CN107248755B - A kind of data center's renewable energy smoothing method of supplying power to - Google Patents
A kind of data center's renewable energy smoothing method of supplying power to Download PDFInfo
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- CN107248755B CN107248755B CN201710609143.6A CN201710609143A CN107248755B CN 107248755 B CN107248755 B CN 107248755B CN 201710609143 A CN201710609143 A CN 201710609143A CN 107248755 B CN107248755 B CN 107248755B
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000009499 grossing Methods 0.000 title claims abstract description 14
- 230000006978 adaptation Effects 0.000 claims abstract description 10
- 238000004146 energy storage Methods 0.000 claims description 13
- 230000001172 regenerating effect Effects 0.000 claims description 9
- 238000013480 data collection Methods 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
- 230000003111 delayed effect Effects 0.000 description 2
- 238000005265 energy consumption 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
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
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- 239000002803 fossil fuel Substances 0.000 description 1
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Classifications
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- H02J3/382—
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- H02J3/383—
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- 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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Abstract
The invention discloses a kind of data center's renewable energy to smooth method of supplying power to: renewable energy smooths module and obtains the best charge and discharge scheme of power storage equipment by solving Solution of Nonlinear Optimal Problem, makes finally minimum for fluctuation of the renewable energy of data center's energy supply in day part (such as one hour)；Loading adaptation module is a kind of load delay scheme based on greedy algorithm, on the basis of renewable energy smoothing, is realized by the ductile load of scheduling and maximizes the effect for using renewable energy.The fluctuation of renewable energy can be effectively relieved in the method for the present invention, and realizes under the steady supply situation of renewable energy and maximumlly use renewable energy.
Description
Technical field
The invention belongs to consumption of data center technical fields, flat more particularly, to a kind of data center's renewable energy
Cunningization method of supplying power to.
Background technique
With the continuous development of cloud computing technology, the computing capability of data center is rapidly increasing with scale, therewith
The high-power energy consumption come brings two serious consequences: firstly, data center, which buys power, will bring huge electricity charge expense；Its
Secondary, data center still depends on obtain the energy from power grid at present, is produced by coal intensity fossil fuel
Raw major part power, huge energy consumption, which will lead to negative environment, to be influenced, and Global Greenhouse Effect is accelerated.
Due to renewable energy (such as wind energy, solar energy) it is inexpensive, pollution-free the features such as, more and more companies start
Construction parts or all by the data center of regenerative resource power supply.Using renewable energy be data center power supply 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 renewable energy can challenge the stability of power grid and data center, while frequent transitions energy supply source can also increase
Add operation expense；(2) intermittence of renewable energy can reduce its utilization rate.
However, existing most variations can not all handle first challenge well, the renewable energy for neglecting fluctuation is supplied
The impact of power grid and data center should be brought, and some work are all stored in doing for power storage equipment using by renewable energy
Method eliminates fluctuation, but this needs huge battery capacity.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, it is flat that the present invention provides a kind of data center's renewable energy
Cunningization method of supplying power to, this method are suitable for utilization (such as wind energy, solar energy) of the data center to multiple renewable energy sources, woth no need to
Seek huge battery capacity, can effectively gentle renewable energy fluctuation, and it is real under the steady supply situation of renewable energy
Now maximumlly use renewable energy.
