CN107248755A - A kind of data center's regenerative resource smooths method of supplying power to - Google Patents
A kind of data center's regenerative resource smooths method of supplying power to Download PDFInfo
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- CN107248755A CN107248755A CN201710609143.6A CN201710609143A CN107248755A CN 107248755 A CN107248755 A CN 107248755A CN 201710609143 A CN201710609143 A CN 201710609143A CN 107248755 A CN107248755 A CN 107248755A
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- 230000001172 regenerating effect Effects 0.000 title claims abstract description 112
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000009499 grossing Methods 0.000 claims abstract description 14
- 230000006978 adaptation Effects 0.000 claims abstract description 10
- 238000004146 energy storage Methods 0.000 claims description 14
- 238000013480 data collection Methods 0.000 claims description 3
- 230000003111 delayed effect Effects 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 3
- 238000010248 power generation Methods 0.000 claims description 3
- 230000001502 supplementing effect Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 6
- 230000008901 benefit Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000005611 electricity Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000001556 precipitation Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000006641 stabilisation Effects 0.000 description 2
- 238000011105 stabilization Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
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Classifications
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- H02J3/382—
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- H02J3/383—
-
- H02J3/386—
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- 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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- 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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
Method of supplying power to is smoothed the invention discloses a kind of data center's regenerative resource：Regenerative resource smoothing module obtains the optimal discharge and recharge scheme of power storage equipment by solving Solution of Nonlinear Optimal Problem, makes the final fluctuation for the regenerative resource of data center's energy supply in day part (such as one hour) minimum；It is a kind of load delay scheme based on greedy algorithm to load adaptation module, and it realizes the effect maximized using regenerative resource on the basis of regenerative resource smoothing by dispatching ductile load.The inventive method can effectively alleviate the fluctuation of regenerative resource, and realize under the steady supply situation of regenerative resource and substantially to use regenerative resource.
Description
Technical field
It is flat more particularly, to a kind of data center's regenerative resource the invention belongs to consumption of data center technical field
Cunningization method of supplying power to.
Background technology
With continuing to develop for cloud computing technology, the computing capability of data center is rapidly increasing with scale, therewith
The high-power power consumption come brings two serious consequences：First, data center, which buys power, will bring huge electricity charge expense；Its
Secondary, data center is still depended on the energy is obtained from power network at present, and it is produced by the intensive fossil fuel of coal
Raw major part power, huge energy resource consumption can cause negative ambient influnence, accelerate Global Greenhouse Effect.
Due to regenerative resource (such as wind energy, solar energy) it is inexpensive, pollution-free the features such as, increasing company starts
Construction parts or all by the data center of regenerative resource power supply.Using regenerative resource be data center power bring with
Lower advantage：(1) cost is reduced；(2) carbon emission is reduced.But, regenerative resource power supply also brings new challenge to data center：
(1) fluctuation of regenerative resource can challenge the stability of power network and data center, while frequent transitions energy supply source can also increase
Add operation expense；(2) intermittence of regenerative resource can reduce its utilization rate.
However, existing most variations can not all handle first challenge well, the regenerative resource for neglecting fluctuation is supplied
The impact of power network and data center should be brought, and some work are all stored in doing for power storage equipment using by regenerative resource
Method eliminates fluctuation, but this needs huge battery capacity.
The content of the invention
It is flat the invention provides a kind of data center's regenerative resource for the disadvantages described above or Improvement requirement of prior art
Cunningization method of supplying power to, this method is applied to utilization (such as wind energy, solar energy) of the data center to multiple renewable energy sources, no needs
Seek huge battery capacity, just can effectively gentle regenerative resource fluctuation, it is and real under the steady supply situation of regenerative resource
Now substantially use regenerative resource.
