CN112418619B - Data center park power distribution network economic operation method oriented to flexible substation access - Google Patents

Data center park power distribution network economic operation method oriented to flexible substation access Download PDF

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CN112418619B
CN112418619B CN202011249052.4A CN202011249052A CN112418619B CN 112418619 B CN112418619 B CN 112418619B CN 202011249052 A CN202011249052 A CN 202011249052A CN 112418619 B CN112418619 B CN 112418619B
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data center
representing
period
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flexible
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CN112418619A (en
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冀浩然
陈思睿
王成山
季节
于浩
邓占峰
赵国亮
刘云
李鹏
赵金利
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Tianjin University
State Grid Tianjin Electric Power Co Ltd
Global Energy Interconnection Research Institute
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State Grid Tianjin Electric Power Co Ltd
Global Energy Interconnection Research Institute
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

A data center park power distribution network economic operation method oriented to flexible substation access comprises the following steps: inputting basic parameter information of the power distribution network according to the selected power distribution network of the data center park powered by the flexible transformer substation; establishing a flexible operation scheduling strategy of the data center according to basic parameter information of a power distribution network of the data center park; establishing a data center park energy-saving loss-reducing model based on a flexible transformer substation; solving the energy-saving loss-reducing model of the data center park based on the flexible transformer substation, and outputting a solving result, wherein the solving result comprises the following steps: the method comprises the steps of running cost of a power distribution network of a data center park, transmission power of a flexible substation and a data load scheduling strategy of each data center. The method provided by the invention can be used for solving the problem of improving the operation economy of the power distribution network of the data center park, reducing the operation cost of the power distribution network of the data center park and realizing flexible operation of the system.

Description

Data center park power distribution network economic operation method oriented to flexible substation access
Technical Field
The invention relates to a data center park energy-saving loss-reducing method. In particular to an economic operation method for a data center park power distribution network accessed to a flexible substation.
Background
With the rapid development of Internet technology, the scale and number of data centers (IDCs) are rapidly expanding, and become important power consumers in an active power distribution network, thereby greatly increasing the power consumption load. According to statistics, the power consumption of the data center accounts for more than 1.3% of the total power supply amount in the world, and accounts for more than 2.35% in china, and how to effectively realize energy-saving and loss-reducing operation of the data center becomes a problem to be solved urgently.
Because the IT server in the data center is usually a direct current power supply device, the operation efficiency of the data center is effectively improved by adopting a direct current power supply mode. The flexible transformer substation is novel flexible power distribution equipment based on a power electronic device, and flexible interconnection of a multi-voltage-grade and AC/DC multi-electric-energy-form power distribution network can be realized through various AC/DC conversion links. The method comprises the steps that efficient integration and power supply of a data center are carried out on the basis of a direct current link connected with a flexible substation, and the flexible substation reduces operation loss of the data center by improving the tide distribution of a medium-low voltage alternating current-direct current power distribution network. Moreover, the data center can flexibly transfer data loads with longer tolerance service delay on a time scale, and the data center loads can be adjusted on a space dimension so as to achieve the effect of balancing regional loads, so that the data center can be used as a demand side response resource by considering the time and space load adjustment potential of the data center, and the operation economy of a data center park is further improved through source-network-load-storage coordination.
Researches on electricity utilization characteristics and flexible scheduling of data centers have been carried out at home and abroad, and mainly focus on price-based data center demand response, and time distribution of data center loads is guided through electricity price signals so as to balance regional loads. But the method still has the challenge of realizing energy conservation and loss reduction of the data center based on the flexible substation. The space-time load regulation potential of the data center needs to be considered, and the data center is coordinated and matched with the flexible transformer substation, so that the operation cost of a power distribution network of a data center park is reduced. Therefore, an economic operation method for a power distribution network of a data center park accessed to a flexible substation is urgently needed, and energy-saving and loss-reducing operation of the data center park is realized by flexibly scheduling data loads on a time-space scale and performing source-network-load-storage coordination.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an economic operation method of a power distribution network in a data center park facing flexible substation access, which can reduce the operation cost of the power distribution network in the data center park and realize flexible operation of a system.
