome or at least partially solve the above problems, including:
a method of managing a data center deployed with a plurality of electrical devices, the method comprising:
acquiring historical monitoring information aiming at the plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment;
predicting the PUE of the power supply use efficiency of the data center in a preset time period according to the historical monitoring information and the historical environment information;
when the predicted PUE exceeds a PUE threshold value, acquiring predicted environment information aiming at the preset time period, and determining a target energy-saving and energy-consumption strategy aiming at the plurality of electric equipment under the predicted environment information;
and controlling the plurality of electric equipment according to the target energy-saving energy consumption strategy in a preset time period.
Optionally, the method further comprises:
when an inquiry request is received, first monitoring information aiming at the plurality of electric equipment in the previous time period is obtained;
determining a target PUE according to the first monitoring information;
when the target PUE exceeds the PUE threshold value, displaying a first identifier and the first monitoring information;
and when the target PUE does not exceed the PUE threshold value, displaying a second identifier and the first monitoring information.
Optionally, the method further comprises:
collecting second monitoring information of each electric device in the current time period;
storing the second monitoring information to a monitoring information database based on a preset measuring point code;
the obtaining of the first monitoring information for the plurality of electric devices in the previous time period includes:
and acquiring the first monitoring information from the monitoring information database according to the target measuring point code corresponding to the first monitoring information.
Optionally, the first monitoring information includes at least one of: active power, active power degree, heating and ventilation data.
Optionally, the predicting, according to the historical monitoring information and the historical environmental information, the power usage efficiency PUE of the data center in a preset time period includes:
predicting energy consumption information of each electric device in a preset time period according to the historical monitoring data and the historical environment information;
and calculating the predicted PUE according to the energy consumption information of each electric device in a preset time period.
Optionally, the predicted PUE comprises at least one of: a second PUE for the data center building, and a third PUE for each room in the data center.
Optionally, the predicted PUE is predicted by a preset long-short term memory network.
The embodiment of the present invention further provides a management apparatus for a data center, where the data center is deployed with a plurality of electric devices, and the apparatus includes:
the acquisition module is used for acquiring historical monitoring information aiming at the plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment;
the prediction module is used for predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information;
the strategy determining module is used for acquiring predicted environment information aiming at the preset time period when the predicted PUE exceeds a PUE threshold value, and determining a target energy-saving and energy-consumption strategy aiming at the plurality of electric equipment under the predicted environment information;
and the control module is used for controlling the plurality of electric equipment according to the target energy-saving energy consumption strategy in a preset time period.
Optionally, the apparatus further comprises:
the display module is used for acquiring first monitoring information aiming at the plurality of electric equipment in the previous time period when receiving the query request; determining a target PUE according to the first monitoring information; when the target PUE exceeds the PUE threshold value, displaying a first identifier and the first monitoring information; and when the target PUE does not exceed the PUE threshold value, displaying a second identifier and the first monitoring information.
Optionally, the apparatus further comprises:
the storage module is used for collecting second monitoring information of each piece of electric equipment in the current time period; storing the second monitoring information to a monitoring information database based on a preset measuring point code;
the display module includes:
and the first monitoring information acquisition submodule is used for acquiring the first monitoring information from the monitoring information database according to the target measuring point code corresponding to the first monitoring information.
Optionally, the first monitoring information includes at least one of: active power, active power degree, heating and ventilation data.
Optionally, the prediction module includes:
the energy consumption prediction submodule is used for predicting the energy consumption information of each electric device in a preset time period according to the historical monitoring data and the historical environment information;
and the PUE calculation submodule is used for calculating the predicted PUE according to the energy consumption information of each electric device in a preset time period.
Optionally, the predicted PUE comprises at least one of: a second PUE for the data center building, and a third PUE for each room in the data center.
Optionally, the predicted PUE is predicted by a preset long-short term memory network.
An embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the computer program is executed by the processor, the method for managing a data center is implemented.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the management method of the data center is implemented.