The present invention proposes a kind of data center's regenerative resource smoothing method of supplying power to, comprises the following steps：
(1) regenerative resource is smoothed：Differentiate whether regenerative resource power variance used in current electric grid is more than or equal to pre-
Fixed threshold value, is then to assert that regenerative resource power supply is in the fluctuation energy supply stage, goes to step (2)；Otherwise to stablize the energy supply stage,
Go to step (3)；
(2) it is electrically operated by the electrical energy storage progress charge and discharge in data center's electric power system, by following smooth operations
The fluctuation that regenerative resource is energized in the energy supply stage, then goes to step (3)；
Smooth operation is as follows：Each period (for example, one hour) for belonging to the fluctuation energy supply stage is carried out smoothly respectively；Can
Renewable sources of energy prediction data it is general with 5 minutes or 1 minute for granularity, in beginning (such as the 0th point of each hour of each period
Clock) carry out the period smooth tactful calculating；The holding period is taken to power stable optimal electrical power storage device discharge and recharge plan
Slightly；The strategy determines in each granularity time the total work that (such as five minutes) electrical energy storage should discharge or charge
Rate, so that within each period, the regenerative resource for being finally supplied to data center is smooth steady；
(3) load adaptation：Using the load delay algorithm based on greedy algorithm, the task load in system is classified and arranged
Sequence；
The task load is divided into two classes, and a class is real time load, such as Web request；Another kind of is that can postpone load, is such as criticized
Processing task, scientific algorithm；
It is immediately performed for real time load；Pair can be delayed load by can delay time sort from small to large, meeting task
Under conditions of the required late start time of load, ductile task load is deferred to the load and uses regenerative resource
Most period operations；
The threshold value, for dividing powering phase：Historical data is energized and renewable according to place power network regenerative resource
The energy energizes prediction data, regenerative resource power variance is calculated, it is determined that the threshold value for dividing the stage；When a period of time (example
Such as, one hour) variance yields of the power of interior regenerative resource energy supply when being less than the threshold value, assert that the period belongs to stable energy supply rank
Section, now regenerative resource is more steady in itself；When variance yields is more than or equal to the threshold value, assert that the period belongs to fluctuation energy supply
Stage.Regenerative resource energy supply power prediction data can be estimated by information such as wind speed, the precipitation known from weather forecast；
Historical data is intended merely to one power network regenerative resource overall condition of analysis with threshold value；With prediction data during specific utilization
To carry out divided stages；
Preferably, Threshold is as follows in the step (1)：
The threshold value is, according to local regenerative resource historical data and prediction data, to calculate each power supply period regenerative resource
General power variance yields, takes the less preceding 20%-30% of variance yields power supply period as stablizing the energy supply stage；
The period refers to the time interval for being divided into power-on time by fixed duration, and fixed duration is desirable 30-90 minutes.
Because the prediction taken or historical data are usually that comparatively 1 hour data amount compares for granularity with 1 minute or 5 minutes
Properly, (such as one hour) to be smoothed within the period afterwards, the period is longer, may original fluctuation situation meeting
Bigger, battery capacity is also required to bigger.
Preferably, in the step (2), electrical energy storage realizes smooth power supply using optimal discharge and recharge strategy, specifically
Step is as follows：
By the period of each regenerative resource power supply, by the fixation duration of 1-10 minutes, m time granularity is divided into.For example,
Period is 60 minutes, and when a length of 5 minutes when fixed, m is 12.U=(u1 u2...um) represent on each time granularity (for example,
5 minutes) renewable energy power generation general power；S=(s1 s2...sm)TRepresent that electrical energy storage quilt can on each time granularity
The power of renewable sources of energy charge or discharge；Wherein siJust to represent in the i-th time granularity battery discharge | si|, it is current for supplementing
Insufficient regenerative resource；siThen represent sufficient in the i-th time granularity regenerative resource to be negative, charged to battery | si|；A=U
+ S, i.e.,
For within the period each time granularity by battery charge or discharge operation after, can finally be provided to data center
The power of regenerative resource；The renewable energy source power for being finally supplied to data center is U+S, i.e., after battery operation
Renewable energy source power.
To object function σAMinimizing, for smoothing the period regenerative resource, so that being filled by battery
Regenerative resource fluctuation variance after electricity or electric discharge optimization is minimum, that is, solves Solution of Nonlinear Optimal Problem as follows, from
And obtain A：
Each variable bound condition of above object function is：
Wherein M is the maximum capacity for the electrical energy storage being equipped with；μ is uiThe arithmetic mean of instantaneous value of (i ∈ [1, m]),Represent
Appoint and take；
The σ made according to obtaining in object functionAReach the battery charging and discharging power of minimum value | si|, you can obtain electric energy and deposit
Store up the charge-discharge electric power S of equipment.There is battery electric quantity to be less than the constraint of capacity 90% in constraints；Simultaneous Stabilization energizes the stage
Do not perform that the charge and discharge is electrically operated, just allow for reduce without the need for frequent charge and discharge it is electrically operated.