The present invention proposes a kind of data center's renewable energy smoothing method of supplying power to, comprising the following steps:
(1) renewable energy smooths: it is pre- to differentiate whether renewable energy power variance used in current electric grid is more than or equal to
Fixed threshold value is 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) electrically operated by the electrical energy storage progress charge and discharge in data center's power supply system, by following smooth operations
The fluctuation that renewable energy energizes in the energy supply stage, then goes to step (3)；
Smooth operation is as follows: carrying out respectively smoothly to each period (for example, one hour) for belonging to the fluctuation energy supply stage；It can
Renewable sources of energy prediction data is generally with 5 minutes or 1 minute for granularity, at (such as the 0th point of each hour of beginning of each period
Clock) carry out the period smooth tactful calculating；It takes and keeps the stable optimal electrical power storage equipment charge and discharge plan of period power supply
Slightly；The strategy has determined in each granularity time the total work that (such as five minutes) electrical energy storage should discharge or charge
Rate, so that being finally supplied to the renewable energy of data center is smooth steady within each period；
(3) load adaptation: using the load delay algorithm based on greedy algorithm, classifies to the task load in system and arranges
Sequence；
The task load is divided into two classes, and one kind is real time load, such as Web request；Another kind of is that can postpone to load, and is such as criticized
Processing task, scientific algorithm；
Real time load is immediately performed；To 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 renewable energy
Most period operations；
The threshold value, for dividing powering phase: energizing historical data and renewable according to place power grid renewable energy
The energy energizes prediction data, calculates renewable energy power variance, determines the threshold value for dividing the stage；When a period of time (example
Such as, one hour) variance yields of the power of interior renewable energy energy supply when being less than the threshold value, assert that the period belongs to and stablizes energy supply rank
Section, renewable energy itself is more steady at this time；When variance yields is more than or equal to the threshold value, assert that the period belongs to fluctuation energy supply
Stage.Renewable energy 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 grid renewable energy overall condition of analysis with threshold value；With prediction data when specific utilization
To carry out divided stages；
Preferably, Threshold is as follows in the step (1):
The threshold value is to calculate each power supply period renewable energy according to local renewable energy historical data and prediction data
General power variance yields takes the power supply period of the lesser preceding 20%-30% of variance yields to be used as and stablizes 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 30-90 minutes desirable.
Since the prediction taken or historical data are usually with 1 minute or 5 minutes for granularity, in contrast 1 hour data amount compares
Properly, it (such as one hour) to be smoothed during this period of time later, 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 charge and discharge strategy, specifically
Steps are as follows:
The period of each regenerative resource power supply is divided into m time granularity by 1-10 minutes fixation durations.For example,
Period is 60 minutes, when a length of 5 minutes when fixed, m 12.U=(u1 u2...um) indicate on each time granularity (for example,
5 minutes) renewable energy power generation general power；S=(s1 s2...sm)TIndicate that electrical energy storage quilt can on each time granularity
The power of renewable sources of energy charge or discharge；Wherein siExpression be positive in the i-th time granularity battery discharge | si|, it is current for supplementing
Insufficient renewable energy；siBeing negative then indicates sufficient in the i-th time granularity renewable energy, charges to battery | si|；A=U
+ S, i.e.,
It is time granularity each within the period after battery charge or discharge operation, can finally be provided to data center
The power of renewable energy；Finally being supplied to the renewable energy source power of data center is U+S, i.e., after battery operates
Renewable energy source power.
To objective function σAMinimizing, for smoothing the period renewable energy, so that being filled by battery
Renewable energy fluctuation variance after electricity or electric discharge optimization is minimum, that is, solves Solution of Nonlinear Optimal Problem as follows, from
And obtain A:
Above each variable bound condition of objective function are as follows:
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]),Table
Show to appoint and take；
According to finding out the σ made in objective functionAReach the battery charging and discharging power of minimum value | si|, electric energy can be obtained and deposit
Store up the charge-discharge electric power S of equipment.There is battery capacity to be less than the constraint of capacity 90% in constraint condition；Stablize the energy supply stage simultaneously
Do not execute 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), specific step is as follows for load delay algorithm:
Each task energy quantity to be consumed in calculating task load data collection；
Establish task schedule queue, by each task by its can delay time sort from small to large, be inserted into task schedule
In queue, wherein can delay time be remaining free time, the Late Finish for being defined as each mission requirements subtracts this
The runing time and current time that task needs；The each task in scheduling queue, i.e. clock synchronization are waited for by first in, first out sequential scheduling
Between more urgent i.e. free time few task preferentially execute load delay algorithm, when determining the actual execution of the task with this
Between；
Specifically, for the task of each quasi- execution, first judge whether its remaining free time is greater than 0, if remaining idle
Time is not more than 0, then no matter whether renewable energy is sufficient must all execute the task at once；If remaining free time is greater than 0,
It selects under conditions of meeting late start time, the task can use most the period of renewable energy optimal as its
Execute the time.Because the decision to the latter task in scheduling queue is determined in previous task using greedy algorithm
It is carried out on the basis of plan, so the conflict of optimal exercising time is not present.