The technical scheme adopted by the invention is as follows: a data center park power distribution network economic operation method oriented to flexible substation access comprises the following steps:
1) inputting basic parameter information of the power distribution network according to the selected power distribution network of the data center park powered by the flexible transformer substation, wherein the basic parameter information comprises the following steps: the system comprises the flexible transformer substation access positions and capacities, data center park alternating current and direct current distribution network topology and parameter information, the data center access positions and data load change curves, the energy storage access positions and capacities, the load access positions and power change curves, the photovoltaic power station access positions and output curves, and system reference voltages and reference powers;
2) establishing a flexible operation scheduling strategy of the data center according to the basic parameter information of the power distribution network of the data center park provided in the step 1), wherein the strategy comprises the following steps: modeling the power consumption of a data center based on dynamic voltage frequency regulation, processing constraint of delay sensitive data loads and space-time scheduling constraint of delay tolerant data loads;
3) the method for establishing the energy-saving loss-reducing model of the data center park based on the flexible transformer substation comprises the following steps: setting the minimum operating cost of a power distribution network of a data center park as a target function, and respectively considering the operation constraint of a flexible transformer substation, a flexible data center scheduling strategy, the operation constraint of an energy storage system, the operation constraint of a photovoltaic power station and the operation constraint of an alternating current-direct current power distribution network;
4) solving the data center park energy-saving loss-reducing model based on the flexible transformer substation obtained in the step 3), and outputting a solving result, wherein the solving result comprises the following steps: the method comprises the steps of running cost of a power distribution network of a data center park, transmission power of a flexible substation and a data load scheduling strategy of each data center.
The economic operation method of the data center park power distribution network for flexible substation access provided by the invention can be used for solving the problem of improving the operation economy of the data center park power distribution network, fully considering the flexible power control of the flexible substation and the load regulation potential of the data center, establishing a data center park energy-saving loss-reducing model based on the flexible substation, obtaining a flexible dispatching strategy of the flexible substation and the data center load for the economic operation of the data center park power distribution network, reducing the operation cost of the data center park power distribution network and realizing the flexible operation of the system.
Drawings
FIG. 1 is a flow chart of an economic operation method of a power distribution network of a data center park accessed to a flexible substation;
FIG. 2 is a block diagram of a data center campus distribution network based on flexible substation power supply;
FIG. 3 is a photovoltaic and load operating curve;
FIG. 4 is a time of use electricity price curve for the system;
FIG. 5 is a data workload fluctuation curve;
FIG. 6a is a variation curve of the operating frequency of the class I server in the data center in the scheme 2;
FIG. 6b is a variation curve of the operating frequency of the class II server in the data center in the scheme 2;
FIG. 7 is a data center workload storage in scenario 2;
fig. 8 is active power transmitted by the medium voltage ac side port of the flexible substation of schemes 1 and 2;
FIG. 9 is a diagram of charging and discharging power of the energy storage system in scheme 2;
FIG. 10 is a graph comparing operating costs of data centers for scenarios 1 and 2;
fig. 11 is a graph comparing data center power consumption for scenarios 1 and 2.
Detailed Description
The economic operation method of the power distribution network of the data center park facing the flexible substation access is described in detail below with reference to the embodiments and the accompanying drawings.
According to the economic operation method of the power distribution network of the data center park facing the access of the flexible transformer substation, disclosed by the invention, aiming at the energy conservation and loss reduction problems of the power distribution network of the data center park, a data center park energy conservation and loss reduction model based on the flexible transformer substation is established, the operation constraint of the flexible transformer substation, the flexible scheduling constraint of the data center, the energy storage operation constraint, the distributed power supply operation constraint and the operation constraint of an alternating current-direct current power distribution network are comprehensively considered, and finally, the flexible transformer substation facing the economic operation of the power distribution network of the data center park and the flexible scheduling strategy of loads of the data center are determined.