Preferably, in the step (3), load delay algorithm is comprised the following steps that：
Each task energy quantity to be consumed in calculating task load data collection；
Set up task scheduling queue, by each task by its can delay time sort from small to large, be inserted into task scheduling
In queue, wherein can delay time be remaining free time, its Late Finish for being defined as each mission requirements subtracts this
Run time and current time that task needs；Pair each task in scheduling queue is treated by FIFO sequential scheduling, i.e., when
Between more urgent i.e. free time few priority of task perform load delay algorithm, when determining the actual execution of the task with this
Between；
Specifically, for each the intending performing of the task, first judge whether its remaining free time is more than 0, if remaining idle
Time is not more than 0, then whether abundance must all perform the task at once to regenerative resource；If remaining free time is more than 0,
Selection is under conditions of late start time is met, the task can use the period of regenerative resource optimal as its most
The execution time.Because using greedy algorithm, the decision-making for treating the latter task in scheduling queue is determined in previous task
Carried out on the basis of plan, so in the absence of the conflict of optimal exercising time.
The present invention is one by calculating optimal power supply storage device discharge and recharge strategy so as to which gentle regenerative resource is fluctuated
Property so pass through load dispatch maximize renewable energy utilization rate method.This method is broadly divided into two steps, first
Step is regenerative resource smoothing, and the module obtains the optimal of power storage equipment by solving Solution of Nonlinear Optimal Problem
Discharge and recharge scheme, make the final regenerative resource energized for data center in day part (such as one hour) power variance value
It is minimum；Second step is load adaptation, is a kind of load delay scheme based on greedy algorithm, it is smooth in regenerative resource
On the basis of change, the effect maximized using regenerative resource is realized by dispatching ductile load.
In general, by the contemplated above technical scheme of the present invention compared with prior art, with advantages below：
The regenerative resource realized using the present invention is smoothed, and can need not require the power storage equipment of huge capacity
In the case of, the effectively simply fluctuation of gentle regenerative resource, so as to ensure the stability of power network and data center, together
When reduction frequently power supply source transfer zone operation overhead；And follow-up load adaptation can significantly improve data center can
Utilization of regenerative energy rate.
Brief description of the drawings
Fig. 1 is the overall flow figure of the inventive method；
Fig. 2 is regenerative resource divided stages schematic diagram and regenerative resource and the load situation of change signal of the present invention
Figure；
Fig. 3 is that the present invention implements the renewable energy source power effect diagram after regenerative resource smoothing step；
Fig. 4 is the flow chart of load adaptation method of the present invention based on smooth regenerative resource；
Fig. 5 is the schematic diagram that the present invention implements the load delay scheduling after load adaptation step and initial load situation.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, not
For limiting the present invention.As long as in addition, technical characteristic involved in each embodiment of invention described below that
Not constituting conflict between this can just be mutually combined.
As shown in figure 1, data center's regenerative resource smoothing method of supplying power to of the embodiment of the present invention comprises the following steps：
Step 1：Divide powering phase：Historical data and regenerative resource energy supply are energized according to place power network regenerative resource
Prediction data, calculates regenerative resource power variance, it is determined that the threshold value for dividing the stage；When a period of time (such as one hour)
When the variance yields of the power of interior regenerative resource energy supply is less than the threshold value, assert that the period belongs to the stable energy supply stage, now may be used
The renewable sources of energy are more steady in itself；When variance yields is more than or equal to the threshold value, assert that the period belongs to the fluctuation energy supply stage.Can be again
Raw energy energy supply power prediction data can be estimated by information such as wind speed, the precipitation known from weather forecast；Historical data
One power network regenerative resource overall condition of analysis is intended merely to threshold value；It is specific with when row order entered with prediction data
Section is divided；
Specifically, Threshold is as follows：
The threshold value is, according to local regenerative resource historical data and prediction data, to calculate each power supply period regenerative resource
General power variance yields, takes the less preceding 20%-30% of variance yields power supply period as stablizing the energy supply stage；
The period refers to the time interval for being divided into power-on time by fixed duration, and fixed duration is desirable 30-90 minutes.
Because the prediction taken or historical data are usually that comparatively 1 hour data amount compares for granularity with 1 minute or 5 minutes
Properly, (for example, one hour) to be smoothed within the period afterwards, the period is longer, may original fluctuation situation
Can be bigger, battery capacity is also required to bigger；
Regenerative resource divided stages situation and regenerative resource and load situation of change are as shown in Figure 2.