The embodiment of the invention has the following advantages:
in the embodiment of the invention, historical monitoring information aiming at a plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment are obtained; predicting the power utilization efficiency PUE of the data center in a preset time period according to historical monitoring information and historical environmental information; when the predicted PUE exceeds a PUE threshold value, obtaining predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information; and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period. Through the embodiment of the invention, when the PUE of the data center possibly exceeds the preset value, the electric equipment of the data center is controlled, so that the PUE of the data center is prevented from exceeding the preset value; thus, the energy efficiency of the data center is improved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flow chart of the steps of a method for managing a data center according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a long term short term memory network according to an embodiment of the present invention;
FIG. 3 is a flow chart of steps in another data center management method according to an embodiment of the invention;
FIG. 4 is a flow chart illustrating a calculation of PUE according to an embodiment of the present invention;
FIG. 5 is a schematic view of an interactive interface of an embodiment of the present invention;
FIG. 6 is a schematic flow chart illustrating a process of querying energy efficiency of a data center according to an embodiment of the present invention
Fig. 7 is a block diagram of a management apparatus of a data center according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a flowchart illustrating steps of a management method of a data center according to an embodiment of the present invention is shown, where the data center may be deployed with a plurality of electric devices, for example: IT devices and non-IT devices.
Specifically, the method may include the steps of:
The historical monitoring information can be information obtained by monitoring a plurality of electric devices in a historical time period by a pointer; in particular, static data and dynamic data for the powered device may be included.
Static data may refer to information that is fixed for the powered device, such as: the number of devices, the model of the devices, etc.; dynamic data may refer to information that changes in real time to the powered device, such as: electricity consumption, machine room set humidity, etc.
The historical environmental information may refer to information that may affect the energy consumption of the electric device at the time when the historical monitoring information corresponds to the historical monitoring information, for example: temperature, humidity, etc.
As table 1, historical monitoring information and historical environmental information of a portion of an embodiment of the present invention are shown:
table 1:
| outdoor wet bulb temperature |
| Outdoor dry bulb temperature |
| Set temperature of machine room |
| Humidity setting in machine room |
| Number of water chilling units |
| Number of freezing pumps |
| Number of cooling pumps |
| Total electric quantity degree of IT machine room |
| Total electric quantity degree of precision air conditioner room |
| Total electric quantity of cold source machine room |
| Frequency setting of a refrigeration pump |
| Cooling pump frequency setting |
| Wet bulb temperature difference of cooling tower |
| Current of cold machine |
| Cold storage tank flowmeter |
In practical application, when the PUE of the data center needs to be predicted, the historical monitoring information of each electric device in the data center and the historical environmental information at the moment corresponding to the historical monitoring information can be obtained first.
As an example, the collected monitoring information and environmental information may be stored in a database in advance; when the PUE of the data center in a future time period needs to be predicted, the historical monitoring information and the historical environmental information may be directly obtained from the database, which is not limited in the embodiment of the present invention.
And step 102, predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information.
As an example, the predicted PUE may include at least one of: a first predicted PUE for a data center building, and a second predicted PUE for each machine room in the data center.
Among other things, a building may include a machine room with IT equipment deployed, and other areas than the machine room with a data center deployed, such as: elevators, etc. A machine room may refer to an area where IT equipment is deployed.
In practical application, after the historical monitoring information and the historical environmental information are obtained, the historical monitoring information and the historical environmental information can be input into a preset prediction model so as to predict and obtain a predicted PUE of the data center in a future preset time period.
For the first predicted PUE for the data center building, the global PUE of the data center may be taken as the PUE for the data center building; the global PUE can be calculated by the following formula:
global PUE = (global IT energy consumption + heating ventilation energy consumption + lighting energy consumption + energy saving project energy consumption)/global IT energy consumption.
The system comprises a global IT energy consumption management system, a data center and a free network computer room, wherein one part of the global IT energy consumption is the energy consumption of the internet data center hosting computer room, and the other part of the global IT energy consumption is the energy consumption of the free network computer room; the matched heating and ventilation energy consumption can comprehensively consider the loads of the fans at the tail ends of the air conditioners in the cold station and the machine room; the lighting energy consumption can be the energy consumption of all lighting in the data center; the building Power distribution loss is obtained by making a difference between a distribution room low-voltage load output cabinet (UPS (uninterruptible Power Supply)) and the sum of the energy consumption of electric meters of all IT machine room head cabinets (a plurality of servers can be deployed in each head cabinet); the energy-saving project is independently metering engineering energy consumption such as indirect evaporation cooling, CO2 cold carrying, natural cold source and the like.
