CN117669260A - Data center demand response strategy calculation method, device, equipment and storage medium - Google Patents
Data center demand response strategy calculation method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN117669260A CN117669260A CN202311832679.6A CN202311832679A CN117669260A CN 117669260 A CN117669260 A CN 117669260A CN 202311832679 A CN202311832679 A CN 202311832679A CN 117669260 A CN117669260 A CN 117669260A
- Authority
- CN
- China
- Prior art keywords
- data center
- demand response
- energy storage
- load
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000004044 response Effects 0.000 title claims abstract description 108
- 238000004364 calculation method Methods 0.000 title claims abstract description 26
- 238000003860 storage Methods 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 125
- 230000008878 coupling Effects 0.000 claims abstract description 19
- 238000010168 coupling process Methods 0.000 claims abstract description 19
- 238000005859 coupling reaction Methods 0.000 claims abstract description 19
- 238000004378 air conditioning Methods 0.000 claims abstract description 7
- 238000004146 energy storage Methods 0.000 claims description 74
- 230000008569 process Effects 0.000 claims description 54
- 238000005057 refrigeration Methods 0.000 claims description 25
- 238000012545 processing Methods 0.000 claims description 19
- 238000007599 discharging Methods 0.000 claims description 16
- 238000004519 manufacturing process Methods 0.000 claims description 11
- 238000001816 cooling Methods 0.000 claims description 10
- 230000005611 electricity Effects 0.000 claims description 10
- 239000013307 optical fiber Substances 0.000 claims description 7
- 230000032683 aging Effects 0.000 claims description 5
- 238000005338 heat storage Methods 0.000 claims description 5
- 238000012886 linear function Methods 0.000 claims description 5
- 238000010248 power generation Methods 0.000 claims description 5
- 230000003287 optical effect Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a data center demand response strategy calculation method, a device, equipment and a storage medium, and relates to the technical field of electric power, wherein the method comprises the following steps: receiving a data center parameter set, and inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment; inputting the price type demand response into a data center energy supply model based on the price type demand response to obtain a data center demand response model; and solving the data center demand response model to obtain a data center demand response strategy.
Description
Technical Field
The present invention relates to the field of power technologies, and in particular, to a data center demand response policy calculation method, apparatus, device, and storage medium.
Background
With the development of technologies such as 5G, big data and the like, a data center has become one of main power loads in China. As an emerging load with huge volume and rapid growth, the method has great significance in fully mining the adjustment potential of the load of the data center. However, common data center demand response strategies that utilize a single load regulation approach cannot fully exploit their regulatory potential.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a data center demand response strategy calculation method.
In a first aspect, the present invention provides a data center demand response policy calculation method, including:
receiving a data center parameter set, and inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment;
inputting the price type demand response into a data center energy supply model based on the price type demand response to obtain a data center demand response model;
and solving the data center demand response model to obtain a data center demand response strategy.