Step 2：Regenerative resource is smoothed：Differentiate whether regenerative resource power variance used in current electric grid is more than described
Threshold value, is then to assert that regenerative resource power supply is in the fluctuation energy supply stage, passes through the power storage in data center's electric power system
Equipment progress charge and discharge is electrically operated, the fluctuation that regenerative resource is energized in the smooth energy supply stage；Otherwise 3 are gone to step；
Smooth operation is as follows：Each period (such as one hour) for belonging to the fluctuation energy supply stage is carried out smoothly respectively；Can
Renewable sources of energy prediction data it is general with 5 minutes or 1 minute for granularity, in beginning (such as the 0th point of each hour of each period
Clock) carry out the period smooth tactful calculating；The holding period is taken to power stable optimal electrical power storage device discharge and recharge plan
Slightly；The strategy determines in each granularity time the total work that (such as five minutes) electrical energy storage should discharge or charge
Rate, so that within each period, the regenerative resource for being finally supplied to data center is smooth steady；
Specifically, the step of electrical energy storage realizes smooth power supply using optimal discharge and recharge strategy is as follows：
By the period of each regenerative resource power supply, by the fixation duration of 1-10 minutes, m time granularity is divided into.For example,
Period is 60 minutes, and when a length of 5 minutes when fixed, m is 12.U=(u1u2...um) represent on each time granularity (for example, 5
Minute) renewable energy power generation general power；S=(s1 s2...sm)TRepresent that electrical energy storage quilt can be again on each time granularity
The power of raw energy charge or discharge；Wherein siJust to represent in the i-th time granularity battery discharge | si|, for supplementing currently not
Sufficient regenerative resource；siThen represent sufficient in the i-th time granularity regenerative resource to be negative, charged to battery | si|；A=U+
S, i.e.,
For within the period each time granularity by battery charge or discharge operation after, can finally be provided to data center
The power of regenerative resource；The renewable energy source power for being finally supplied to data center is U+S, i.e., after battery operation
Renewable energy source power.
To object function σAMinimizing, for smoothing the period regenerative resource, so that being filled by battery
Regenerative resource fluctuation variance after electricity or electric discharge optimization is minimum, that is, solves Solution of Nonlinear Optimal Problem as follows, from
And obtain A：
Each variable bound condition of above object function is：
Wherein M is the maximum capacity for the electrical energy storage being equipped with；μ is uiThe arithmetic mean of instantaneous value of (i ∈ [1, m]),Represent
Appoint and take；
The σ made according to obtaining in object functionAReach the battery charging and discharging power of minimum value | si|, you can obtain electric energy and deposit
Store up the charge-discharge electric power S of equipment.There is battery electric quantity to be less than the constraint of capacity 90% in constraints；Simultaneous Stabilization energizes the stage
Do not perform that the charge and discharge is electrically operated, just allow for reduce without the need for frequent charge and discharge it is electrically operated；
Renewable energy source power effect after implementation steps 2 is as shown in Figure 3.
Step 3：Load adaptation：Using the load delay algorithm based on greedy algorithm, the task load in system is classified
And sequence；
The task load is divided into two classes, and a class is real time load, such as Web request；Another kind of is that can postpone load, is such as criticized
Processing task, scientific algorithm；
It is immediately performed for real time load；Pair can be delayed load by can delay time sort from small to large, meeting task
Under conditions of the required late start time of load, ductile task load is deferred to the load and uses regenerative resource
Most period operations；
As shown in figure 4, load delay algorithm is comprised the following steps that：Each task will be consumed in calculating task load data collection
Energy quantity；
Set up task scheduling queue, by each task by its can delay time sort from small to large, be inserted into task scheduling
In queue, wherein can delay time be remaining free time, its Late Finish for being defined as each mission requirements subtracts this
Run time and current time that task needs；Pair each task in scheduling queue is treated by FIFO sequential scheduling, i.e., when
Between more urgent i.e. free time few priority of task perform load delay algorithm, when determining the actual execution of the task with this
Between；
Specifically, for each the intending performing of the task, first judge whether its remaining free time is more than 0, if remaining idle
Time is not more than 0, then whether abundance must all perform the task at once to regenerative resource；If remaining free time is more than 0,
Selection is under conditions of late start time is met, the task can use the period of regenerative resource optimal as its most
The execution time.Because using greedy algorithm, the decision-making for treating the latter task in scheduling queue is determined in previous task
Carried out on the basis of plan, so in the absence of the conflict of optimal exercising time；
Load delay dispatch situation after implementation steps 3 is as shown in Figure 5.There are three can postpone load in Fig. 5, be work respectively
Making 1, work 2 and work 3, Fig. 5 left figures is the power situation of initial regenerative resource and each work, wherein work 2 execution
Regenerative resource can not be used, Fig. 5 right figures are the power situations of regenerative resource after load delay algorithm and each work,
Wherein work and 2 be deferred to before the cut-off target date and can maximize the period using regenerative resource.