As an example, the global IT energy consumption may be calculated based on the global UPS and the global dc; the matched heating and ventilation energy consumption can be calculated and obtained on the basis of a refrigerating unit, a cooling tower, a water pump, an electronic valve and an air-conditioning power distribution cabinet; the energy-saving project energy consumption can be calculated based on indirect evaporation cold, CO2 cold carrying, a natural cold source and the like.
For a second predicted PUE for a single room, it can be calculated by the following formula:
single machine room PUE = (machine room IT energy consumption + power distribution apportionment energy consumption + water cooling apportionment energy consumption + energy saving project apportionment energy consumption + air conditioner power distribution cabinet energy consumption + machine room lighting energy consumption)/machine room IT energy consumption.
The energy consumption of the machine room IT is the sum of the energy consumption values of all the electricity meters of the first row cabinet; the distribution allocation, the water cooling allocation and the energy-saving project allocation are respectively calculated according to the IT real-time load ratio of the machine room, the UPS self loss and the line loss, and the allocation amount of the real-time energy consumption of the energy-saving project in the machine room of a water cooling system; the operation index of the heating and ventilation system is a key attention object, the safety of the machine room environment is reflected while the energy consumption value is measured, and the safety comprises measuring point data such as air conditioner return air, water inlet and outlet, fan rotating speed, machine room temperature and humidity and the like.
As an example, the power distribution apportionment energy consumption may be calculated based on building power distribution loss, machine room IT energy consumption, and downstream head cabinet total work; the water cooling apportionment energy consumption can be calculated based on building matched heating ventilation, machine room ITE energy consumption and global IT energy consumption; the energy-saving project apportioned energy consumption can be calculated based on the energy consumption of the building energy-saving project, the energy consumption of the machine room IT and the overall IT energy consumption.
As an example, the predicted PUE may be predicted from a preset long-short term memory network; specifically, the prediction model may be a preset long-term and short-term memory network.
As shown in FIG. 2, a single long-short term memory network unit protects and controls the information in the memory cell by 3 gates, the information is realized by multiplying the point of the activation function by [ ], and the state of each gate is controlled by a series of parameters of gradient descent training. Each gate in the LSTM (Long Short-term memory network) has a specific and unique function. Left behind door f from previous state h t-1 To decide which information to discard. Input x t And h t-1 After the operation of the update gate u, the update state h is determined together with the corrected forgetting gate f t Should use the candidate state
How much weight is. To generate an output y t First using non-linear g 2 The function filters its current state and then operates with the output gate o to the next block of output y t In which a partial state y is returned t As the next input y t-1 . Each gate being dependent on a current external input x t And the previous output y t-1 。
forget gate:f t ＝σ(W f x t +R f y t-1 +b f )
update state:u t ＝σ(W u x t +R u y t-1 +b u )
output gate:o t ＝σ(W o x t +R o y t-1 +b o )
output:yt＝o t ⊙g 2 (h t )
In the formula: x is a radical of a fluorine atom t Is the input vector at the time t; w is a group of t 、W h 、W u And W o Is a weight matrix associated with the input unit; r f 、R h 、R u And R o A weight matrix connected to the hidden layer; and b f 、b h 、b u And b o Is a bias vector; the activation function sigma is sigmoid or tanh; g 1 And g 2 Is a non-linear activation function; an as dot product.
Energy consumption prediction is carried out through a stacking cycle long-short term memory network:
building a stacked LSTM network by using LSTM units, and building a four-layer LSTM stacked network: the first layer is composed of 32 LSTM units; the second layer is composed of 64 LSTM units; the third layer is composed of 16 LSTM units; the fourth layer is composed of 3 full-connection layer units; by adding the depth of the network, the training efficiency is improved, and higher accuracy is obtained.
And 103, when the predicted PUE exceeds the PUE threshold value, acquiring predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information.
Wherein, the PUE threshold value can be set according to the actual situation; for example: the PUE threshold may be set according to requirements for PUEs of the data center; it should be noted that, in order to pre-warn the PUE of the data center, a PUE threshold lower than the requirement of the PUE of the data center may be set; for example: if the PUE of the data center needs to be lower than 1.6, the PUE threshold may be set to 1.5, which is not limited in the embodiment of the present invention.