As shown in fig. 1, the economic operation method of the power distribution network in the data center park for flexible substation access includes the following steps:
1) inputting basic parameter information of the power distribution network according to the selected power distribution network of the data center park powered by the flexible transformer substation, wherein the basic parameter information comprises the following steps: the system comprises the flexible transformer substation access positions and capacities, data center park alternating current and direct current distribution network topology and parameter information, the data center access positions and data load change curves, the energy storage access positions and capacities, the load access positions and power change curves, the photovoltaic power station access positions and output curves, and system reference voltages and reference powers;
for the embodiment of the invention, the data center park distribution network structure based on the flexible transformer substation is shown in fig. 2, the data center park distribution network structure comprises the flexible transformer substation, a direct current network, a photovoltaic power station and an energy storage and data center, firstly, load parameters, line parameters and network topology connection relations of the data center park distribution network are input, and detailed parameters are shown in tables 1-3. The capacities of an AC/DC converter, a DC/DC converter and a DC/AC converter in the flexible transformer substation are respectively 10MVA, 10MW and 5MVA, and the loss coefficient of each converter is 0.01; the 10kV medium-voltage alternating current side of the flexible transformer substation is connected to a 10kV bus of a 110kV transformer substation; photovoltaic power generation is accessed to a 10kV medium-voltage direct-current side of a flexible substation through a photovoltaic direct-current booster station and a direct-current line, the access capacity is 2.5MW, and the photovoltaic power generation can be consumed on site through a data center and also can be consumed on line through an alternating-current 10kV power distribution network; 380V low-voltage alternating current output of the flexible transformer substations supplies power to alternating current loads of the data center, and 750V low-voltage direct current of the two flexible transformer substations are interconnected to supply power to direct current loads of the data center. In order to meet the power supply reliability, an energy storage system is connected to a 750V low-voltage direct current side for standby, the energy storage capacity is 5000kWh, the upper and lower limits of the charge state are 1000kWh and 4500kWh, and the upper and lower limits of the energy storage charge and discharge power are +/-1000 kW. Two portal servers are set to transmit data to the data center, 3 data centers are respectively connected to the low-voltage direct-current side of the flexible transformer substation, two types of servers are installed in each sub-data center, the same type of servers are homogeneous (performance and power consumption parameters are the same), and detailed data center parameters are shown in a table 4; and finally setting the system reference power to be 1 MVA.
TABLE 1 load parameters
Figure BDA0002770714110000031
TABLE 2 alternating network parameters
Figure BDA0002770714110000032
TABLE 3 DC network parameters
Figure BDA0002770714110000033
TABLE 4 data center operating parameters
Figure BDA0002770714110000034
Figure BDA0002770714110000041
2) Establishing a flexible operation scheduling strategy of the data center according to the basic parameter information of the power distribution network of the data center park provided in the step 1), wherein the strategy comprises the following steps: modeling the power consumption of a data center based on dynamic voltage frequency regulation, processing constraint of delay sensitive data loads and space-time scheduling constraint of delay tolerant data loads; wherein the content of the first and second substances,
(2.1) the modeling of the data center power consumption based on dynamic voltage frequency adjustment is represented as:
Figure BDA0002770714110000042
in the formula (I), the compound is shown in the specification,
Figure BDA0002770714110000043
representing the active power consumed by the data center at the node i in the period t;
Figure BDA0002770714110000044
representing active power consumed by a server in the data center at a node i in a period t;
Figure BDA0002770714110000045
the active power consumed by cooling equipment in the data center at the node i in the period t is represented;
Figure BDA0002770714110000046
the active power consumed by auxiliary power supply equipment in the data center at a node i in a period t is represented; PUEiThe electric energy utilization efficiency of a data center node i is obtained; mi,kRepresenting the total number of k-type servers operated by the data center at the node i; n is a radical ofkRepresenting the total number of server types in the data center;
Figure BDA0002770714110000047
the active power consumed by each k-type server of the data center at the node i in the period t is represented;
Figure BDA0002770714110000048
representing the fixed power consumed by each k-type server of the data center at the node i;
Figure BDA0002770714110000049
the active power consumed by each K-type server CPU of the data center at the node i in the period t is represented; c1Representing the power consumption coefficient of a CPU of the server;
Figure BDA00027707141100000410
representing the working frequency of a CPU (central processing unit) of a k-type server of a data center at a node i in a period t;
Figure BDA00027707141100000411
representing the working voltage of a CPU (central processing unit) of a k-type server of the data center at a node i in a period t; u. ofi,k,tRepresenting the utilization rate of a CPU (central processing unit) of a k-type server of the data center at a node i in a period t; n is a radical ofρRepresenting a total number of data payload types; di,k,ρ,tThe rho type data load amount processed by the k type server in the data center at the node i in the t period is represented; mu.si,k,tRepresenting the service efficiency of a k-type server of the data center at the node i in the period t;
the CPU of the server has discrete and adjustable working voltage and working frequency, and in actual operation, the CPU can be set at several given frequencies
Figure BDA00027707141100000412
Of the same typeCPU working voltage of server
Figure BDA00027707141100000413
And service efficiency mui,k,tAll are consistent with the working frequency
Figure BDA00027707141100000414
In direct proportion, the CPU energy consumption of the data center server is further expressed as:
Figure BDA00027707141100000415
Figure BDA0002770714110000051
Figure BDA0002770714110000052
Figure BDA0002770714110000053
in the formula, C2Representing a CPU power consumption coefficient; n is a radical ofsRepresenting the number of gears of the CPU working frequency of the server; a isi,k,t,sThe s-gear working frequency zone bit of a CPU of a data center k-type server at a node i in the t period is represented;
Figure BDA0002770714110000054
representing s-gear working frequency, d 'of a data center k-type server CPU at node i'i,k,tRepresenting the data load amount processed by each k-type server of the data center at the node i in the period t;
introducing an auxiliary variable bi,k,t,s＝ai,k,t,sd′i,k,tThe server CPU power consumption model is subjected to linearization processing, and the processing is further expressed as follows:
Figure BDA0002770714110000055
in the formula, bi,k,t,sAn auxiliary variable representing the amount of data load processed by the k-type server in the data center at the node i in the period t; m is a constant representing any value greater than the computational efficiency of the server data.