In general, the present invention is one by calculating optimal power supply storage device discharge and recharge strategy so as to gentle renewable
Energy fluctuation and then the method that renewable energy utilization rate is maximized by load dispatch.This method is broadly divided into two steps
Suddenly, first step is regenerative resource smoothing, and the module obtains power storage by solving Solution of Nonlinear Optimal Problem
The optimal discharge and recharge scheme of equipment, makes the final regenerative resource for data center's energy supply in day part (for example, one hour)
Power variance value it is minimum；Second step is load adaptation, is a kind of load delay scheme based on greedy algorithm, and it is can
On the basis of renewable sources of energy smoothing, the effect maximized using regenerative resource is realized by dispatching ductile load.Make
Smoothed with the regenerative resource realized of the present invention, can in the case where the power storage equipment of huge capacity need not be required,
The effectively simply fluctuation of gentle regenerative resource, so as to ensure the stability of power network and data center, while reducing frequency
The operation overhead of numerous power supply source transfer zone；And follow-up load adaptation can significantly improve the regenerative resource of data center
Utilization rate.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, it is not used to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the invention etc., it all should include
Within protection scope of the present invention.
Claims (4)
1. a kind of data center's regenerative resource smooths method of supplying power to, it is characterised in that the described method comprises the following steps：
(1) regenerative resource is smoothed：Differentiate whether regenerative resource power variance used in current electric grid is more than or equal to predetermined
Threshold value, is then to assert that regenerative resource power supply is in the fluctuation energy supply stage, goes to step (2)；Otherwise to stablize the energy supply stage, step is turned
Suddenly (3)；
(2) it is electrically operated by the electrical energy storage progress charge and discharge in data center's electric power system, by the confession of following smooth operations
The fluctuation that regenerative resource is energized in the energy stage, then goes to step (3)；
Smooth operation is as follows：Each period for belonging to the fluctuation energy supply stage is carried out smoothly respectively；The holding period is taken to power
Stable optimal electrical power storage device discharge and recharge strategy；The strategy determines in each granularity time that electrical energy storage should
Electric discharge or the general power of charging, so that within each period, the regenerative resource for being finally supplied to data center is smooth
Stable；
(3) load adaptation：Using the load delay algorithm based on greedy algorithm, the task load in system is classified and sorted；
The task load is divided into two classes, and a class is real time load, and another kind of is that can postpone load；
It is immediately performed for real time load；
Pair can be delayed load by can delay time sort from small to large, meeting the late start time required by task load
Under the conditions of, ductile task load is deferred to the load and run using regenerative resource most period.
2. a kind of data center's regenerative resource smoothing method of supplying power to according to claim 1, it is characterised in that described
Threshold is as follows in step (1)：
The threshold value is, according to local regenerative resource historical data and prediction data, to take power supply period regenerative resource general power side
The 20%-30% of difference is as stablizing the energy supply stage；
The period refers to the time interval for being divided into power-on time by fixed duration, and fixed duration is desirable 30-90 minutes.