After obtaining the predicted PUE for the future predetermined time period, the magnitude relationship between the predicted PUE and the PUE threshold may be compared.
If the predicted PUE does not exceed the PUE threshold, it may indicate that the PUE of the data center is at a normal level within a preset time period in the future; at this time, the original operation can be continuously maintained without intervening in the control of each electric device of the data center.
If the predicted PUE exceeds the PUE threshold, it may indicate that the PUE of the data center is at an abnormal level within a preset time period in the future; at this time, in order to improve the energy efficiency of the data center, the management and control of each electric device of the data center may be actively involved.
Specifically, the predicted environment information in a future preset time period may be obtained first; the predicted environment information may be obtained from a server that provides a weather forecast, which is not limited in this embodiment of the present invention.
Then, based on the obtained predicted environment information, a minimum PUE that can be achieved by the data center under the condition that the data center can provide services in a normal production manner under the predicted environment information can be determined, and a target energy saving and consumption strategy for each electric device under the minimum PUE can be determined.
IT should be noted that, when IT is ensured that the data center can provide services normally, the energy supply of the IT equipment needs to be ensured; in addition, because IT equipment emits a large amount of heat during operation, and excessive temperature may cause failure of IT equipment, IT is necessary to ensure the energy supply of other electric equipment (such as air conditioners, water cooling equipment, etc.) besides IT equipment to ensure normal operation of IT equipment.
And 104, controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period.
When the preset time period is reached, in order to avoid that the PUE of the data center in the preset time period is too high, a target energy-saving energy consumption strategy can be adopted to control a plurality of electric devices of the data center, so as to ensure that the PUE of the data center in the preset time period can be in a normal level.
In the embodiment of the invention, historical monitoring information aiming at a plurality of electric equipment and historical environment information which is in an incidence relation with the energy consumption of the electric equipment at the corresponding moment are obtained; predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information; when the predicted PUE exceeds a PUE threshold value, obtaining predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information; and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period. By the embodiment of the invention, when the PUE of the data center possibly exceeds the preset value, the control on each electric device of the data center is realized, so that the PUE of the data center is prevented from exceeding the preset value; thus, the energy efficiency of the data center is improved.
Referring to fig. 3, a flowchart illustrating steps of a management method of a data center according to an embodiment of the present invention is shown, which may include the following steps:
In practical application, when the PUE of the data center needs to be predicted, the historical monitoring information and the historical environment information at the moment corresponding to the historical monitoring information can be obtained from the database.
And 302, predicting energy consumption information of each electric device in a preset time period according to the historical monitoring data and the historical environment information.
In practical applications, PUE is actually related to the energy consumption of each electrical device of the data center; therefore, after the historical monitoring data and the historical environmental information are obtained, the energy consumption information of each electric device in the preset time period can be predicted based on the historical monitoring data and the historical environmental information; the energy consumption information may refer to power consumption of the electric device in a preset time period and corresponding operating parameters.
The energy consumption of the electric equipment is related to the environment; for example: when the ambient temperature is higher, the air conditioner will consume more electric quantity to guarantee that the temperature of data center is at the default. Therefore, when the energy consumption information of each electric device in the preset time period is predicted, the predicted environment information in the preset time period can be obtained firstly; the predicted environment information may be obtained from a server capable of providing a weather forecast, which is not limited in this embodiment of the present invention.
After the preset environment information is obtained, the historical monitoring data, the historical environment information and the preset environment information input value can be preset in a prediction model, so that the electric quantity which is required to be consumed by the data center to operate normally under the environment corresponding to the preset environment information can be predicted according to the historical monitoring data and the historical environment information; and determines corresponding energy consumption information based on the amount of power.
And 303, calculating the predicted PUE according to the energy consumption information of each electric device in a preset time period.
After the energy consumption information of each electric device in the preset time period is obtained, the predicted PUE of the data center in the preset time period can be calculated based on the energy consumption information.