(2.2) said delay-sensitive data load handling constraint represented by
Figure BDA0002770714110000056
In the formula, NδRepresenting the number of front-end servers; n is a radical ofkRepresenting the total number of server types in the data center; di,ρ,tRepresenting rho type data load amount processed by a data center at a node i in a period t; lambda [ alpha ]i,δ,ρ,tRepresenting rho type data load quantity transmitted from a front-end server delta to a data center at a node i in a period t; mu.si,k,tRepresenting the data calculation efficiency of each k-type server of the data center at the node i in the period t;
Figure BDA0002770714110000057
representing the CPU working frequency of a k-type server of the data center at a node i in a period t; di,k,ρ,tThe rho type data load amount processed by the k type server in the data center at the node i in the t period is represented; mi,kRepresenting the total number of k-type servers operated by the data center at the node i; dρRepresenting delay tolerance time of rho-type delay sensitive data load; c3Indicating that the server calculates the coefficient of performance.
(2.3) said delay tolerant data load spatio-temporal scheduling constraint represented as
(2.3.1) data load time transfer strategy:
Figure BDA0002770714110000058
Figure BDA0002770714110000061
Figure BDA0002770714110000062
Figure BDA0002770714110000063
Figure BDA0002770714110000064
Figure BDA0002770714110000065
Figure BDA0002770714110000066
in the formula, NδRepresenting the number of front-end servers; n is a radical ofnRepresenting the total number of network nodes; n is a radical ofρRepresenting a total number of data payload types; delta lambdai,ρ,tRepresenting rho type data load variation in the data center at a node i in a period t; lambda [ alpha ]i,δ,ρ,tRepresenting rho type data load quantity transmitted from a front-end server delta to a data center at a node i in a period t; lambda [ alpha ]i,j,ρ,tRepresenting rho type data load quantity transmitted from a data center at a node j to a data center at a node i in a period t;
Figure BDA0002770714110000067
representing the total rho type data load transferred from the data center at the node i to other data centers in the period t; di,ρ,tRepresenting rho type data load amount processed by a data center at a node i in a period t; ei,ρ,tRepresenting the total load of rho type data stored in the data center at the node i in the period t; ei,ρ,TAnd
Figure BDA0002770714110000068
representing a computing service knotThe total load of rho type data stored in the data center at the node i at the beam and start time; Δ t represents the duration of each period; ei,maxRepresenting the data center data load storage upper limit at the node i;
Figure BDA0002770714110000069
representing the total rho type data load which is to be processed at the end time of the t' time period; l isδ,ρ,tRepresenting the total load of rho type data transmitted by a front-end server delta in a period t; t is t0Representing an initial period of operation of the data center; t is tρRepresenting delay tolerance time of rho-type delay tolerant data loads;
(2.3.2) data payload space allocation strategy:
Figure BDA00027707141100000610
in the formula, Lδ,ρ,tRepresenting the total load of rho type data transmitted by a front-end server delta in a period t; l isi,ρ,tRepresenting that the data center at the node i receives rho type data load total amount from other data centers in the period t; lambda [ alpha ]j,i,ρ,tRepresenting rho type data load quantity transmitted from a data center at a node i to a data center at a node j in a period t;
Figure BDA00027707141100000611
and
Figure BDA00027707141100000612
respectively representing the data load state zone bits received and transmitted by the data center at the node i in the period of t when
Figure BDA00027707141100000613
When the time is 1, the data center at the node i receives data load transmitted from other data centers in the time period t
Figure BDA00027707141100000614
And when the time is 1, the data center at the node i transmits data load to other data centers in the time period t.