The present invention is one and stores equipment charge and discharge strategy by calculating optimal power supply to which gentle renewable energy fluctuates
Property, and then by load dispatch maximization renewable energy utilization rate method.This method is broadly divided into two steps, and first
Step is renewable energy smoothing, which obtains the best of power storage equipment by solving Solution of Nonlinear Optimal Problem
Charge and discharge scheme, make finally for data center energy supply renewable energy 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, smooth in renewable energy
On the basis of change, the effect maximized using renewable energy is realized by dispatching ductile load.
In general, through the invention it is contemplated above technical scheme is compared with the prior art, have the advantage that
It is smoothed using the renewable energy that the present invention realizes, it can be in the power storage equipment without requiring huge capacity
In the case where, the effectively simply fluctuation of gentle renewable energy, to guarantee the stability of power grid and data center, together
When reduce frequently power supply source convert bring operation overhead；And subsequent load adaptation can significantly improve data center can
Utilization of regenerative energy rate.
Detailed description of the invention
Fig. 1 is the overall flow figure of the method for the present invention；
Fig. 2 is renewable energy divided stages schematic diagram and renewable energy and load situation of change signal of the invention
Figure；
Fig. 3 is that the present invention implements the renewable energy source power effect diagram after renewable energy smoothing step；
Fig. 4 is the flow chart of the load adaptation method the present invention is based on smooth renewable energy；
Fig. 5 be the present invention implement load adaptation step after load delay scheduling and initial load situation schematic diagram.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below that
Not constituting conflict between this can be combined with each other.
As shown in Figure 1, data center's renewable energy smoothing method of supplying power to of the embodiment of the present invention includes the following steps:
Step 1: dividing powering phase: historical data being energized according to place power grid renewable energy and renewable energy energizes
Prediction data calculates renewable energy power variance, determines 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 renewable energy energy supply is less than the threshold value, assert that the period belongs to the stable energy supply stage, at this time may be used
Renewable sources of energy itself are more steady；When variance yields is more than or equal to the threshold value, assert that the period belongs to the fluctuation energy supply stage.It 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 grid renewable energy overall condition of analysis is intended merely to threshold value；It is specific with when rank carried out with prediction data
Section divides；
Specifically, Threshold is as follows:
The threshold value is to calculate each power supply period renewable energy according to local renewable energy historical data and prediction data
General power variance yields takes the power supply period of the lesser preceding 20%-30% of variance yields to be used as and stablizes 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 30-90 minutes desirable.
Since the prediction taken or historical data are usually with 1 minute or 5 minutes for granularity, in contrast 1 hour data amount compares
Properly, it (for example, one hour) to be smoothed during this period of time later, the period is longer, may original fluctuation situation
Can be bigger, battery capacity is also required to bigger；
Renewable energy divided stages situation and renewable energy and load situation of change are as shown in Figure 2.
Step 2: it is described renewable energy smoothing: to differentiate whether renewable energy power variance used in current electric grid is greater than
Threshold value is to assert that regenerative resource power supply is in the fluctuation energy supply stage, passes through the power storage in data center's power supply system
Equipment carries out the fluctuation that charge and discharge is electrically operated, and renewable energy energizes in the smooth energy supply stage；Otherwise 3 are gone to step；
Smooth operation is as follows: carrying out respectively smoothly to each period (such as one hour) for belonging to the fluctuation energy supply stage；It can
Renewable sources of energy prediction data is generally with 5 minutes or 1 minute for granularity, at (such as the 0th point of each hour of beginning of each period
Clock) carry out the period smooth tactful calculating；It takes and keeps the stable optimal electrical power storage equipment charge and discharge plan of period power supply
Slightly；The strategy has determined in each granularity time the total work that (such as five minutes) electrical energy storage should discharge or charge
Rate, so that being finally supplied to the renewable energy of data center is smooth steady within each period；
Specifically, the step of electrical energy storage realizes smooth power supply using optimal charge and discharge strategy is as follows:
The period of each regenerative resource power supply is divided into m time granularity by 1-10 minutes fixation durations.For example,
Period is 60 minutes, when a length of 5 minutes when fixed, m 12.U=(u1u2...um) indicate on each time granularity (for example, 5
Minute) renewable energy power generation general power；S=(s1 s2...sm)TIndicate that electrical energy storage quilt can be again on each time granularity
The power of raw energy charge or discharge；Wherein siExpression be positive in the i-th time granularity battery discharge | si|, for supplementing currently not
Sufficient renewable energy；siBeing negative then indicates sufficient in the i-th time granularity renewable energy, charges to battery | si|；A=U+
S, i.e.,
It is time granularity each within the period after battery charge or discharge operation, can finally be provided to data center
The power of renewable energy；Finally being supplied to the renewable energy source power of data center is U+S, i.e., after battery operates
Renewable energy source power.