As an example, for the first prediction PUE, the outdoor wet bulb temperature, the outdoor dry bulb temperature, the machine room set humidity, the number of water chilling units, the number of freezing pumps, the number of cooling pumps, the total electric quantity degree of IT machine room, the total electric quantity degree of precision air conditioner machine room, the total electric quantity of cold source machine room, the frequency setting of cooling pumps, the frequency setting of freezing pumps, the wet bulb temperature difference of cooling towers, the current of cold machines, the flow meter of cold storage tanks, etc. may be used as input parameters of the preset prediction model; such that the predictive model outputs energy consumption information for determining the first predicted PUE.
As another example, for the second prediction PUE, the air-conditioning return air temperature, the air-conditioning return air humidity, the machine room ambient temperature, the air-conditioning energy consumption, the first cabinet IT energy consumption, the air supply mode, and the like may be used as input parameters of the preset prediction model; such that the predictive model outputs energy consumption information for determining the second predicted PUE.
Referring to FIG. 4, the predictive model may be an AI (Artificial Intelligence) model; the outdoor environmental factors, the machine room environmental indexes and the refrigeration system equipment operation parameters can be used for training an AI model and outputting corresponding equipment energy consumption; based on the device energy consumption, calculation of the PUE may be performed.
And 304, when the predicted PUE exceeds the PUE threshold value, acquiring predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information.
After obtaining the predicted PUE for the future predetermined time period, the magnitude relationship between the predicted PUE and the PUE threshold may be compared.
If the predicted PUE does not exceed the PUE threshold, it may indicate that the PUE of the data center is at a normal level within a preset time period in the future; at this time, the original operation can be continuously maintained without intervening in the management and control of each electric device of the data center.
If the predicted PUE exceeds the PUE threshold, it may indicate that the PUE of the data center is at an abnormal level within a preset time period in the future; at this time, in order to improve the energy efficiency of the data center, the management and control of each electric device of the data center may be actively involved.
Specifically, the predicted environment information in a future preset time period may be obtained first; the predicted environment information may be obtained from a server that provides a weather forecast, which is not limited in this embodiment of the present invention.
Then, based on the obtained predicted environment information, a minimum PUE that can be achieved by the data center under the condition that the data center can provide services in a normal production mode under the predicted environment information can be determined, and a target energy-saving and energy-consumption strategy for each electric device under the minimum PUE is determined.
As an example, the target energy saving and energy consumption policy may be a setting parameter for the electric device, as shown in table 2, which shows a setting parameter for the electric device related to a target energy saving and energy consumption policy of an embodiment of the present invention,
table 2:
| serial number | Refrigeration |
| 1 | Frequency setting of a refrigeration pump |
| 2 | Cooling pump frequency setting |
| 3 | Temperature range of cooling tower |
| 4 | Predicted cold source machine room power |
And 305, controlling the plurality of electric devices according to the target energy-saving and energy-consumption strategy in a preset time period.
When the preset time period is reached, in order to avoid that the PUE of the data center in the preset time period is too high, a target energy-saving energy consumption strategy can be adopted to control a plurality of electric devices of the data center, so that the PUE of the data center in the preset time period can be in a normal level.
As an example, the first monitoring information includes at least one of: active power, active power degree, heating and ventilation data.
The active power refers to alternating current electric energy actually emitted or consumed in unit time and is average power in a period; the method can be used for reflecting the energy consumption operation condition of the data center in real time and guiding operation and maintenance personnel to manage and optimize. The active power is the product of the active power consumed by the electric equipment and the time; and reflecting the overall energy consumption situation and average indexes of the data center within a period of time. The heating and ventilation data focuses on air conditioning and temperature and humidity data in the machine room, reflects the correlation between the operation of the heating and ventilation system and energy consumption indexes, and provides decision basis for optimizing the operation of equipment.
In the field of power environment monitoring, aiming at the energy consumption monitoring of an old large-scale data center, the problems of difficult energy consumption data acquisition, slow data presentation and difficult data analysis are limited, the energy consumption metering of the data center is usually carried out by adopting a manual timing meter reading and periodic accounting statistics mode, the dynamic monitoring and displaying capability of building energy consumption is not provided, the real validity of data reported by energy-saving manufacturers cannot be effectively verified, and the great difficulty is brought to the energy consumption management of the data center.
The method aims at the problems that the energy consumption data acquisition is difficult, the data presentation is slow and the data analysis is difficult in the existing large-scale data center; according to the embodiment, the monitoring server can capture data regularly and in a customized manner by combining the interface specification definition based on the webservice service with the production practice and the system capacity through an energy consumption system interface technology.