3) The method for establishing the energy-saving loss-reducing model of the data center park based on the flexible transformer substation comprises the following steps: setting the minimum operating cost of a power distribution network in a data center park as a target function, and respectively considering the operation constraint of a flexible transformer substation, a flexible operation scheduling strategy of the data center, the operation constraint of an energy storage system, the operation constraint of a photovoltaic power station and the operation constraint of an alternating current-direct current power distribution network; wherein the content of the first and second substances,
(3.1) the minimum operation cost of the power distribution network of the data center park is represented as an objective function:
Figure BDA0002770714110000071
wherein f represents an objective function, fIDCRepresenting the electricity charge of the data center; f. ofESSRepresenting energy storage scheduling cost; n is a radical ofTRepresents the total number of time segments; n is a radical ofnRepresenting the total number of network nodes;
Figure BDA0002770714110000072
the active power injected by the flexible substation at the medium-voltage alternating-current node i in the t period is represented;
Figure BDA0002770714110000073
the active power of energy storage injection at a node i in the data center park at the time period t is represented; c. CtRepresenting the system electricity price in the t period;
Figure BDA0002770714110000074
representing the unit scheduling cost of the t-period energy storage.
(3.2) the flexible substation operation constraint is expressed as:
Figure BDA0002770714110000075
in the formula (I), the compound is shown in the specification,
Figure BDA0002770714110000076
and
Figure BDA0002770714110000077
respectively representing active power injected by the flexible transformer substations at nodes i, j, k and g in the period t; eta1、η2And η3Respectively representing loss coefficients of an AC/DC converter, a DC/DC converter and a DC/AC converter in the flexible substation;
Figure BDA0002770714110000078
the active power output by the direct current side of the AC/DC converter in the flexible substation in the t period is represented;
Figure BDA0002770714110000079
and
Figure BDA00027707141100000710
the active power input and output by a DC/DC converter in the flexible substation in the t period is represented;
Figure BDA00027707141100000711
the active power input at the direct current side of a DC/AC converter in the flexible substation in the t period is represented;
Figure BDA00027707141100000712
and
Figure BDA00027707141100000713
respectively representing reactive power injected by the flexible transformer substation at nodes i and g in the t period;
Figure BDA00027707141100000714
and
Figure BDA00027707141100000715
respectively representing the upper limit and the lower limit of reactive power output by the AC/DC converter in the flexible substation;
Figure BDA00027707141100000716
and
Figure BDA00027707141100000717
respectively representThe upper and lower limits of reactive power output by the AC side of a DC/AC converter in the flexible transformer substation are set;
Figure BDA00027707141100000718
Figure BDA00027707141100000719
and
Figure BDA00027707141100000720
respectively representing the capacities of an AC/DC converter, a DC/DC converter and a DC/AC converter in the flexible substation;
because the formula (8) contains absolute value terms, auxiliary variables are introduced
Figure BDA00027707141100000721
And
Figure BDA00027707141100000722
linearization is performed and constraints are added:
Figure BDA00027707141100000723
Figure BDA0002770714110000081
Figure BDA0002770714110000082
Figure BDA0002770714110000083
Figure BDA0002770714110000084
in the formula (I), the compound is shown in the specification,
Figure BDA0002770714110000085
and
Figure BDA0002770714110000086
and respectively representing the active power loss of the AC/DC converter, the DC/DC converter and the DC/AC converter in the flexible substation in the t period.
(3.3) the energy storage system operating constraints are expressed as:
Figure BDA0002770714110000087
in the formula (I), the compound is shown in the specification,
Figure BDA0002770714110000088
representing the charging and discharging power of the energy storage system at a node i in the t period;
Figure BDA0002770714110000089
the maximum value of the charging and discharging power of the energy storage system at the node i in the t period is represented;
Figure BDA00027707141100000810
and
Figure BDA00027707141100000811
respectively representing the electric quantity stored by the energy storage system at the node i in the t +1 time period and the t time period; delta t is the time difference of two time periods;
Figure BDA00027707141100000812
and
Figure BDA00027707141100000813
respectively representing the lower limit and the upper limit of the stored electric quantity of the energy storage system at the node i;
Figure BDA00027707141100000814
and
Figure BDA00027707141100000815
respectively representing the initial time t of operation0And the energy storage system at the T node i at the end timeThe stored electric quantity value of (2).
