A data center energy-saving optimization guidance method based on a PUE index

Abstract

The application discloses a data center energy-saving optimization guidance method based on a PUE index, and relates to the technical field of system operation energy saving; an alarm is sent for the case that the PUE index seriously deviates from a better index, and the system operation condition is screened in combination with previous data center PUE data to obtain an unreasonable operation condition of energy consumption, which is used as a basis for equipment optimization and preliminary positioning of safety accidents, and is convenient for optimization scheduling reference and use.

Description

Technical Field

[0001] This invention discloses a method relating to the field of energy-saving technology for system operation, specifically a data center energy-saving optimization guidance method based on the PUE index. Background Technology

[0002] In recent years, the growth rate of data centers in China has been rapid. Currently, the scale of data centers in China has reached 5 million standard racks, with over 2 million in operation, and a computing power of 130 EFLOPS (13 quadrillion floating-point operations per second). The number of new racks added annually in China exceeds 300,000. Power Usage Effectiveness (PUE) is an important indicator for measuring the rationality of a data center's energy consumption design and usage. PUE = Total Energy Consumption of Data Center Equipment / Energy Consumption of IT Equipment. PUE is a ratio, with a baseline of 2; the closer it is to 1, the better the energy efficiency. Although PUE is a general formula, the PUE value will not be exactly the same for different data centers, different seasons, different construction locations, and even different data center buildings within the same park. Currently, there is no perfect method to provide energy consumption optimization suggestions for data centers under different operating conditions based on the optimal PUE energy consumption index of the current data center when the PUE index is not ideal, and to issue alarms for operating conditions with severely excessive PUE. Summary of the Invention

[0003] This invention addresses the problems of existing technologies by providing a data center energy-saving optimization guidance method based on the PUE index. It issues an alarm when the PUE index deviates significantly from the historical best and optimizes the system operation by combining historical data center PUE data, serving as a basis for equipment optimization and preliminary location of security incidents.

[0004] The specific solution proposed in this invention is as follows:

[0005] This invention provides a data center energy-saving optimization guidance method based on the Power Usage Effectiveness (PUE) index. It collects and records data center energy consumption data using a data table, simultaneously recording outdoor temperature, wind speed, and PUE values. The data center energy consumption data includes high-voltage system energy consumption data, transformer system energy consumption data, air conditioning system energy consumption data, fire protection system energy consumption data, UPS system energy consumption data, IT equipment energy consumption data, and office power consumption data. The total data center energy consumption data is obtained by summing these data points.

[0006] Measure the current data center energy consumption, current outdoor temperature, and current wind speed to obtain the current total data center energy consumption and current IT equipment energy consumption data. Calculate the current PUE value and name it PUE1.

[0007] Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table.

[0008] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all high-voltage system energy consumption data entries in the data table. Then, cyclically compare the high-voltage system energy consumption data corresponding to PUE1 with the high-voltage system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding high-voltage system energy consumption data entry.

[0009] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data entries in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding transformer system energy consumption data entry.

[0010] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data entries in the data table. Then, cyclically compare the air conditioning system energy consumption data corresponding to PUE1 with the air conditioning system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding air conditioning system energy consumption data entry.

[0011] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data entries in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding fire system energy consumption data entry.

[0012] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data entries in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding UPS system energy consumption data entry.

[0013] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data entries in the data table. Then, iteratively compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding office power consumption data entry.

[0014] When the alarm displays PUE1>PUE2+0.2 or PUE1>1.5, it also displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatching.

[0015] Furthermore, in the aforementioned data center energy-saving optimization guidance method based on the PUE index, data center energy consumption data is collected and recorded using a data table at set intervals, while outdoor temperature, wind speed, and PUE value are also recorded accordingly.

[0016] Furthermore, the data center energy-saving optimization guidance method based on the PUE index utilizes a data table to record data center energy consumption data, and simultaneously records outdoor temperature, wind speed, and PUE values, including:

[0017] Data tables are set up with PUE, high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office power consumption as the meter headers respectively.

[0018] Set the key fields for the data table, including the PUE value field (PUE_Value), outdoor temperature (Outdoor_Temp), wind speed (Wind_Speed), and total IT equipment energy consumption data (IT_Consum).