Therefore, when a query request for the energy consumption of the data center is received, the first monitoring information for the plurality of electric devices in the previous time period can be acquired, so that the energy consumption condition of each electric device of the data center in the previous time period can be shown to a user.
In an embodiment of the present invention, in order to avoid the problems of data concurrent congestion and foreground refresh blocking, a database for monitoring information may be pre-established through the following steps:
collecting second monitoring information of each electric device in the current time period; and storing the second monitoring information to a monitoring information database based on the preset measuring point codes.
First, the energy consumption conditions of the electric devices can be collected in each time period, and second monitoring information can be generated.
Then, the second monitoring information can be stored in the monitoring information database according to the preset point codes, so that when the monitoring information is subsequently acquired from the monitoring information database, the corresponding monitoring information can be directly called based on the preset point codes. If there is new data, the new measurement point may be supplemented with a definition code.
As shown in Table 3, a portion of the default station codes for embodiments of the present invention are shown.
Table 3:
as an example, a timing algorithm may be deployed in the monitoring server in advance; therefore, the monitoring server may collect monitoring information periodically based on the timing algorithm, which is not limited in the embodiment of the present invention.
The data acquisition work can be undertaken by the collector of the intelligent dynamic loop monitoring unit of the communication base station; the monitoring server can send a command to the collector of the intelligent dynamic ring monitoring unit of the communication base station at regular time through a preset operation program to call the data of the marked measuring point codes.
Based on the monitoring information database, the embodiment of the present invention can be implemented based on the following steps when acquiring the first monitoring information to be displayed:
and acquiring the first monitoring information from the monitoring information database according to the target measuring point code corresponding to the first monitoring information.
Specifically, when first monitoring information to be displayed is obtained, the corresponding first monitoring information can be directly called from the monitoring information database based on a target measuring point code corresponding to the first monitoring information; therefore, the problems of data concurrent congestion and foreground refreshing blockage are solved by storing the monitoring information in the monitoring information database and calling the monitoring information in the foreground.
And 307, determining the target PUE according to the first monitoring information.
After determining the first monitoring information, a target PUE of the data center during a last time period may be determined based on the first monitoring information.
And 308, when the target PUE exceeds the PUE threshold value, displaying the first identification and the first monitoring information.
If the target PUE exceeds the PUE threshold, it may indicate that the energy efficiency in a period of time on the data center is poor; at this moment, the first identification representing sub-health and the first monitoring information can be displayed, so that the user can know that the energy efficiency of the data center is poor in time, and each electric device of the data center is controlled in time.
If the target PUE does not exceed the PUE threshold, it may indicate that the energy efficiency in a time period on the data center is better; at this time, the second identifier indicating health may be presented, together with the first monitoring information.
FIG. 5 is a schematic diagram showing an interactive interface of an embodiment of the present invention; the interactive interface displays a first identifier (namely treatment effect evaluation) and first monitoring information (namely energy consumption conditions of all electric equipment and the like).
The interface can be divided into three functional areas of an overall index, a machine room index and a unit configuration from top to bottom:
in the whole index area, besides the real-time PUE value of the building, various production loads such as IT equipment energy consumption, heating and ventilation equipment energy consumption, lighting equipment energy consumption and the like can be compared in parallel.
The machine room index area divides machine rooms in rows, and static basic information such as the area of the machine rooms, the number of air conditioners, rated refrigerating capacity and the like is recorded; at the same time, dynamic data in the database for the last hour is presented.
And the unit configuration area presents relevant indexes of the clicked machine room in the machine room index area, and reflects the power consumption ratio of various devices in the machine room and the PUE operation curve of the machine room in a pie chart and a line chart mode.
In the machine room index area, after the PUE of a single machine room is calculated, the PUE is compared with a threshold value, and different configuration graphs are presented through 'treatment effect evaluation'.
The abnormal data can enable the operation and maintenance team to pay attention to the energy consumption operation condition of the machine room, examine the matching relation between the IT load and the air conditioner refrigerating capacity, set an optimization scheme, adjust in time and monitor in real time.
Fig. 6 is a schematic flow chart illustrating a process of querying energy efficiency of a data center according to an embodiment of the present invention.