3. a kind of data center's regenerative resource smoothing method of supplying power to according to claim 1, it is characterised in that described
In step (2), electrical energy storage realizes smooth power supply using optimal discharge and recharge strategy, comprises the following steps that：
By the period of each regenerative resource power supply, by the fixation duration of 1-10 minutes, m time granularity is divided into；U=
(u1u2...um) represent renewable energy power generation general power on each time granularity；S=(s1s2...sm)TRepresent each time grain
Electrical energy storage is by the power of regenerative resource charge or discharge on degree；Wherein siJust to represent in the i-th time granularity battery
Electric discharge | si|, for supplementing current insufficient regenerative resource；siThen represent to fill in the i-th time granularity regenerative resource to be negative
Foot, charges to battery | si|；A=U+S, i.e.,
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For each time granularity is after battery charge or discharge operation within the period, can finally be provided to data center can be again
The power of the raw energy；
To object function σAMinimizing, for smoothing the period regenerative resource, so that charging or putting by battery
Regenerative resource fluctuation variance after electrically optimized is minimum, that is, Solution of Nonlinear Optimal Problem as follows is solved, so as to obtain
A：
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<mn>1</mn>
<mi>m</mi>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>m</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>a</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<mi>&mu;</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
1
Each variable bound condition of above object function is：
<mrow>
<mo>&ForAll;</mo>
<mi>i</mi>
<mo>&Element;</mo>
<mo>&lsqb;</mo>
<mn>1</mn>
<mo>,</mo>
<mi>m</mi>
<mo>&rsqb;</mo>
<mo>,</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<mo>|</mo>
<msub>
<mi>s</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<mo>&le;</mo>
<mn>0.9</mn>
<mi>M</mi>
<mo>,</mo>
<msub>
<mi>s</mi>
<mi>i</mi>
</msub>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<mo>|</mo>
<msub>
<mi>s</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<mo>&le;</mo>
<msub>
<mi>u</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<msub>
<mi>s</mi>
<mi>i</mi>
</msub>
<mo><</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
<mrow>
<mo>&ForAll;</mo>
<mi>i</mi>
<mo>&Element;</mo>
<mo>&lsqb;</mo>
<mn>1</mn>
<mo>,</mo>
<mi>m</mi>
<mo>&rsqb;</mo>
<mo>,</mo>
<mn>0.1</mn>
<mi>M</mi>
<mo>&le;</mo>
<mo>|</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>i</mi>
</munderover>
<msub>
<mi>s</mi>
<mi>t</mi>
</msub>
<mo>|</mo>
<mo>&le;</mo>
<mi>M</mi>
</mrow>
Wherein M is the maximum capacity for the electrical energy storage being equipped with；μ is uiThe arithmetic mean of instantaneous value of (i ∈ [1, m]),Represent to appoint
Take；
The σ made according to obtaining in object functionAReach the battery charging and discharging power of minimum value | si|, you can obtain power storage and set
Standby charge-discharge electric power S.
4. a kind of data center's regenerative resource smoothing method of supplying power to according to claim 1, it is characterised in that described
In step (3), load delay algorithm is comprised the following steps that：
Each task energy quantity to be consumed in calculating task load data collection；
Set up task scheduling queue, by each task by its can delay time sort from small to large, be inserted into task scheduling queue
In, wherein can delay time be remaining free time, its Late Finish for being defined as each mission requirements subtracts the task
The run time and current time needed；The each task in scheduling queue is treated by FIFO sequential scheduling, i.e., to the time more
Load delay algorithm is performed for urgent priority of task, the task actual execution time is determined with this；
Specifically, for each the intending performing of the task, first judge whether its remaining free time is more than 0, if remaining free time
No more than 0, then whether abundance must all perform the task at once to regenerative resource；If remaining free time is more than 0, selection
Under conditions of late start time is met, the task period of regenerative resource can be used optimal to be performed as its most
Time.
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| CN103138227A (en) * | 2013-02-06 | 2013-06-05 | 上海交通大学 | Power distribution network fast power restoration method containing distributed power connected grid |
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| CN103138227A (en) * | 2013-02-06 | 2013-06-05 | 上海交通大学 | Power distribution network fast power restoration method containing distributed power connected grid |
| CN105305480A (en) * | 2015-07-13 | 2016-02-03 | 陕西省地方电力（集团）有限公司 | Hybrid energy-storage DC micro grid hierarchical control method |
| CN105322550A (en) * | 2015-08-28 | 2016-02-10 | 南方电网科学研究院有限责任公司 | Method for optimizing operation of household micro-grid |
| CN105262098A (en) * | 2015-10-23 | 2016-01-20 | 海南电网有限责任公司 | Agile automatic voltage control method based on wind farm generated power fluctuating assessment |
| CN106022973A (en) * | 2016-07-04 | 2016-10-12 | 国网江苏省电力公司扬州供电公司 | Greedy algorithm-based scheduling policy for three-phase load balance of real-time-allocating distribution network |
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