[0019] Furthermore, the method for guiding data center energy-saving optimization based on the PUE index, which involves querying historical PUE values ​​from a data table based on current outdoor temperature, current wind speed, and current data center energy consumption data including IT equipment energy consumption data, includes:

[0020] If no PUE value is found, update the data center energy consumption data, outdoor temperature, and wind speed in the data table. Collect and record the data center energy consumption data according to the set intervals, and record the outdoor temperature, wind speed, and PUE value accordingly.

[0021] Furthermore, the method for guiding data center energy-saving optimization based on PUE index, which involves determining whether PUE1 > PUE2 + 0.2 or PUE1 > 1.5, includes:

[0022] If PUE2 > PUE1, update the data center energy consumption data, outdoor temperature, and wind speed in the data table. Continue to collect and record data center energy consumption data using the data table according to the set interval, and record the outdoor temperature, wind speed, and PUE value accordingly.

[0023] This invention also provides a data center energy-saving optimization guidance system based on the PUE index, including a data acquisition module, a storage module, a computation and analysis module, and an alarm module.

[0024] The data acquisition module collects data on data center energy consumption, and the storage module records this data using a data table. It also records corresponding outdoor temperature, wind speed, and PUE values. The data center energy consumption data includes high-voltage system energy consumption, transformer system energy consumption, air conditioning system energy consumption, fire protection system energy consumption, UPS system energy consumption, IT equipment energy consumption, and office power consumption. The total data center energy consumption is obtained by summing these data points.

[0025] The computational analysis module obtains the current total energy consumption data of the data center and the current energy consumption data of IT equipment by measuring the current energy consumption data of the data center, the current outdoor temperature, and the current wind speed, and calculates the current PUE value, named PUE1.

[0026] Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table.

[0027] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, all high-voltage system energy consumption data entries in the data table are queried. The energy consumption data of the high-voltage system corresponding to PUE1 is compared cyclically with the energy consumption data of the high-voltage system corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding high-voltage system energy consumption data entry.

[0028] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data entries in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding transformer system energy consumption data entry.

[0029] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data entries in the data table. Then, compare the energy consumption data of the air conditioning system corresponding to PUE1 with the energy consumption data of the air conditioning system corresponding to the maximum PUE value, checking if the difference is greater than 10%. If so, the storage module records the corresponding air conditioning system energy consumption data entry.

[0030] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data entries in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding fire system energy consumption data entry.

[0031] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data entries in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding UPS system energy consumption data entry.

[0032] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data entries in the data table. Then, compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value, checking if the difference is greater than 10%. If so, the storage module records the corresponding office power consumption data entry.

[0033] The alarm module displays PUE1 when PUE1>PUE2+0.2 or PUE1>1.5, and displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatch when PUE1>1.5.

[0034] Furthermore, in the data center energy-saving optimization guidance system based on the PUE index, the acquisition module collects data tables at set intervals to record data center energy consumption data, and the storage module uses the data tables to record data center energy consumption data, while also recording outdoor temperature, wind speed and PUE value.

[0035] Furthermore, in the aforementioned data center energy-saving optimization guidance system based on PUE, the storage module records data center energy consumption data using a data table, and simultaneously records outdoor temperature, wind speed, and PUE values, including:

[0036] Data tables are set up with PUE, high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office power consumption as the meter headers respectively.

[0037] Set the key fields for the data table, including the PUE value field (PUE_Value), outdoor temperature (Outdoor_Temp), wind speed (Wind_Speed), and total IT equipment energy consumption data (IT_Consum).

[0038] Furthermore, in the data center energy-saving optimization guidance system based on the PUE index, the calculation and analysis module queries the data table for past PUE values ​​based on the current outdoor temperature, current wind speed, and IT equipment energy consumption data in the current data center energy consumption data, including:

[0039] If no PUE value is found, the storage module updates the data center energy consumption data, outdoor temperature, and wind speed in the data table. The acquisition module collects data center energy consumption data at the set intervals. The storage module records the data center energy consumption data in the data table, and also records the outdoor temperature, wind speed, and PUE value accordingly.