(3.4) the photovoltaic power plant operation constraint is expressed as
Figure BDA00027707141100000816
In the formula (I), the compound is shown in the specification,
Figure BDA00027707141100000817
representing the active power output by the photovoltaic power station at a node i in the t period;
Figure BDA00027707141100000818
representing an active power predicted value output by the photovoltaic power station at a node i in a t period;
Figure BDA00027707141100000819
and the reduction amount of the photovoltaic power station at the node i in the t period is shown.
(3.5) the operation constraint of the alternating current and direct current distribution network is represented as:
(3.5.1) power flow constraint of the alternating-current power distribution network:
Figure BDA00027707141100000820
in the formula (I), the compound is shown in the specification,
Figure BDA00027707141100000821
representing an AC line set; omegaacRepresenting a set of traffic nodes; pij,tAnd Pjh,tRespectively representing active power transmitted by a line ij and a line jh in a period t; qij,tAnd Qjh,tRepresenting the reactive power transmitted by the line ij and the line jh in the period t; pj,tAnd Qj,tRepresenting the active power and reactive power injected by the node j in the period t; lij,tRepresents the square of the current amplitude of line ij during period t; v. ofi,tRepresents the square of the voltage amplitude of the node i in the period t; r isijRepresents the resistance value of the line ij; x is the number ofijRepresents the reactance value of line ij;
Figure BDA00027707141100000822
and
Figure BDA00027707141100000823
representing active and reactive loads at a node j in a period t;
Figure BDA0002770714110000091
and
Figure BDA0002770714110000092
and the active power and the reactive power injected by the flexible substation at the node j in the period t are represented.
(3.5.2) direct current distribution network power flow operation constraint:
Figure BDA0002770714110000093
in the formula (I), the compound is shown in the specification,
Figure BDA0002770714110000094
representing a set of direct current lines; omegadcRepresenting a set of direct current nodes;
Figure BDA0002770714110000095
and
Figure BDA0002770714110000096
the active power injected by the flexible transformer substation, the photovoltaic power station and the energy storage system at the position of the direct-current node j in the t period is represented;
Figure BDA0002770714110000097
and
Figure BDA0002770714110000098
and the active power consumed by the data center and the load at the direct current node j in the period t is represented.
And (3.6) flexibly operating the scheduling strategy by the data center, which is provided by the step 2).
4) Solving the data center park energy-saving loss-reducing model based on the flexible transformer substation obtained in the step 3), and outputting a solving result, wherein the solving result comprises the following steps: the method comprises the steps of running cost of a power distribution network of a data center park, transmission power of a flexible substation and a data load scheduling strategy of each data center.
In order to fully verify the advancement of the economic operation method of the power distribution network in the data center park oriented to the flexible substation access, in this embodiment, the following two schemes are adopted for comparative analysis:
scheme 1: flexible dispatching is not carried out on the flexible transformer substation, the energy storage system and the data center load, and the initial running state of the active power distribution network is obtained;
scheme 2: by adopting the method for economically operating the power distribution network of the data center park accessed to the flexible transformer substation, the operation economy of the power distribution network of the data center park is improved.
The optimization results of the scheme 1 and the scheme 2 are compared in a table 5, the photovoltaic and load operation fluctuation curve is shown in a figure 3, the time-of-use electricity price of a power distribution system is shown in a figure 4, the working load fluctuation curve of a data center is shown in a figure 5, the working frequency and the working load storage capacity of a data center server in the scheme 2 are shown in a figure 6 and a figure 7, the active power emitted by a medium-voltage alternating-current side port of a flexible substation in the schemes 1 and 2 is shown in a figure 8, the charging and discharging power of an energy storage system in the scheme 2 is shown in a figure 9, and the comparison conditions of the operation cost and the power consumption of the data center in the two schemes are shown in a figure 10 and a figure 11.
The computer hardware environment for executing the optimization calculation is Intel (R) Xeon (R) CPU E5-1620, the main frequency is 3.70GHz, and the memory is 32 GB; the software environment is a Windows 10 operating system.
Compared with the scheme 1 and the scheme 2, the load regulation potential of the data center is fully developed from the aspects of time transfer and space distribution, the work load scheduling of the data center is carried out, the flexible scheduling of the transmission power of the flexible transformer substation is carried out, the power consumption of the data center can be effectively reduced, and the economical and efficient operation of a power distribution network in a park is guaranteed.