Preferably, the data center power consumption model includes: IT device power consumption, refrigeration system power consumption, and other devices, wherein,
the IT equipment power consumption comprises power consumption generated by processing delay tolerant load and power consumption generated by processing delay sensitive load, and the power consumption can be obtained by needing data center auxiliary equipment parameters in a data center parameter set, and the formula is as follows:
in the method, in the process of the invention,respectively representing delay sensitive type load quantity and delay tolerant type load quantity which need to be processed at the moment t; />The no-load and rated power of each server in the data center are respectively; u (u) i Is the average utilization rate of the data center server; />Respectively representing the running number of servers of the data center for processing the delay-sensitive load and the running number of servers of the delay-tolerant load;
the refrigeration system power consumption is simplified into a linear function only about refrigeration capacity according to the law of conservation of energy, and the refrigeration system power consumption can be obtained only by data center auxiliary equipment parameters in a data center parameter set:
wherein b is 1i 、b 2i H is an empirical parameter in a cooling system power consumption model it In order to achieve the aim of refrigerating the air,for refrigerating system power consumption>Maximum power consumption of the refrigeration system;
the other devices include lighting systems that require data center auxiliary device parameters in a data center parameter set to be obtained, which is reduced to a constant
The data center parameter set is input into a pre-established data center power consumption model, and a data center energy supply model is obtained:
in the method, in the process of the invention,total power consumption of data center, < >>Supplying power to the mains, ">For wind turbine power, < >> Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
Preferably: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval,respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
Preferably, the data center demand response model is as follows:
under the condition of considering the economic cost of load adjustment, the economic cost of the data center in the whole dispatching period is the lowest as the optimal target:
wherein, gamma it The electricity price at the time t is the electricity price,for the total cost of load regulation, < >>To adjust the cost for delay-sensitive loads, +.>Cost for operating the energy storage system->The energy production cost of the conventional generator set is realized;
according to the optimal goal of minimizing the economic cost of the data center in the whole dispatching period, wherein the total cost of load adjustment comprises the optical fiber interface loss, the data dispatching cost, the energy storage loss cost generated by dispatching the delay sensitive load in space and the energy production cost generated by self-provided conventional generator sets:
in the method, in the process of the invention,indicating the delay-sensitive load quantity to be processed before participating in demand response at time t,/>Representing delay-sensitive load unit scheduling cost, +.>Representing the unit ageing cost of the energy storage system, < >>Representing the unit power generation cost of a conventional generator set;
the solving process of the data center demand response model is as follows:
when solving the data center demand response model, the data load balance constraint on the spatial scale, the data load scheduling constraint on the time scale, the heat storage constraint by using building thermal inertia, the user service quality requirement constraint and the auxiliary equipment constraint energy supply balance constraint need to be satisfied:
in the method, in the process of the invention,delay-sensitive load to reach the data center operator front-end server for time t;
wherein D is the maximum delay time of the delay tolerant load, φ it The delay tolerant load quantity which needs to be processed before the participation of the demand response at the moment t is represented;
in the method, in the process of the invention,indicating the indoor temperature of the data center at time t +.>Indicating the outdoor temperature of the data center at time T, T i I0 Indicating the indoor temperature of the data center at the initial time, b 3i 、b 4i T is the equivalent thermal resistance and the equivalent heat capacity of the cooling system i Imax 、T i Imin Representing upper and lower allowable indoor temperature limits of the data center;
in the formula, v I Representing the delay bound of the delay-sensitive load,for handling delay-sensitive load total number of servers, < >>The total number of servers to handle delay tolerant load;
in the method, in the process of the invention,supplying power to the mains, ">For wind turbine power, < >>Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
In a second aspect, the present invention also discloses a data center demand response policy calculation device, including:
and a data receiving module: the method comprises the steps of receiving a data center parameter set, inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises the following components: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment;
a demand response module: the price type demand response module is used for inputting the price type demand response into the data center energy supply model based on the price type demand response to obtain a data center demand response model;
and a data solving module: and the method is used for solving the data center demand response model to obtain a data center demand response strategy.