[0040] Furthermore, in the aforementioned data center energy-saving optimization guidance system based on the PUE index, the calculation and analysis module determines whether PUE1 > PUE2 + 0.2 or PUE1 > 1.5, including:

[0041] If PUE2 > PUE1, the storage module updates the data center energy consumption data, outdoor temperature, and wind speed in the data table. The acquisition module continues to collect data center energy consumption data at the set intervals. The storage module records the data center energy consumption data using the data table, and also records the outdoor temperature, wind speed, and PUE value accordingly.

[0042] The advantages of this invention are:

[0043] This invention provides a data center energy-saving optimization guidance method based on the Power Usage Effectiveness (PUE) index. It issues an alarm when the PUE index deviates significantly from the optimal index, and filters the system operation status by combining it with previous data center PUE data to obtain the operation status of unreasonable energy consumption. This serves as a basis for equipment optimization and preliminary location of safety incidents, facilitating optimization scheduling reference and use. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0047] This invention provides a data center energy-saving optimization guidance method based on the Power Usage Effectiveness (PUE) index. It collects and records data center energy consumption data using a data table, simultaneously recording outdoor temperature, wind speed, and PUE values. The data center energy consumption data includes high-voltage system energy consumption data, transformer system energy consumption data, air conditioning system energy consumption data, fire protection system energy consumption data, UPS system energy consumption data, IT equipment energy consumption data, and office power consumption data. The total data center energy consumption data is obtained by summing these data points.

[0048] Measure the current data center energy consumption, current outdoor temperature, and current wind speed to obtain the current total data center energy consumption and current IT equipment energy consumption data. Calculate the current PUE value and name it PUE1.

[0049] Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table.

[0050] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all high-voltage system energy consumption data entries in the data table. Then, cyclically compare the high-voltage system energy consumption data corresponding to PUE1 with the high-voltage system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding high-voltage system energy consumption data entry.

[0051] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data entries in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding transformer system energy consumption data entry.

[0052] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data entries in the data table. Then, cyclically compare the air conditioning system energy consumption data corresponding to PUE1 with the air conditioning system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding air conditioning system energy consumption data entry.

[0053] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data entries in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding fire system energy consumption data entry.

[0054] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data entries in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding UPS system energy consumption data entry.

[0055] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data entries in the data table. Then, iteratively compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding office power consumption data entry.

[0056] When the alarm displays PUE1>PUE2+0.2 or PUE1>1.5, it also displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatching.

[0057] The method of this invention uses comparison calculation rules to calculate PUE and find equipment status. It can filter data center energy consumption and perform fault analysis on sudden abnormal PUE indicators, which facilitates scheduling and handling.

[0058] In specific applications, in some embodiments of the method of the present invention, the following process can be used as a reference to provide guidance for data center energy-saving optimization.

[0059] Data tables are used to record data center energy consumption, along with corresponding records of outdoor temperature, wind speed, and PUE values, including:

[0060] Data tables are set up with PUE, high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office power consumption as the meter headers respectively.

[0061] Set the key fields for the data table, including the PUE value field (PUE_Value), outdoor temperature (Outdoor_Temp), wind speed (Wind_Speed), and total IT equipment energy consumption data (IT_Consum).

[0062] Furthermore, the PUE value field is PUE_Value, outdoor temperature is Outdoor_Temp, wind speed is Wind_Speed, last total energy consumption is Old_energy_Consum, last total IT equipment energy consumption is Old_IT_Consum, position is Position, power consumption is Power_Consum, total IT equipment power is IT_Consum, and the wind speed value is the actual measured value rounded down.

[0063] The header of the energy consumption dictionary table TABLE0 is [Old_energy_Consum, Old_IT_Consum];

[0064] The PUE table is the header of TABLE1 [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum];

[0065] The high-voltage system table has the header [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum] of TABLE2;

[0066] The transformer system table has the header [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum] of TABLE3;

[0067] The air conditioning system table has the header [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum] of TABLE4;

[0068] The fire protection system table has the header [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum] of TABLE5;

[0069] The UPS system table has the header [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum] of TABLE6;

[0070] The office power consumption table has the following header: TABLE7 [PUE_Value,Outdoor_Temp,Wind_Speed,IT_Consum,Position,Power_Consum].