First, a user may log into a query interface and determine a query bureau.
Then, static data and dynamic data of the machine room are obtained, and process data are calculated based on the static data and the dynamic data.
Then, a PUE is calculated based on the process data and a determination is made whether the PUE exceeds a PUE threshold.
If not, outputting a health mark; if so, outputting the sub-health identification.
The query results are then displayed based on the health indicator/sub-health indicator, and the process data.
After the query result is displayed, the user can refresh a query interface; and if the refreshing time exceeds the preset time length, re-determining the query station. And if the preset time length is not exceeded, continuing to display the query result.
In the embodiment of the invention, historical monitoring information aiming at a plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment are obtained; according to the historical monitoring data and the historical environmental information, energy consumption information of each electric device in a preset time period is predicted; calculating a predicted PUE according to energy consumption information of each electric device in a preset time period; when the predicted PUE exceeds a PUE threshold value, obtaining predicted environment information aiming at a preset time period, and determining a target energy-saving and energy-consumption strategy aiming at a plurality of electric equipment under the predicted environment information; and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period. By the embodiment of the invention, when the PUE of the data center possibly exceeds the preset value, the control on each electric device of the data center is realized, so that the PUE of the data center is prevented from exceeding the preset value; thus, the energy efficiency of the data center is improved.
In addition, when an inquiry request is received, first monitoring information aiming at the plurality of electric equipment in the previous time period is obtained; determining a target PUE according to the first monitoring information; when the target PUE exceeds a PUE threshold value, displaying a first identifier and first monitoring information; and when the target PUE does not exceed the PUE threshold value, displaying the second identification and the first monitoring information. Through the embodiment of the invention, the presentation of the energy consumption of the data center is realized.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those of skill in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the embodiments of the invention.
Referring to fig. 7, a schematic structural diagram of a management apparatus of a data center according to an embodiment of the present invention is shown, where the data center is deployed with a plurality of electric devices;
specifically, the method may include the following modules:
an obtaining module 701, configured to obtain historical monitoring information for a plurality of electrical devices, and historical environment information that is associated with energy consumption of the electrical devices at corresponding time;
the prediction module 702 is configured to predict, according to the historical monitoring information and the historical environmental information, a predicted power usage efficiency PUE of the data center within a preset time period;
the policy determining module 703 is configured to, when the predicted PUE exceeds the PUE threshold, obtain predicted environment information for a preset time period, and determine a target energy saving and energy consumption policy for a plurality of electrical devices under the predicted environment information;
and the control module 704 is configured to control the multiple electric devices according to the target energy saving and energy consumption strategy in a preset time period.
In an optional embodiment of the invention, the apparatus further comprises:
the display module is used for acquiring first monitoring information aiming at the plurality of electric equipment in the previous time period when receiving the query request; determining a target PUE according to the first monitoring information; when the target PUE exceeds a PUE threshold value, displaying a first identifier and first monitoring information; and when the target PUE does not exceed the PUE threshold value, displaying the second identification and the first monitoring information.
In an optional embodiment of the invention, the apparatus further comprises:
the storage module is used for collecting second monitoring information of each piece of electric equipment in the current time period; storing the second monitoring information to a monitoring information database based on the preset measuring point codes;
a display module comprising:
and the first monitoring information acquisition submodule is used for acquiring the first monitoring information from the monitoring information database according to the target measuring point code corresponding to the first monitoring information.
In an optional embodiment of the invention, the first monitoring information comprises at least one of: active power, active power degree, heating and ventilation data.
In an alternative embodiment of the present invention, the prediction module 702 includes:
the energy consumption prediction submodule is used for predicting the energy consumption information of each electric device in a preset time period according to the historical monitoring data and the historical environment information;
and the PUE calculation sub-module is used for calculating and predicting the PUE according to the energy consumption information of each electric device in a preset time period.
In an optional embodiment of the invention, the predicted PUE comprises at least one of: a second PUE for a data center building, and a third PUE for each room in the data center.
In an alternative embodiment of the present invention, the predicted PUE is predicted from a predetermined long-short term memory network.