Preferably, the data center power consumption model includes: IT device power consumption, refrigeration system power consumption, and other devices, wherein,
the IT equipment power consumption comprises power consumption generated by processing delay tolerant load and power consumption generated by processing delay sensitive load, and the power consumption can be obtained by needing data center auxiliary equipment parameters in a data center parameter set, and the formula is as follows:
in the method, in the process of the invention,respectively representing delay sensitive type load quantity and delay tolerant type load quantity which need to be processed at the moment t; />The no-load and rated power of each server in the data center are respectively; u (u) i Is the average utilization rate of the data center server; />Representing data centers separately forThe number of server operations to handle delay-sensitive loads and the number of server operations to handle delay-tolerant loads;
the refrigeration system power consumption is simplified into a linear function only about refrigeration capacity according to the law of conservation of energy, and the refrigeration system power consumption can be obtained only by data center auxiliary equipment parameters in a data center parameter set:
wherein b is 1i 、b 2i H is an empirical parameter in a cooling system power consumption model it In order to achieve the aim of refrigerating the air,for refrigerating system power consumption>Maximum power consumption of the refrigeration system;
the other devices include lighting systems that require data center auxiliary device parameters in a data center parameter set to be obtained, which is reduced to a constant
The data center parameter set is input into a pre-established data center power consumption model, and a data center energy supply model is obtained:
in the method, in the process of the invention,total power consumption of data center, < >>Supplying power to the mains, ">For wind turbine power, < >> Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
Preferably, the data center energy supply model includes: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval,respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
Preferably, the data center demand response model is as follows:
under the condition of considering the economic cost of load adjustment, the economic cost of the data center in the whole dispatching period is the lowest as the optimal target:
wherein, gamma it The electricity price at the time t is the electricity price,for the total cost of load regulation, < >>To adjust the cost for delay-sensitive loads, +.>Cost for operating the energy storage system->The energy production cost of the conventional generator set is realized;
according to the optimal goal of minimizing the economic cost of the data center in the whole dispatching period, wherein the total cost of load adjustment comprises the optical fiber interface loss, the data dispatching cost, the energy storage loss cost generated by dispatching the delay sensitive load in space and the energy production cost generated by self-provided conventional generator sets:
in the method, in the process of the invention,indicating the delay-sensitive load quantity to be processed before participating in demand response at time t,/>Representing delay-sensitive load unit scheduling costs，/>Representing the unit ageing cost of the energy storage system, < >>Representing the unit power generation cost of a conventional generator set;
the solving process of the data center demand response model is as follows:
when solving the data center demand response model, the data load balance constraint on the spatial scale, the data load scheduling constraint on the time scale, the heat storage constraint by using building thermal inertia, the user service quality requirement constraint and the auxiliary equipment constraint energy supply balance constraint need to be satisfied:
in the method, in the process of the invention,delay-sensitive load to reach the data center operator front-end server for time t;
wherein D is the maximum delay time of the delay tolerant load, φ it The delay tolerant load quantity which needs to be processed before the participation of the demand response at the moment t is represented;
in the method, in the process of the invention,indicating the indoor temperature of the data center at time t +.>Indicating the outdoor temperature of the data center at time T, T i I0 Indicating the indoor temperature of the data center at the initial time, b 3i 、b 4i T is the equivalent thermal resistance and the equivalent heat capacity of the cooling system i Imax 、T i Imin Representing upper and lower allowable indoor temperature limits of the data center;
in the formula, v I Representing the delay bound of the delay-sensitive load,for handling delay-sensitive load total number of servers, < >>The total number of servers to handle delay tolerant load;
in the method, in the process of the invention,supplying power to the mains, ">For wind turbine power, < >>Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
The invention relates to a data center demand response strategy computing device considering various coupling load adjustment means, which comprises:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods described above.
The storage medium of the present invention containing computer-executable instructions for performing the above-described method when executed by a computer processor.
The beneficial effects are that: inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, inputting price type demand response into the data center energy supply model based on price type demand response to obtain a data center demand response model, and obtaining a data center demand response strategy by solving the data center demand response model. Compared with the prior art, the method has the remarkable advantages that: the invention adopts the optimization method to realize the balance between the cost of the data center and the service quality of the user, so that the running cost of the data center can be minimized, and the service quality requirement of the corresponding user can be met.