Table 5 comparison of active power distribution system operation
Figure BDA0002770714110000099

Claims (5)

1. A data center park power distribution network economic operation method oriented to flexible substation access is characterized by comprising the following steps:
1) inputting basic parameter information of the power distribution network according to the selected power distribution network of the data center park powered by the flexible transformer substation, wherein the basic parameter information comprises the following steps: the system comprises the flexible transformer substation access positions and capacities, data center park alternating current and direct current distribution network topology and parameter information, the data center access positions and data load change curves, the energy storage access positions and capacities, the load access positions and power change curves, the photovoltaic power station access positions and output curves, and system reference voltages and reference powers;
2) establishing a flexible operation scheduling strategy of the data center according to the basic parameter information of the power distribution network of the data center park provided in the step 1), wherein the strategy comprises the following steps: modeling the power consumption of a data center based on dynamic voltage frequency regulation, processing constraint of delay sensitive data loads and space-time scheduling constraint of delay tolerant data loads;
3) the method for establishing the energy-saving loss-reducing model of the data center park based on the flexible transformer substation comprises the following steps: setting the minimum operating cost of a power distribution network of a data center park as a target function, and respectively considering the operation constraint of a flexible transformer substation, a flexible data center scheduling strategy, the operation constraint of an energy storage system, the operation constraint of a photovoltaic power station and the operation constraint of an alternating current-direct current power distribution network;
4) solving the data center park energy-saving loss-reducing model based on the flexible transformer substation obtained in the step 3), and outputting a solving result, wherein the solving result comprises the following steps: the method comprises the steps of running cost of a power distribution network of a data center park, transmission power of a flexible substation and a data load scheduling strategy of each data center.
2. The economic operation method of the power distribution network of the data center park oriented to the flexible substation access according to claim 1, characterized in that the modeling of the power consumption of the data center based on the dynamic voltage frequency regulation in the step 2) is represented as:
Figure FDA0002770714100000011
in the formula (I), the compound is shown in the specification,
Figure FDA0002770714100000012
representing the active power consumed by the data center at the node i in the period t;
Figure FDA0002770714100000013
representing active power consumed by a server in the data center at a node i in a period t;
Figure FDA0002770714100000014
the active power consumed by cooling equipment in the data center at the node i in the period t is represented;
Figure FDA0002770714100000015
the active power consumed by auxiliary power supply equipment in the data center at a node i in a period t is represented; PUEiThe electric energy utilization efficiency of a data center node i is obtained; mi，kRepresenting the total number of k-type servers operated by the data center at the node i; n is a radical ofkRepresenting the total number of server types in the data center;
Figure FDA0002770714100000016
the active power consumed by each k-type server of the data center at the node i in the period t is represented;
Figure FDA0002770714100000017
representing the fixed power consumed by each k-type server of the data center at the node i;
Figure FDA0002770714100000018
the active power consumed by each K-type server CPU of the data center at the node i in the period t is represented; c1Representing the power consumption coefficient of a CPU of the server;
Figure FDA0002770714100000019
representing the t period nodeThe working frequency of a CPU of a k-type server of the data center at the position i;
Figure FDA00027707141000000110
representing the working voltage of a CPU (central processing unit) of a k-type server of the data center at a node i in a period t; mu.si，k，tRepresenting the utilization rate of a CPU (central processing unit) of a k-type server of the data center at a node i in a period t; n is a radical ofρRepresenting a total number of data payload types; di，k，ρ，tThe rho type data load amount processed by the k type server in the data center at the node i in the t period is represented; mu.si，k，tRepresenting the service efficiency of a k-type server of the data center at the node i in the period t;
the CPU of the server has discrete and adjustable working voltage and working frequency, and in actual operation, the CPU can be set at several given frequencies
Figure FDA0002770714100000021
The CPU working voltage of the same type of server
Figure FDA0002770714100000022
And service efficiency mui，k，tAll are consistent with the working frequency
Figure FDA0002770714100000023
In direct proportion, the CPU energy consumption of the data center server is further expressed as:
Figure FDA0002770714100000024
in the formula, C2Representing a CPU power consumption coefficient; n is a radical ofsRepresenting the number of gears of the CPU working frequency of the server; a isi，k，t，sThe s-gear working frequency zone bit of a CPU of a data center k-type server at a node i in the t period is represented;
Figure FDA0002770714100000025
representing s-gear working frequency, d 'of a data center k-type server CPU at node i'i，k，tRepresenting the data load amount processed by each k-type server of the data center at the node i in the period t;
introducing an auxiliary variable bi，k，t，s＝ai，k，t，sd′i，k，tThe server CPU power consumption model is subjected to linearization processing, and the processing is further expressed as follows:
Figure FDA0002770714100000026
in the formula, bi，k，t，sAn auxiliary variable representing the amount of data load processed by the k-type server in the data center at the node i in the period t; m is a constant representing any value greater than the computational efficiency of the server data.