[0071] Data center energy consumption data is collected and recorded in a data table at set intervals, along with corresponding outdoor temperature, wind speed, and PUE values.

[0072] Measure the energy consumption data of each node, prefixing the current measurement value field with "New" and the previous measurement value field with "Old".

[0073] Total energy consumption of data center equipment = New_energy_Consum - Old_energy_Consum

[0074] Total IT equipment energy consumption = New_IT_Consum - Old_IT_Consum

[0075] New_PUE = Total energy consumption of data center equipment / Total energy consumption of IT equipment, i.e., PUE1.

[0076] Based on the current outdoor temperature, current wind speed, and current data center energy consumption data, query the previous PUE values ​​in data table 1. If no PUE value is found, update the data center energy consumption data, outdoor temperature, and wind speed in the data table. Collect and record data center energy consumption data in the data table according to the set interval, such as 15-30 minutes, and record the outdoor temperature, wind speed, and PUE values ​​accordingly.

[0077] If a PUE value is found, it is named PUE2. It is then determined whether PUE1 > PUE2 + 0.2 or PUE1 > 1.5. If PUE2 > PUE1, the data center energy consumption data, outdoor temperature, and wind speed in the data table are updated. The data center energy consumption data is collected and recorded in the data table according to the time interval set. At the same time, the outdoor temperature, wind speed, and PUE value are recorded accordingly.

[0078] If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the maximum PUE value from the data table.

[0079] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all high-voltage system energy consumption data entries in the data table. Then, compare the high-voltage system energy consumption data corresponding to PUE1 with the high-voltage system energy consumption data corresponding to the maximum PUE value, checking if the difference exceeds 10%. The formula is as follows:

[0080] |Power_Consumi1-Power_Consumi2| / Power_Consumi2|>10%, i=1…n

[0081] Then record the corresponding high-voltage system energy consumption data entry and the position of Positioni at this time.

[0082] Based on the comparison method described above, query the status of each entry in the remaining TABLE2, TABLE3, TABLE4, TABLE5, TABLE6, and TABLE7, and record the corresponding entry and its corresponding Positioni position.

[0083] When the alarm displays PUE1>PUE2+0.2 or PUE1>1.5, it also displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatching.

[0084] When PUE1 > PUE2 + 0.2 or PUE1 > 1.5, the alarm displays PUE1 and shows the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office, as well as their corresponding Positioni, recorded when PUE1 > 1.5, for remote monitoring and dispatching.

[0085] Update the previous total energy consumption = Old_energy_Consum, and the previous total IT equipment energy consumption = Old_IT_Consum. Wait for the data collection interval to be 15-30 minutes, then continue data collection and recording.

[0086] This invention also provides a data center energy-saving optimization guidance system based on the PUE index, including a data acquisition module, a storage module, a computation and analysis module, and an alarm module.

[0087] The data acquisition module collects data on data center energy consumption, and the storage module records this data using a data table. It also records corresponding outdoor temperature, wind speed, and PUE values. The data center energy consumption data includes high-voltage system energy consumption, transformer system energy consumption, air conditioning system energy consumption, fire protection system energy consumption, UPS system energy consumption, IT equipment energy consumption, and office power consumption. The total data center energy consumption is obtained by summing these data points.

[0088] The computational analysis module obtains the current total energy consumption data of the data center and the current energy consumption data of IT equipment by measuring the current energy consumption data of the data center, the current outdoor temperature, and the current wind speed, and calculates the current PUE value, named PUE1.

[0089] Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table.

[0090] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, all high-voltage system energy consumption data entries in the data table are queried. The energy consumption data of the high-voltage system corresponding to PUE1 is compared cyclically with the energy consumption data of the high-voltage system corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding high-voltage system energy consumption data entry.

[0091] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding transformer system energy consumption data entry.

[0092] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data in the data table. Then, cyclically compare the air conditioning system energy consumption data corresponding to PUE1 with the air conditioning system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding air conditioning system energy consumption data entry.

[0093] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding fire system energy consumption data entry.

[0094] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding UPS system energy consumption data entry.

[0095] Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data in the data table. Then, compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value, checking if the difference is greater than 10%. If so, the storage module records the corresponding office power consumption data entry.