Drawings
FIG. 1 is a flow chart of a method for calculating a demand response strategy of a data center according to an embodiment of the present invention, which considers various coupling load adjustment means;
FIG. 2 is a schematic diagram of a data center demand response policy calculation device according to a second embodiment of the present invention, which considers various coupling load adjustment means;
fig. 3 is a schematic structural diagram of a data center demand response policy computing device according to a third embodiment of the present invention, in which multiple coupling load adjustment means are considered.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a data center demand response strategy calculation method, a data center demand response strategy calculation device, data center demand response strategy calculation equipment and a data center demand response strategy storage medium taking various coupling load adjustment means into consideration. Firstly, constructing a data center power consumption model comprising IT equipment, a refrigerating system, other equipment and the like; secondly, constructing a data center energy supply model comprising a wind turbine generator, a conventional generator set, energy storage equipment and the like; and finally, constructing a data center demand response model based on the price type demand response, and providing reference for formulating a data center demand response strategy.
Example 1
The following describes in detail a data center demand response policy calculation method taking into account various coupling load adjustment means provided by the embodiment of the present invention. FIG. 1 is a flow chart of a data center demand response strategy calculation method calculation taking into account a plurality of coupled load adjustment means, as shown in FIG. 1, the method may include:
s1, receiving a data center parameter set, and inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relationships of equipment in the data center, and operating characteristics of data center IT equipment and air conditioning equipment.
The data center power consumption model includes: IT device power consumption, refrigeration system power consumption, and other devices, wherein,
the IT equipment power consumption comprises power consumption generated by processing delay tolerant load and power consumption generated by processing delay sensitive load, and the power consumption can be obtained by needing data center auxiliary equipment parameters in a data center parameter set, and the formula is as follows:
in the method, in the process of the invention,respectively representing delay sensitive type load quantity and delay tolerant type load quantity which need to be processed at the moment t; />The no-load and rated power of each server in the data center are respectively; u (u) i Is the average utilization rate of the data center server; />Respectively representing the running number of servers of the data center for processing the delay-sensitive load and the running number of servers of the delay-tolerant load;
the refrigeration system power consumption is simplified into a linear function only about refrigeration capacity according to the law of conservation of energy, and the refrigeration system power consumption can be obtained only by data center auxiliary equipment parameters in a data center parameter set:
wherein b is 1i 、b 2i H is an empirical parameter in a cooling system power consumption model it In order to achieve the aim of refrigerating the air,for refrigerating system power consumption>Maximum power consumption of the refrigeration system;
the other devices include lighting systems that require data center auxiliary device parameters in a data center parameter set to be obtained, which is reduced to a constant
The data center parameter set is input into a pre-established data center power consumption model, and a data center energy supply model is obtained:
in the method, in the process of the invention,total power consumption of data center, < >>Supplying power to the mains, ">For wind turbine power, < >> Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
S2, inputting the price type demand response into the data center energy supply model based on the price type demand response to obtain a data center demand response model.
The data center energy model includes: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval,respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
And S3, solving a data center demand response model to obtain a data center demand response strategy.
The data center demand response model is as follows:
under the condition of considering the economic cost of load adjustment, the economic cost of the data center in the whole dispatching period is the lowest as the optimal target:
wherein, gamma it The electricity price at the time t is the electricity price,for the total cost of load regulation, < >>To adjust the cost for delay-sensitive loads, +.>Cost for operating the energy storage system->The energy production cost of the conventional generator set is realized;
according to the optimal goal of minimizing the economic cost of the data center in the whole dispatching period, wherein the total cost of load adjustment comprises the optical fiber interface loss, the data dispatching cost, the energy storage loss cost generated by dispatching the delay sensitive load in space and the energy production cost generated by self-provided conventional generator sets:
in the method, in the process of the invention,indicating the delay-sensitive load quantity to be processed before participating in demand response at time t,/>Representing delay-sensitive load unit scheduling cost, +.>Indicating the unit aging of the energy storage systemThis, ->Representing the unit power generation cost of a conventional generator set;
the solving process of the data center demand response model is as follows:
when solving the data center demand response model, the data load balance constraint on the spatial scale, the data load scheduling constraint on the time scale, the heat storage constraint by using building thermal inertia, the user service quality requirement constraint and the auxiliary equipment constraint energy supply balance constraint need to be satisfied:
in the method, in the process of the invention,delay-sensitive load to reach the data center operator front-end server for time t;
wherein D is the maximum delay time of the delay tolerant load, φ it The delay tolerant load quantity which needs to be processed before the participation of the demand response at the moment t is represented;
in the method, in the process of the invention,indicating the indoor temperature of the data center at time t +.>Indicating the outdoor temperature of the data center at time T, T i I0 Indicating the indoor temperature of the data center at the initial time, b 3i 、b 4i T is the equivalent thermal resistance and the equivalent heat capacity of the cooling system i Imax 、T i Imin Representing upper and lower allowable indoor temperature limits of the data center;
in the formula, v I Representing the delay bound of the delay-sensitive load,for handling delay-sensitive load total number of servers, < >>The total number of servers to handle delay tolerant load;
in the method, in the process of the invention,supplying power to the mains, ">For wind turbine power, < >>Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
Example two
Fig. 2 is a schematic diagram of a data center demand response policy calculation device according to a second embodiment of the present invention, which considers various coupling load adjustment means. The device can be implemented in a software and/or hardware manner, and can be configured in a terminal device. The device comprises:
and a data receiving module: the method comprises the steps of receiving a data center parameter set, inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises the following components: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment;
a demand response module: the price type demand response module is used for inputting the price type demand response into the data center energy supply model based on the price type demand response to obtain a data center demand response model;
and a data solving module: and the method is used for solving the data center demand response model to obtain a data center demand response strategy.
The data center power consumption model includes: IT device power consumption, refrigeration system power consumption, and other devices, wherein,
the IT equipment power consumption comprises power consumption generated by processing delay tolerant load and power consumption generated by processing delay sensitive load, and the power consumption can be obtained by needing data center auxiliary equipment parameters in a data center parameter set, and the formula is as follows:
in the method, in the process of the invention,respectively representing delay sensitive type load quantity and delay tolerant type load quantity which need to be processed at the moment t; />The no-load and rated power of each server in the data center are respectively; u (u) i Is the average utilization rate of the data center server; />Respectively representing the running number of servers of the data center for processing the delay-sensitive load and the running number of servers of the delay-tolerant load;
the refrigeration system power consumption is simplified into a linear function only about refrigeration capacity according to the law of conservation of energy, and the refrigeration system power consumption can be obtained only by data center auxiliary equipment parameters in a data center parameter set:
wherein b is 1i 、b 2i H is an empirical parameter in a cooling system power consumption model it In order to achieve the aim of refrigerating the air,for refrigerating system power consumption>Maximum power consumption of the refrigeration system;
the other devices include lighting systems that require data center auxiliary device parameters in a data center parameter set to be obtained, which is reduced to a constant
The data center parameter set is input into a pre-established data center power consumption model, and a data center energy supply model is obtained:
in the method, in the process of the invention,total power consumption of data center, < >>Supplying power to the mains, ">For wind turbine power, < >> Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
Preferably, the data center energy supply model includes: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval +.>Respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
Preferably, the data center demand response model is as follows:
under the condition of considering the economic cost of load adjustment, the economic cost of the data center in the whole dispatching period is the lowest as the optimal target:
wherein, gamma it The electricity price at the time t is the electricity price,for the total cost of load regulation, < >>To adjust the cost for delay-sensitive loads, +.>Cost for operating the energy storage system->The energy production cost of the conventional generator set is realized;