In the embodiment of the invention, historical monitoring information aiming at a plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment are obtained; predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information; when the predicted PUE exceeds a PUE threshold value, acquiring predicted environment information aiming at a preset time period, and determining a target energy-saving energy consumption strategy aiming at a plurality of electric equipment under the predicted environment information; and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period. By the embodiment of the invention, when the PUE of the data center possibly exceeds the preset value, the control on each electric device of the data center is realized, so that the PUE of the data center is prevented from exceeding the preset value; thus, the energy efficiency of the data center is improved.
The embodiment of the invention also provides electronic equipment, which comprises a processor, a memory and a computer program which is stored on the memory and can run on the processor, wherein when the computer program is executed by the processor, the management method of the data center is realized.
The embodiment of the invention also provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when being executed by a processor, the computer program realizes the management method of the data center.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or terminal device that comprises the element.
The above detailed description is provided for the management method, apparatus, electronic device and storage medium of a data center, and the principle and implementation of the present invention are explained by applying specific examples, and the description of the above embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A management method of a data center, wherein the data center is deployed with a plurality of electric devices, the method comprising:
acquiring historical monitoring information aiming at the plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment;
predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information;
when the predicted PUE exceeds a PUE threshold value, acquiring predicted environment information aiming at the preset time period, and determining a target energy-saving and energy-consumption strategy aiming at the plurality of electric equipment under the predicted environment information;
and controlling the plurality of electric equipment according to the target energy-saving and energy-consumption strategy in a preset time period.
2. The method of claim 1, further comprising:
when an inquiry request is received, first monitoring information aiming at the plurality of electric equipment in the previous time period is obtained;
determining a target PUE according to the first monitoring information;
when the target PUE exceeds the PUE threshold value, displaying a first identifier and the first monitoring information;
and when the target PUE does not exceed the PUE threshold value, displaying a second identifier and the first monitoring information.
3. The method of claim 2, further comprising:
collecting second monitoring information of each electric device in the current time period;
storing the second monitoring information to a monitoring information database based on a preset measuring point code;
the obtaining of the first monitoring information for the plurality of electric devices in the previous time period includes:
and acquiring the first monitoring information from the monitoring information database according to the target measuring point code corresponding to the first monitoring information.
4. The method of claim 2, wherein the first monitoring information comprises at least one of: active power, active power degrees and heating and ventilation data.
5. The method according to claim 1, wherein the predicting the power usage efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environmental information comprises:
predicting energy consumption information of each electric device in a preset time period according to the historical monitoring data and the historical environmental information;
and calculating the predicted PUE according to the energy consumption information of each electric device in a preset time period.
6. The method according to any one of claims 1 to 5,
the predicted PUE comprises at least one of: a second PUE for the data center building, and a third PUE for each room in the data center.
7. The method according to any one of claims 1 to 5,
the predicted PUE is obtained by prediction of a preset long-term and short-term memory network.
8. A management device of a data center, wherein the data center is deployed with a plurality of electric devices, the device comprises:
the acquisition module is used for acquiring historical monitoring information aiming at the plurality of electric equipment and historical environment information which has an incidence relation with the energy consumption of the electric equipment at the corresponding moment;
the prediction module is used for predicting the power utilization efficiency PUE of the data center in a preset time period according to the historical monitoring information and the historical environment information;
the strategy determining module is used for acquiring the predicted environment information aiming at the preset time period when the predicted PUE exceeds a PUE threshold value, and determining a target energy-saving and energy-consumption strategy aiming at the plurality of electric equipment under the predicted environment information;
and the control module is used for controlling the plurality of electric equipment according to the target energy-saving energy consumption strategy in a preset time period.
9. An electronic device comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, the computer program, when executed by the processor, implementing a method of managing a data center according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a method of managing a data center according to any one of claims 1 to 7.
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| CN117937522A (en) * | 2024-03-25 | 2024-04-26 | 湖北世纪森源电气集团有限公司 | Power energy-saving control method of power control cabinet, control cabinet and storage medium |
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| CN117937522A (en) * | 2024-03-25 | 2024-04-26 | 湖北世纪森源电气集团有限公司 | Power energy-saving control method of power control cabinet, control cabinet and storage medium |
| CN117937522B (en) * | 2024-03-25 | 2024-06-04 | 湖北世纪森源电气集团有限公司 | Power energy-saving control method of power control cabinet, control cabinet and storage medium |
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