To objective function σAMinimizing, for smoothing the period renewable energy, so that being filled by battery
Renewable energy fluctuation variance after electricity or electric discharge optimization is minimum, that is, solves Solution of Nonlinear Optimal Problem as follows, from
And obtain A:
Above each variable bound condition of objective function are as follows:
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]),Table
Show to appoint and take；
According to finding out the σ made in objective functionAReach the battery charging and discharging power of minimum value | si|, electric energy can be obtained and deposit
Store up the charge-discharge electric power S of equipment.There is battery capacity to be less than the constraint of capacity 90% in constraint condition；Stablize the energy supply stage simultaneously
Do not execute 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, classifies to the task load in system
And sequence；
The task load is divided into two classes, and one kind is real time load, such as Web request；Another kind of is that can postpone to load, and is such as criticized
Processing task, scientific algorithm；
Real time load is immediately performed；To 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 renewable energy
Most period operations；
As shown in figure 4, specific step is as follows for load delay algorithm: each task will consume in calculating task load data collection
Energy quantity；
Establish task schedule queue, by each task by its can delay time sort from small to large, be inserted into task schedule
In queue, wherein can delay time be remaining free time, the Late Finish for being defined as each mission requirements subtracts this
The runing time and current time that task needs；The each task in scheduling queue, i.e. clock synchronization are waited for by first in, first out sequential scheduling
Between more urgent i.e. free time few task preferentially execute load delay algorithm, when determining the actual execution of the task with this
Between；
Specifically, for the task of each quasi- execution, first judge whether its remaining free time is greater than 0, if remaining idle
Time is not more than 0, then no matter whether renewable energy is sufficient must all execute the task at once；If remaining free time is greater than 0,
It selects under conditions of meeting late start time, the task can use most the period of renewable energy optimal as its
Execute the time.Because the decision to the latter task in scheduling queue is determined in previous task using greedy algorithm
It is carried out on the basis of plan, so the conflict of optimal exercising time is not present；
Load delay dispatch situation after implementation steps 3 is as shown in Figure 5.It is work respectively there are three that can postpone to load in Fig. 5
Make 1, work 2 and work 3, Fig. 5 left figure be the power situation of initial renewable energy and each work, wherein work 2 execution
Renewable energy cannot be used, Fig. 5 right figure is the power situation of the renewable energy and each work after load delay algorithm,
It wherein works and 2 has been deferred to before ending the target date period that can be maximized using renewable energy.