according to the optimal goal of minimizing the economic cost of the data center in the whole dispatching period, wherein the total cost of load adjustment comprises the optical fiber interface loss, the data dispatching cost, the energy storage loss cost generated by dispatching the delay sensitive load in space and the energy production cost generated by self-provided conventional generator sets:
in the method, in the process of the invention,indicating the delay-sensitive load quantity to be processed before participating in demand response at time t,/>Representing delay-sensitive load unit scheduling cost, +.>Representing the unit ageing cost of the energy storage system, < >>Representing the unit power generation cost of a conventional generator set;
the solving process of the data center demand response model is as follows:
when solving the data center demand response model, the data load balance constraint on the spatial scale, the data load scheduling constraint on the time scale, the heat storage constraint by using building thermal inertia, the user service quality requirement constraint and the auxiliary equipment constraint energy supply balance constraint need to be satisfied:
in the method, in the process of the invention,delay-sensitive load to reach the data center operator front-end server for time t; />
Wherein D is the maximum delay time of the delay tolerant load, φ it The delay tolerant load quantity which needs to be processed before the participation of the demand response at the moment t is represented;
in the method, in the process of the invention,indicating the indoor temperature of the data center at time t +.>Indicating the outdoor temperature of the data center at time T, T i I0 Indicating the indoor temperature of the data center at the initial time, b 3i 、b 4i T is the equivalent thermal resistance and the equivalent heat capacity of the cooling system i Imax 、T i Imin Representing upper and lower allowable indoor temperature limits of the data center;
in the formula, v I Representing the delay bound of the delay-sensitive load,for handling delay-sensitive load total number of servers, < >>The total number of servers to handle delay tolerant load;
in the method, in the process of the invention,supplying power to the mains, ">For wind turbine power, < >>Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
The device provided by the embodiment of the invention can be used for executing the method provided by the first embodiment of the invention, and has the corresponding functions and beneficial effects of executing the method.
It should be noted that, in the embodiment of the determining apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding function can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Example III
Fig. 3 is a schematic structural diagram of an apparatus according to a third embodiment of the present invention, where the third embodiment of the present invention provides services for implementing a data center demand response policy calculation method taking into account multiple coupling load adjustment means according to the first embodiment of the present invention, and the data center demand response policy calculation device taking into account multiple coupling load adjustment means according to the first embodiment of the present invention may be configured. Fig. 3 illustrates a block diagram of an exemplary device 12 suitable for use in implementing embodiments of the present invention. The device 12 shown in fig. 3 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 3, device 12 is in the form of a general purpose computing device. Components of device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects the various system components including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. Device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, commonly referred to as a "hard disk drive"). Although not shown in fig. 3, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
Device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with device 12, and/or any devices (e.g., network card, modem, etc.) that enable device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, via network adapter 20. As shown in fig. 3, network adapter 20 communicates with other modules of device 12 over bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing a data center demand response policy calculation method that takes into account various coupling load adjustment means provided by embodiments of the present invention.
By the device, reference is provided for calculating the demand response strategy of the data center by considering various coupling load adjustment means.
Example IV
The fourth embodiment of the present invention also provides a storage medium containing computer-executable instructions for performing the method of the first embodiment when executed by a computer processor.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the above method operations, but may also perform the related operations in the method for determining the data center demand response policy calculation taking into account the multiple coupling load adjustment means provided in any embodiment of the present invention.
The above disclosure is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (10)
1. The data center demand response strategy calculation method is characterized by comprising the following steps:
receiving a data center parameter set, and inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment;
inputting the price type demand response into a data center energy supply model based on the price type demand response to obtain a data center demand response model;
and solving the data center demand response model to obtain a data center demand response strategy.