[0096] The alarm module displays PUE1 when PUE1>PUE2+0.2 or PUE1>1.5, and displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatch when PUE1>1.5.

[0097] The information interaction and execution process of the various modules in the above system are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0098] Similarly, the system of the present invention can issue an alarm when the PUE index deviates significantly from the optimal index, and filter the system operation status by combining previous data center PUE data to obtain the operation status of unreasonable energy consumption, which can serve as the basis for equipment optimization and preliminary location of safety accidents, and facilitate optimization scheduling reference and use.

[0099] It should be noted that not all steps and modules in the above processes and system structures are mandatory; some steps or modules can be omitted as needed. The execution order of the steps is not fixed and can be adjusted as required. The system structures described in the above embodiments can be physical or logical structures. That is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or they may be implemented by certain components in multiple independent devices.

[0100] The embodiments described above are merely preferred embodiments for fully illustrating the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. The scope of protection of the present invention is defined by the claims.

Claims

1. A data center energy-saving optimization guidance method based on PUE index, characterized by: Data center energy consumption data is collected and recorded using data tables, along with corresponding outdoor temperature, wind speed, and PUE values. This data center energy consumption data includes high-voltage system energy consumption, transformer system energy consumption, air conditioning system energy consumption, fire protection system energy consumption, UPS system energy consumption, IT equipment energy consumption, and office power consumption. The total data center energy consumption data is obtained by summing these data points. Measure the current data center energy consumption, current outdoor temperature, and current wind speed to obtain the current total data center energy consumption and current IT equipment energy consumption data. Calculate the current PUE value and name it PUE1. Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.

5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all high-voltage system energy consumption data entries in the data table. Then, cyclically compare the high-voltage system energy consumption data corresponding to PUE1 with the high-voltage system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding high-voltage system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data entries in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding transformer system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data entries in the data table. Then, cyclically compare the air conditioning system energy consumption data corresponding to PUE1 with the air conditioning system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding air conditioning system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data entries in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding fire system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data entries in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding UPS system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data entries in the data table. Then, iteratively compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, record the corresponding office power consumption data entry. When the alarm displays PUE1>PUE2+0.2 or PUE1>1.5, it also displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatching.

2. The data center energy-saving optimization guidance method based on PUE index according to claim 1, characterized in that: Data center energy consumption data is collected and recorded in a data table at set intervals, along with corresponding outdoor temperature, wind speed, and PUE values.

3. The data center energy-saving optimization guidance method based on PUE index according to claim 1, characterized in that: Data tables are used to record data center energy consumption, along with corresponding records of outdoor temperature, wind speed, and PUE values, including: Data tables are set up with PUE, high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office power consumption as the meter headers respectively. Set the key fields for the data table, including the PUE value field (PUE_Value), outdoor temperature (Outdoor_Temp), wind speed (Wind_Speed), and total IT equipment energy consumption data (IT_Consum).

4. The data center energy-saving optimization guidance method based on PUE index according to claim 1, characterized in that: The step of querying historical PUE values ​​from a data table based on current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data) includes: If no PUE value is found, update the data center energy consumption data, outdoor temperature, and wind speed in the data table. Collect and record the data center energy consumption data according to the set intervals, and record the outdoor temperature, wind speed, and PUE value accordingly.

5. A data center energy-saving optimization guidance method based on PUE index according to claim 1, characterized in that: The determination of whether PUE1 > PUE2 + 0.2 or PUE1 > 1.5 includes: If PUE2 > PUE1, update the data center energy consumption data, outdoor temperature, and wind speed in the data table. Continue to collect and record data center energy consumption data using the data table according to the set interval, and record the outdoor temperature, wind speed, and PUE value accordingly.