3. The economic operation method of the flexible substation access-oriented data center park distribution network according to claim 1, characterized in that the delay-sensitive data load handling constraint in the step 2) is expressed as
Figure FDA0002770714100000027
Figure FDA0002770714100000031
In the formula, NδRepresenting the number of front-end servers; n is a radical ofkRepresenting the total number of server types in the data center; di，ρ，tRepresenting rho type data load amount processed by a data center at a node i in a period t; lambda [ alpha ]i，δ，ρ，tRepresenting rho type data load quantity transmitted from a front-end server delta to a data center at a node i in a period t; mu.si，k，tRepresenting the data calculation efficiency of each k-type server of the data center at the node i in the period t;
Figure FDA0002770714100000032
representing the t period node iThe CPU working frequency of a k-type server in a data center; di，k，ρ，tThe rho type data load amount processed by the k type server in the data center at the node i in the t period is represented; mt，kRepresenting the total number of k-type servers operated by the data center at the node i; dρRepresenting delay tolerance time of rho-type delay sensitive data load; c3Indicating that the server calculates the coefficient of performance.
4. The economic operation method of the flexible substation access-oriented data center park power distribution network according to claim 1, wherein the minimum operation cost of the data center park power distribution network in the step 3) is expressed as an objective function:
Figure FDA0002770714100000033
wherein f represents an objective function, fIDCRepresenting the electricity charge of the data center; f. ofESSRepresenting energy storage scheduling cost; n is a radical ofTRepresents the total number of time segments; n is a radical ofnRepresenting the total number of network nodes;
Figure FDA0002770714100000034
the active power injected by the flexible substation at the medium-voltage alternating-current node i in the t period is represented;
Figure FDA0002770714100000035
the active power of energy storage injection at a node i in the data center park at the time period t is represented; c. CtRepresenting the system electricity price in the t period;
Figure FDA0002770714100000036
representing the unit scheduling cost of the t-period energy storage.
5. The economic operation method of the flexible substation access-oriented data center park distribution network according to claim 1, characterized in that the flexible substation operation constraint in the step 3) is expressed as
Figure FDA0002770714100000037
In the formula (I), the compound is shown in the specification,
Figure FDA0002770714100000038
and
Figure FDA0002770714100000039
respectively representing active power injected by the flexible transformer substations at nodes i, j, k and g in the period t; eta1、η2And η3Respectively representing loss coefficients of an AC/DC converter, a DC/DC converter and a DC/AC converter in the flexible substation;
Figure FDA00027707141000000310
the active power output by the direct current side of the AC/DC converter in the flexible substation in the t period is represented;
Figure FDA00027707141000000311
and
Figure FDA00027707141000000312
the active power input and output by a DC/DC converter in the flexible substation in the t period is represented;
Figure FDA00027707141000000313
the active power input at the direct current side of a DC/AC converter in the flexible substation in the t period is represented;
Figure FDA0002770714100000041
and
Figure FDA0002770714100000042
respectively representing reactive power injected by the flexible transformer substation at nodes i and g in the t period;
Figure FDA0002770714100000043
and
Figure FDA0002770714100000044
respectively representing the upper limit and the lower limit of reactive power output by the AC/DC converter in the flexible substation;
Figure FDA0002770714100000045
and
Figure FDA0002770714100000046
respectively representing the upper limit and the lower limit of reactive power output by the AC side of a DC/AC converter in the flexible substation;
Figure FDA0002770714100000047
and
Figure FDA0002770714100000048
respectively representing the capacities of an AC/DC converter, a DC/DC converter and a DC/AC converter in the flexible substation;
because the formula (6) contains absolute value terms, auxiliary variables are introduced
Figure FDA0002770714100000049
And
Figure FDA00027707141000000410
linearization is performed and constraints are added:
Figure FDA00027707141000000411
in the formula (I), the compound is shown in the specification,
Figure FDA00027707141000000412
and
Figure FDA00027707141000000413
respectively representing an AC/DC converter and a DC converter in the flexible substation in the time period t,Active power loss of the DC/DC converter and the DC/AC converter.
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