In general, the present invention is one by calculating optimal power supply storage equipment charge and discharge strategy 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 renewable energy smoothing, which obtains power storage by solving Solution of Nonlinear Optimal Problem
The best charge and discharge scheme of equipment makes to be finally the renewable energy of 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, can
On the basis of renewable sources of energy smoothing, realize that maximization uses the effect of renewable energy by dispatching ductile load.Make
With the present invention realize renewable energy smoothing, can without require huge capacity power storage equipment in the case where,
The effectively simply fluctuation of gentle renewable energy to guarantee the stability of power grid and data center, while reducing frequency
Convert bring operation overhead in numerous power supply source；And subsequent load adaptation can significantly improve the renewable energy 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, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (3)
1. a kind of data center's renewable energy smooths method of supplying power to, which is characterized in that the described method comprises the following steps:
(1) renewable energy smooths: it is scheduled to differentiate whether renewable energy power variance used in current electric grid is more than or equal to
Threshold value is 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, turn step
Suddenly (3)；
(2) electrically operated by the electrical energy storage progress charge and discharge in data center's power supply system, by following smooth operations wave
The fluctuation of renewable energy energy supply, then goes to step (3) in the dynamic energy supply stage；
Smooth operation is as follows: carrying out respectively smoothly to each period for belonging to the fluctuation energy supply stage；It takes and keeps period power supply
Stable optimal electrical power stores equipment charge and discharge strategy；The strategy has determined that electrical energy storage should in each granularity time
The general power of electric discharge or charging, so that it is smooth for being finally supplied to the renewable energy of data center within each period
Stable；
Smooth power supply is realized using optimal charge and discharge strategy, the specific steps are as follows:
The period of each regenerative resource power supply is divided into m time granularity by 1-10 minutes fixation durations；U=(u1 u2
... um) indicate renewable energy power generation general power on each time granularity；S=(s1 s2 ... sm)TIndicate each time grain
Electrical energy storage is by the power of renewable energy charge or discharge on degree；Wherein siExpression be positive in the i-th time granularity battery
Electric discharge | si|, for supplementing current insufficient renewable energy；siIt is negative, expression is filled in the i-th time granularity renewable energy
Foot charges to battery | si|；A=U+S, i.e.,
It is time granularity each within the period after battery charge or discharge operation, can finally be provided to data center can be again
The power of the raw energy；
To objective function σAMinimizing, for smoothing the period renewable energy, so that charging or putting by battery
Renewable energy fluctuation variance after electrically optimized is minimum, that is, Solution of Nonlinear Optimal Problem as follows is solved, to obtain
A:
Above each variable bound condition of objective function are as follows:
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]),It indicates to appoint
It takes；
According to finding out the σ made in objective functionAReach the battery charging and discharging power of minimum value | si|, power storage can be obtained and set
Standby charge-discharge electric power S；
(3) load adaptation: using the load delay algorithm based on greedy algorithm, classifies to the task load in system and sorts；
The task load is divided into two classes, and one kind is real time load, and another kind of is that can postpone to load；
Real time load is immediately performed；
To can postpone load by can delay time sort from small to large, meeting late start time required by task load
Under the conditions of, ductile task load is deferred to the load and is run using renewable energy most period.
2. a kind of data center's renewable energy according to claim 1 smooths method of supplying power to, which is characterized in that described
Threshold is as follows in step (1):
The threshold value is to take power supply period renewable energy general power side according to local renewable energy historical data and prediction data
The 20%-30% of difference, which is used as, stablizes 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 30-90 minutes desirable.
3. a kind of data center's renewable energy according to claim 1 smooths method of supplying power to, which is characterized in that described
In step (3), specific step is as follows for load delay algorithm:
Each task energy quantity to be consumed in calculating task load data collection；
Establish task schedule queue, by each task by its can delay time sort from small to large, be inserted into task schedule queue
In, wherein can delay time be remaining free time, the Late Finish for being defined as each mission requirements subtracts the task
The runing time and current time needed；The each task in scheduling queue is waited for by first in, first out sequential scheduling, i.e., more to the time
Load delay algorithm is preferentially executed for urgent task, the task actual execution time is determined with this；
Specifically, for the task of each quasi- execution, first judge whether its remaining free time is greater than 0, if remaining free time
No more than 0, then no matter whether renewable energy is sufficient must all execute the task at once；If remaining free time is greater than 0, selection
Under conditions of meeting late start time, the task period of renewable energy can be used most as its optimal execution
Time.
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| 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 |
| CN105322550B (en) * | 2015-08-28 | 2018-03-16 | 南方电网科学研究院有限责任公司 | A kind of optimization method of household micro-capacitance sensor operation |
| CN105262098B (en) * | 2015-10-23 | 2017-12-12 | 海南电网有限责任公司 | The quick automatic voltage control method assessed based on the fluctuation of wind power plant generated output |
| CN106022973B (en) * | 2016-07-04 | 2019-08-30 | 国网江苏省电力有限公司扬州供电分公司 | A kind of scheduling strategy of the real-time distribution distribution three-phrase burden balance based on greedy algorithm |
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