2. The data center demand response policy calculation method of claim 1, wherein said data center power consumption model comprises: IT device power consumption, refrigeration system power consumption, and other devices, wherein,
the IT device power consumption comprises power consumption generated by processing delay tolerant loads and power consumption generated by processing delay sensitive loads, and the formula is as follows:
in the method, in the process of the invention,respectively representing delay sensitive type load quantity and delay tolerant type load quantity which need to be processed at the moment t;respectively as data centersThe idle and rated power of each server; u (u) i Is the average utilization rate of the data center server;respectively representing the running number of servers of the data center for processing the delay-sensitive load and the running number of servers of the delay-tolerant load;
the refrigeration system power consumption is reduced to a linear function with respect to refrigeration only according to the law of conservation of energy:
wherein b is 1i 、b 2i H is an empirical parameter in a cooling system power consumption model it In order to achieve the aim of refrigerating the air,in order for the refrigeration system to consume power,maximum power consumption of the refrigeration system;
the other device comprises a lighting system, which is expressed as a constant
3. The method for computing a data center demand response strategy according to claim 2, wherein the process of inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model comprises the following steps:
in the method, in the process of the invention,total power consumption of data center, < >>Supplying power to the mains, ">For wind turbine power, < >> Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
4. The data center demand response strategy computation method of claim 1, wherein said data center energy model comprises: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval,respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
5. The data center demand response policy calculation method of claim 1, wherein said data center demand response model is as follows:
under the condition of considering the economic cost of load adjustment, the economic cost of the data center in the whole dispatching period is the lowest as the optimal target:
wherein, gamma it The electricity price at the time t is the electricity price,for the total cost of load regulation, < >>In order to delay-sensitive load regulation costs,is an energy storage systemRunning cost->The energy production cost of the conventional generator set is realized;
the energy production cost is generated according to the optimal goal of lowest economic cost of the data center in the whole dispatching period, wherein the total cost of load adjustment comprises the optical fiber interface loss, the data dispatching cost, the energy storage loss cost generated by dispatching the delay sensitive load in space and the energy production cost generated by self-contained conventional generator sets:
in the method, in the process of the invention,indicating the delay-sensitive load quantity to be processed before participating in demand response at time t,/>Representing delay-sensitive load unit scheduling cost, +.>Representing the unit ageing cost of the energy storage system, < >>Representing the unit power generation cost of a conventional generator set.
6. The data center demand response strategy computation method of claim 1, wherein the solving process of the data center demand response model is as follows:
when solving the data center demand response model, the data load balance constraint on the spatial scale, the data load scheduling constraint on the time scale, the heat storage constraint by using building thermal inertia, the user service quality requirement constraint and the auxiliary equipment constraint energy supply balance constraint need to be satisfied:
in the method, in the process of the invention,delay-sensitive load to reach the data center operator front-end server for time t;
wherein D is the maximum delay time of the delay tolerant load, φ it The delay tolerant load quantity which needs to be processed before the participation of the demand response at the moment t is represented;
in the method, in the process of the invention,indicating the indoor temperature of the data center at time t +.>Indicating the outdoor temperature of the data center at time T, T i I0 Indicating the indoor temperature of the data center at the initial time, b 3i 、b 4i T is the equivalent thermal resistance and the equivalent heat capacity of the cooling system i Imax 、T i Imin Representing upper and lower allowable indoor temperature limits of the data center;
in the formula, v I Representing the delay bound of the delay-sensitive load,to handle the total number of servers for delay-sensitive loads,the total number of servers to handle delay tolerant load;
in the method, in the process of the invention,supplying power to the mains, ">For wind turbine power, < >>Charging and discharging power of the energy storage device, < +.>Is the power of a conventional generator set.
7. A data center demand response policy calculation device, comprising:
and a data receiving module: the method comprises the steps of receiving a data center parameter set, inputting the data center parameter set into a pre-established data center power consumption model to obtain a data center energy supply model, wherein the data center parameter set comprises the following components: data center load related parameters, data center auxiliary equipment parameters, heat exchange coupling relation of equipment in the data center, and operation characteristics of data center IT equipment and air conditioning equipment;
a demand response module: the price type demand response module is used for inputting the price type demand response into the data center energy supply model based on the price type demand response to obtain a data center demand response model;
and a data solving module: and the method is used for solving the data center demand response model to obtain a data center demand response strategy.