6. A data center energy-saving optimization guidance system based on the PUE index, characterized in that: It includes a data acquisition module, a storage module, a data processing and analysis module, and an alarm module. The data acquisition module collects data on data center energy consumption, and the storage module records this data using a data table. It also records corresponding outdoor temperature, wind speed, and PUE values. The data center energy consumption data includes high-voltage system energy consumption, transformer system energy consumption, air conditioning system energy consumption, fire protection system energy consumption, UPS system energy consumption, IT equipment energy consumption, and office power consumption. The total data center energy consumption is obtained by summing these data points. The computational analysis module obtains the current total energy consumption data of the data center and the current energy consumption data of IT equipment by measuring the current energy consumption data of the data center, the current outdoor temperature, and the current wind speed, and calculates the current PUE value, named PUE1. Based on the current outdoor temperature, current wind speed, and current data center energy consumption data (IT equipment energy consumption data), query the historical PUE values ​​in the data table. If a PUE value is found, name it PUE2. Determine if PUE1 > PUE2 + 0.2 or PUE1 > 1.

5. If PUE1 > 1.5, retrieve the outdoor temperature and wind speed corresponding to the highest PUE value in the data table. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, all high-voltage system energy consumption data entries in the data table are queried. The energy consumption data of the high-voltage system corresponding to PUE1 is compared cyclically with the energy consumption data of the high-voltage system corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding high-voltage system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all transformer system energy consumption data entries in the data table. Then, cyclically compare the transformer system energy consumption data corresponding to PUE1 with the transformer system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding transformer system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all air conditioning system energy consumption data entries in the data table. Then, compare the energy consumption data of the air conditioning system corresponding to PUE1 with the energy consumption data of the air conditioning system corresponding to the maximum PUE value, checking if the difference is greater than 10%. If so, the storage module records the corresponding air conditioning system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all fire system energy consumption data entries in the data table. Then, cyclically compare the fire system energy consumption data corresponding to PUE1 with the fire system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding fire system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all UPS system energy consumption data entries in the data table. Then, cyclically compare the UPS system energy consumption data corresponding to PUE1 with the UPS system energy consumption data corresponding to the maximum PUE value. If the difference is greater than 10%, the storage module records the corresponding UPS system energy consumption data entry. Based on the outdoor temperature and wind speed corresponding to the maximum PUE value, query all office power consumption data entries in the data table. Then, compare the office power consumption data corresponding to PUE1 with the office power consumption data corresponding to the maximum PUE value, checking if the difference is greater than 10%. If so, the storage module records the corresponding office power consumption data entry. The alarm module displays PUE1 when PUE1>PUE2+0.2 or PUE1>1.5, and displays the energy consumption data entries of the high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office for remote monitoring and dispatch when PUE1>1.

5.

7. A data center energy-saving optimization guidance system based on PUE index according to claim 5, characterized in that: The data acquisition module collects and records the data center's energy consumption data at set intervals. The storage module uses the data table to record the data center's energy consumption data, and also records the outdoor temperature, wind speed, and PUE value.

8. A data center energy-saving optimization guidance system based on PUE index according to claim 6, characterized in that: The storage module uses a data table to record data center energy consumption data, and also records outdoor temperature, wind speed, and PUE values, including: Data tables are set up with PUE, high-voltage system, transformer system, air conditioning system, fire protection system, UPS system, and office power consumption as the meter headers respectively. Set the key fields for the data table, including the PUE value field (PUE_Value), outdoor temperature (Outdoor_Temp), wind speed (Wind_Speed), and total IT equipment energy consumption data (IT_Consum).

9. A data center energy-saving optimization guidance system based on PUE index according to claim 6, characterized in that: The computational analysis module queries historical PUE values ​​from the data table based on the current outdoor temperature, current wind speed, and IT equipment energy consumption data in the current data center energy consumption data, including: If no PUE value is found, the storage module updates the data center energy consumption data, outdoor temperature, and wind speed in the data table. The acquisition module collects data center energy consumption data at the set intervals. The storage module records the data center energy consumption data in the data table, and also records the outdoor temperature, wind speed, and PUE value accordingly.

10. A data center energy-saving optimization guidance system based on PUE index according to claim 6, characterized in that: The calculation and analysis module determines whether PUE1 > PUE2 + 0.2 or PUE1 > 1.5, including: If PUE2 > PUE1, the storage module updates the data center energy consumption data, outdoor temperature, and wind speed in the data table. The acquisition module continues to collect data center energy consumption data at the set intervals. The storage module records the data center energy consumption data using the data table, and also records the outdoor temperature, wind speed, and PUE value accordingly.

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