8. The data center demand response policy calculation device of claim 7, wherein,
the data center energy model includes: wind turbine generator system, conventional generator system and energy storage equipment;
the output power of the wind turbine generator has upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the wind turbine generator is set;
the output power of the conventional generator set has an upper limit constraint:
in the method, in the process of the invention,the maximum value of the output power of the conventional generator set is set;
the energy storage device has associated constraints on power and capacity:
SOC iT ＝SOC i0
in the method, in the process of the invention,maximum power for charging and discharging of the energy storage device, < >>Is the state variable of energy storage charge and discharge, SOC it Is the charge state of the energy storage device, eta bc 、η bd For the charge and discharge efficiency of the energy storage device, Δt is the time interval,respectively the maximum value and the minimum value of the charge state of the energy storage device, and SOC i0 Is the initial state of charge of the energy storage device.
9. An apparatus, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by one or more of the processors, causes the one or more processors to implement the data center demand response policy calculation method of any one of claims 1-6.
10. A storage medium containing computer executable instructions which, when executed by a computer processor, are for performing the data center demand response policy calculation method of any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311832679.6A CN117669260A (en) | 2023-12-28 | 2023-12-28 | Data center demand response strategy calculation method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311832679.6A CN117669260A (en) | 2023-12-28 | 2023-12-28 | Data center demand response strategy calculation method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117669260A true CN117669260A (en) | 2024-03-08 |
Family
ID=90082635
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311832679.6A Pending CN117669260A (en) | 2023-12-28 | 2023-12-28 | Data center demand response strategy calculation method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117669260A (en) |
-
2023
- 2023-12-28 CN CN202311832679.6A patent/CN117669260A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11342746B2 (en) | Managing queue distribution between critical datacenter and flexible datacenter | |
| US9654414B2 (en) | Scheduling cost efficient datacenter load distribution | |
| CN108846506B (en) | Energy system planning method, device, equipment and storage medium | |
| CN112417651B (en) | User-level comprehensive energy system optimization method based on regret avoidance | |
| CN113191558A (en) | Optimized scheduling method, device and terminal for comprehensive energy system | |
| US11481010B1 (en) | Pre-cooling a battery energy storage system for charging or discharging | |
| CN116822697A (en) | Comprehensive energy system low-carbon economic optimization method considering master-slave playing and demand response | |
| US20180107260A1 (en) | Fuel cell to power electronic components | |
| CN117267910B (en) | Method, device, equipment and medium for flexibly adjusting load of central air-conditioning refrigeration system | |
| CN116404683B (en) | Energy regulation and control method, device, terminal and medium of flexible-direct interconnection system | |
| CN107431220B (en) | Apparatus for managing electronic components in a data center, and related systems and methods | |
| CN117669260A (en) | Data center demand response strategy calculation method, device, equipment and storage medium | |
| CN117013597A (en) | Distributed resource aggregation regulation and control method, device and equipment for virtual power plant | |
| CN116777234A (en) | Method and system for constructing two-stage robust optimization model and formulating strategy | |
| CN113779759A (en) | Data center real-time energy management method and system | |
| CN113507124A (en) | Energy internet fast scheduling method and device based on sequence convex optimization | |
| CN116432818B (en) | Power demand response optimization method for energy storage park | |
| CN212114896U (en) | Distributed electric energy management control system based on virtual power plant | |
| CN218920058U (en) | Energy router | |
| Sun et al. | Energy Storage-Transmission Line Planning Based on Complete Information Static Game Model | |
| CN117057463A (en) | Optimization method, device and storage medium for intelligent building shared energy storage and power supply | |
| CN115425663A (en) | Multi-scene sharing energy storage planning method and system of multi-data center alliance | |
| CN116914790A (en) | Hybrid energy storage device configuration optimization method and device, electronic equipment and storage medium | |
| CN117035257A (en) | CCHP-containing regional comprehensive energy system electricity/heat/Leng Yun energy storage optimal configuration method | |
| Su et al. | Optimal Scheduling of Community Integrated Energy System with Integrated Demand Response |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |