CN110311424A - A kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load - Google Patents
A kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load Download PDFInfo
- Publication number
- CN110311424A CN110311424A CN201910422270.4A CN201910422270A CN110311424A CN 110311424 A CN110311424 A CN 110311424A CN 201910422270 A CN201910422270 A CN 201910422270A CN 110311424 A CN110311424 A CN 110311424A
- Authority
- CN
- China
- Prior art keywords
- energy storage
- power
- energy
- net load
- prediction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- 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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
-
- 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
-
- 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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
A kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load, the method steps are as follows: step 1: based on net load prediction result a few days ago, through objective function optimization obtain energy-storage system SOC sequence and peak regulation after dominant eigenvalues, complete energy storage energy it is flow-optimized；Step 2: dominant eigenvalues after peak regulation obtained in the first step are extended to contact power interval；Step 3: SOC sequence obtained in net load power and the first step based on the accuracy in a few days rolling forecast higher than precision of prediction a few days ago corrects the actual charge/discharge power of energy-storage system in the dominant eigenvalues section of second step completes energy storage peak shaving control.The present invention predicts that ultra-short term rolling forecast is that energy storage setting charge-discharge electric power provides more accurate reference compared to net load a few days ago, has given full play to that energy storage is quick, flexible handling capacity, keeps dominant eigenvalues after peak regulation more smooth, peak regulation pressure has been effectively relieved.
Description
Technical field
The energy storage peak shaving control method based on prediction that the present invention relates to a kind of, more particularly to it is a kind of net based on multiple time scale model
The energy storage peak shaving control method of load prediction.
Background technique
Demand-side power peak-valley difference expands year by year in recent years, has the wind-powered electricity generation of intermittent, randomness and anti-tune peak character big
The grid-connected peak regulation pressure for exacerbating system of scale, traditional power grid due to lack flexible peak regulation resource be difficult to dissolve large area it is grid-connected
Wind power resources and lead to serious wind-abandoning phenomenon.To guarantee that sufficiently consumption wind-powered electricity generation provides while power grid security reliability service
Extensive energy-accumulating power station that achievable quick, flexible power is handled up mostly has been established as peak regulation resource in source at present, and charge and discharge are excellent
Changing adjusting is that energy-storage system participation peak regulation control must solve the problems, such as.
Summary of the invention
Goal of the invention:
The invention proposes a kind of energy storage peak shaving control methods based on the prediction of multiple time scale model net load, and the purpose is to excellent
The energy distribution of energy-storage system during change peak regulation.
Technical solution:
A kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load, it is characterised in that: this method step
It is as follows:
Step 1: obtaining the SOC sequence and tune of energy-storage system through objective function optimization based on net load prediction result a few days ago
It is flow-optimized to complete energy storage energy for dominant eigenvalues behind peak；
Step 2: dominant eigenvalues after peak regulation obtained in the first step are extended to contact power interval；
Step 3: based on accuracy it is high than precision of prediction a few days ago (be primarily referred to as precision of prediction height, exact level can because count
According to different difference it is larger.But day interior prediction all can be higher than precision of prediction a few days ago under normal conditions.) in a few days rolling forecast
It is actual that SOC sequence obtained in net load power and the first step corrects energy-storage system in the dominant eigenvalues section of second step
Charge/discharge power completes energy storage peak shaving control.
(it is a term for being often used in description time scale in prediction a few days ago, indicates to predict future for 24 hours at the 0:00 moment
The case where.In a few days: it is 4h that statement time scale is often used in prediction, and the ultra-short term that resolution ratio is 15min or 1h is predicted.Herein
Middle temporal resolution is 15min)
Flow-optimized the specific method is as follows for energy storage energy in the first step:
(1) based on power distribution network historical load power and power distribution network history correspond to the moment (point at the same time (on the period,
What is taken in actual power measurement is the average value of the period), wind power corresponding with load power.) wind power
The prediction a few days ago of load and wind power is carried out respectively, and calculates net load predicted value a few days ago(history is frequent in prediction
Past 1 year, several months or several weeks etc. of band are used to refer to, historical data is mainly used for training and the Qualify Phase of prediction)；
(2) with the net load predicted value a few days ago in (one) stepBased on carry out energy storage charge/discharge power sequence
Optimize calculation optimization energy storage power flow, obtains the dominant eigenvalues P after energy storage peak shavingGWith the SOC sequence of energy-storage system.
(1) the net load predicted value a few days ago of the calculating in stepMode it is as follows:
Wherein,For load power predicted value a few days ago；For wind power prediction value a few days ago.
Dominant eigenvalues after optimization energy storage power flow described in step (2) is adjusted with energy storage are low flat to the maximum extent
For peak regulation target, shown in peak regulation objective function such as formula (1):
Wherein, N is the time step number in estimation range；For the predicted value a few days ago of t moment net load；PBIt (t) is day
The t moment energy storage charge/discharge power of preplanning.
After setting peak regulation target, the bound of energy storage charge and discharge safety value power is set to carrying out in energy storage charge and discharge process
Power constraint, power constraint relational expression may be expressed as:
Wherein, PBNFor the rated power of energy storage；△ t is sample time resolution；ηminAnd ηmaxRespectively set energy storage SOC
Minimum and maximum safety value；EtotFor energy storage total capacity；E (t) is the real surplus electricity of t moment energy storage.(ηminAnd ηmaxRespectively
For guarantee energy-storage system not over-discharge or do not overcharge and the energy-storage system SOC minimum value and maximum value that are arranged, generally
Constant 0.1 and 0.9 is taken respectively.)
According to optimization energy storage power flow, the dominant eigenvalues P after energy storage peak shaving is obtainedGOperation curve and energy-storage system
The mode of SOC sequence is as follows:
SOC(t)=SOC(t-1)+PB(t)Δt/Etot
Wherein, PGIt (t) is t moment dominant eigenvalues；SOCIt (t-1) was the SOC value of energy-storage system at the end of a upper period；
SOCIt (t) is the SOC value of energy-storage system at the end of current slot.
In second step by dominant eigenvalues after peak regulation obtained in the first step be extended to contact power interval mode it is as follows:
In dominant eigenvalues PGThreshold epsilon is added on the basis of operation curve1And ε2It constructs interconnection and runs power interval
[Pthrl,Pthrh], shown in computation rule such as formula (3):
Wherein, PthrlFor the lower limit of power interval；PthrhFor the upper limit of power interval；ε1And ε2The contact respectively set
Line is to up-and-down boundary vertical direction distance, ε1, ε2> 0.
The specific method is as follows for third step:
(A) load power of the based on power distribution network history and corresponding moment (point at the same time (on the period, actual function
What is taken in rate measurement is the average value of the period), wind power corresponding with load power.) wind power carry out respectively
Load and wind power in a few days (it is 4h that statement time scale is often used in prediction, and resolution ratio is the ultra-short term of 15min or 1h
Prediction) rolling forecast, and calculate in a few days net load rolling forecast value
(B) is based in (1) step the in a few days net load power of rolling forecastEnergy-storage system SOC sequence and building
Modify energy-storage system dominant eigenvalues P in dominant eigenvalues sectionGThe reference value of operation curve
(C) is according to modified reference valueThe charge/discharge power P of energy storage is acquired using following formulaBrea:
Step (B) reference valueCalculating the specific method is as follows:
1. taking the actual soc-value S of current time (actual measurement moment) energy-storage systemrea(t).If Srea(t)≤0.1||
Srea(t) >=0.9, energy storage is failure to actuate；If 0.1 < Srea(t) 0.9 <, into next step.
2. being calculated using following formula is to reach t+1 moment energy storage SOC value S in the next stage at current timeOC(t+1), it stores up
The charge/discharge power that can be needed
3. above-mentioned steps 2. on the basis of takeCharge/discharge power of the 1/d as next stage energy storageD is just
It is a constant, takes the 1/d of calculated result in 2.；
4. in conjunction in a few days net load rolling forecast valueNext stage interconnection is calculated with the contact power interval of setting
The reference value of power are as follows:
Wherein,For the ultra-short term predicted value of t+1 moment net load.
5. for the reference value for the next stage dominant eigenvalues being calculatedIn the power ginseng of formula (3) setting
The calculated result of formula (4) can be used directly in period in section.For the reference for the next stage system operation being calculated
ValueThe not period in the power ginseng section of formula (3) setting, ifSo reference value is set
For Pthrh(t+1)；IfSo reference value is set as Pthrl(t+1).Modified next stage system fortune
Row reference value are as follows:
。
The system includes energy storage energy stream optimization module, contact power interval expansion module and correction module；
After energy storage energy stream optimization module obtains SOC sequence and the peak regulation of energy-storage system based on net load prediction result a few days ago
It is flow-optimized to complete energy storage energy for dominant eigenvalues；
Contact power interval expansion module extends dominant eigenvalues after peak regulation obtained in energy storage energy stream optimization module
To get in touch with power interval；
Net load power and energy storage energy stream optimization module of the correction module based on rolling forecast in accuracy higher day
Obtained in SOC sequence contact power interval expansion module formed dominant eigenvalues section in amendment energy-storage system it is actual
Charge/discharge power completes energy storage peak shaving control.
Advantageous effect:
A kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load, this method are pre- including net load a few days ago
It surveys, in a few days ultra-short term net load prediction, energy storage energy is flow-optimized, construct dominant eigenvalues section and energy storage charge/discharge power is repaired
Positive five links.Power swing on interconnection can be effectively reduced using the energy storage peak shaving control method, reduce conventional power unit
Peak regulation pressure.
Flow-optimized the specific method is as follows for mentioned energy storage energy in the present invention:
It is primarily based on power distribution network historical load power and the wind power at corresponding moment carries out load and wind power respectively
Prediction a few days ago, and calculate net load predicted value a few days ago
Then the optimization that energy storage charge/discharge power sequence is carried out based on the prediction result a few days ago of net load calculates, and obtains
To the dominant eigenvalues P after energy storage peak shavingGThe SOC sequence of operation curve and energy storage.Wherein energy storage charge/discharge power sequence is excellent
Change the objective function of computation model are as follows:
Wherein, PBIt (t) is the t moment energy storage charge/discharge power of day preplanning.
Energy storage power constraints during charge/discharge are as follows:
Wherein, PBNFor the rated power of energy storage；△ t is sample time resolution；ηminAnd ηmaxRespectively set energy storage SOC
Minimum and maximum safety value；EtotFor energy storage total capacity；E (t) is the real surplus electricity of t moment energy storage.
Building dominant eigenvalues section specific method is mentioned in the present invention is, in dominant eigenvalues PGThe basis of operation curve
Upper addition threshold epsilon1And ε2It constructs interconnection and runs power interval [Pthrl,Pthrh], computation rule are as follows:
Wherein, PthrlFor the lower limit of power interval；PthrhFor the upper limit of power interval；ε1And ε2The contact respectively set
Line is to up-and-down boundary vertical direction distance, ε1, ε2> 0.
The specific method is as follows for mentioned energy storage charge/discharge power correction in the present invention:
The load power and the wind power at corresponding moment for being primarily based on power distribution network history carry out load and wind-powered electricity generation function respectively
The in a few days rolling forecast of rate, and calculate in a few days net load rolling forecast value
It is then based on the net load power of in a few days rolling forecastThe energy storage SOC sequence that day preplanning obtains and building
The reference value P of dominant eigenvalues section modification system operation curveref。
Wherein, reference value PrefCalculating the specific method is as follows:
1. obtaining the actual soc-value S of current time energy storagerea(t).If Srea(t)≤0.1||Srea(t) >=0.9, energy storage
It is failure to actuate；If 0.1 < Srea(t) 0.9 <, into next step.
2. calculate is the t+1 moment energy storage SOC value S for reaching day preplanning in the next stageOC(t+1), energy storage needs
Charge/discharge power
3. in order to there is better smooth effect in actual moving process, above-mentioned steps 2. on the basis of take1/
Charge/discharge power of the d as next stage energy storage
4. in conjunction in a few days net load rolling forecast valueNext stage system fortune can be calculated with the power ginseng section of setting
Capable reference value are as follows:
5. for the reference value for the next stage system operation being calculatedIn the power ginseng section of setting
The calculated result of above-mentioned formula can be used directly in period.For the reference value for the next stage system operation being calculatedThe not period in the power ginseng section of setting, ifSo reference value is set as Pthrh(t+
1)；IfSo reference value is set as Pthrl(t+1).Modified next stage system runs reference value
Are as follows:
Finally according to modified reference valueThe real-time charge/discharge power P of energy storage can be acquiredBrea。
The specific advantageous effect according to caused by above-mentioned method is as follows:
Present invention is primarily based on the predictions of multiple time scale model net load, and establish energy storage peak shaving model based on this.A few days ago
Prediction gives the variation tendency of in a few days net load, participates in peak regulation for energy storage and gives overall planning, compensates for ultra-short term rolling
The peak regulation curve extension cooked up is dominant eigenvalues section to enhance it by the shortcomings that predicting perspective shortage, local optimum
Fault-tolerant ability；It is predicted compared to net load a few days ago, ultra-short term rolling forecast is arranged charge-discharge electric power for energy storage and provides more accurately
Reference, given full play to that energy storage is quick, flexible handling capacity, kept dominant eigenvalues after peak regulation more smooth, be effectively relieved
Peak regulation pressure.
Detailed description of the invention
Fig. 1 multiple time scale model peak regulation rapport figure
Fig. 2 PBrea(t+1) calculation flow chart
Fig. 3 peak regulation example effect diagram
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawing and by embodiment, and following embodiment is to this hair
Bright explanation and the invention is not limited to following embodiments.
As shown in Figure 1, calculating net load predicted value a few days ago according to the load of prediction and wind power first in last stage dayIgnore the transmission loss on route, net load calculation formula are as follows:
Wherein,For load power predicted value a few days ago；For wind power prediction value a few days ago.
Based on the net load power for predicting to acquire a few days agoDominant eigenvalues after being adjusted with energy storage are low flat to the maximum extent
For objective optimization energy storage power flow.I.e. in the net load trough period, energy storage absorbs superfluous energy from power grid and reduces thermal motor
Group participates in the downward depth of peak regulation, while releasing energy and preparing for the energy storage of wave crest period；In the net load wave crest period, energy storage is released
Leave with the energy of storage, reduces the movement range and stop frequency of fired power generating unit to a certain extent.
In order to reach above-mentioned peak regulation purpose, using the nonlinear property of quadratic function, while for the ease of using two
Secondary planning (QP) solves, and defines peak regulation catalogue and is designated as (objective function of energy storage charge/discharge power sequence optimization computation model):
Wherein, N is the time step number in estimation range, PBIt (t) is the t moment energy storage charge/discharge power of day preplanning.
The unit cost of energy storage at present is also higher, in practical engineering applications all in view of its capacity of economic factor and power
It has certain limitations, and in actual use it is also contemplated that the service life problem of energy storage, needs to set energy storage charge and discharge
The bound of safety value.Power constraint relational expression may be expressed as:
Wherein, PBNFor the rated power of energy storage；△ t is sample time resolution；ηminAnd ηmaxRespectively set energy storage SOC
Minimum and maximum safety value；EtotFor energy storage total capacity；E (t) is the real surplus electricity of t moment energy storage.
Then the dominant eigenvalues P after peak regulation can be calculated according to the energy storage charge/discharge power that optimization obtainsG, while can
To derive the SOC of day preplanning:
SOC(t)=SOC(t-1)+PB(t)Δt/Etot
Wherein, PGIt (t) is t moment dominant eigenvalues；SOC(t-1) SOC value for energy storage at the end of a upper period is (charged
State)；SOCIt (t) is the SOC value of energy storage at the end of current slot.
Based on the above research, energy storage charge/discharge power is obtained based on the prediction biggish prediction optimization a few days ago of error, is
To the sensitivity for predicting error when reducing the setting of smooth reference power, the dominant eigenvalues that the planning stage a few days ago is obtained extend
For power interval.I.e. in dominant eigenvalues PGThreshold epsilon is added on the basis of operation curve1And ε2It constructs interconnection and runs power area
Between [Pthrl,Pthrh], calculation formula are as follows:
Wherein, PthrlFor the lower limit of power interval；PthrhFor the upper limit of power interval；ε1And ε2The contact respectively set
Line is to up-and-down boundary vertical direction distance, ε1, ε2> 0.
Finally in a few days rolling adjusting stage, the net load power based on rolling forecast in accuracy higher dayDay
The reference value of the dominant eigenvalues section modification system operation curve for the energy storage SOC sequence and building that preplanning obtainsIn turn
Correct the charge/discharge power of energy storage.Specific makeover process is as shown in Figure 2.
1. obtaining the actual soc-value S of current time energy storagerea(t).If Srea(t)≤0.1||Srea(t) >=0.9, energy storage
It is failure to actuate；If 0.1 < Srea(t) 0.9 <, into next step.
2. calculate is the t+1 moment energy storage SOC value S for reaching day preplanning in the next stageOC(t+1), energy storage needs
Charge/discharge power
3. in order to there is better smooth effect in actual moving process, above-mentioned steps 2. on the basis of take1/
Charge/discharge power of the d as next stage energy storage
4. in conjunction in a few days net load rolling forecast valueNext stage system fortune can be calculated with the power ginseng section of setting
Capable reference value are as follows:
5. for the reference value for the next stage system operation being calculatedIn the power ginseng section of setting
The calculated result of above-mentioned formula can be used directly in period.For the reference value for the next stage system operation being calculatedThe not period in the power ginseng section of setting, ifSo reference value is set as Pthrh(t+
1)；IfSo reference value is set as Pthrl(t+1).Modified next stage system runs reference value
Are as follows:
According to modified reference value PrefThe real-time charge/discharge power P of energy storage can be acquiredBrea。
A kind of energy storage peak shaving control system based on the prediction of multiple time scale model net load, which includes that energy storage energy stream is excellent
Change module, contact power interval expansion module and correction module；
After energy storage energy stream optimization module obtains SOC sequence and the peak regulation of energy-storage system based on net load prediction result a few days ago
It is flow-optimized to complete energy storage energy for dominant eigenvalues；
Contact power interval expansion module extends dominant eigenvalues after peak regulation obtained in energy storage energy stream optimization module
To get in touch with power interval；
Net load power and energy storage energy stream optimization module of the correction module based on rolling forecast in accuracy higher day
Obtained in SOC sequence contact power interval expansion module formed dominant eigenvalues section in amendment energy-storage system it is actual
Charge/discharge power completes energy storage peak shaving control.
Below with reference to specific implementation object the present invention is described in detail:
The wind energy turbine set installed capacity C accessed in distribution systemap=50MW, wind-powered electricity generation permeability is close to 10%.System matches storage
Energy capacity is EBN=40MWh, ηmaxAnd ηmin0.9 and 0.1, rated power P are taken respectivelyBN=20MW.Data sampling time
Differentiate △ t=15min, i.e., daily sampling number N=96.Power interval threshold epsilon is taken herein1=ε2=5, tracking day preplanning
Step number d=4 set by the track SOC randomly selects three days data and is verified, and operation result is as shown in Figure 3.
Fig. 3 (a), (b) and (c) show respectively same day actual measurement net load, foundation dominant eigenvalues section and make
With the power curve after mentioned dual-time peak regulating method.Peak is in from can be seen that load between 1-5 point in the morning in figure (a)
In paddy period, energy storage absorbs superfluous energy, by taking the fired power generating unit of 300WM as an example, the downward depth of unit can be made to reduce 5% left
It is right.Occur net load peak period three times in the time later, effectively reduces 6:00 AM and at night 22 points of peak value
Period power also plays beneficial reduction to net load wave crest using mentioned dual-time peak regulation strategy in figure (b) and (c) and makees
With.And based on set power interval, there are horizontal linear power periods after peak regulation.The smoothness of dominant eigenvalues after peak regulation
Become surveying the 23.3%, 47.9% and 43.2% of net load respectively, wherein smoothness calculation formula are as follows:
Wherein, Sm--- the day smoothness of power curve.
Power swing on interconnection can be effectively reduced using the energy storage peak shaving control method, reduce the peak regulation of conventional power unit
Pressure.
Embodiments herein can provide as method, system or computer program product.Therefore, the application can be used
The form of full hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects.Moreover, the application can
Using one or more wherein include the computer-usable storage medium of computer usable program code (including but not limited to
Magnetic disk storage, CD-ROM, optical memory etc.) on the form of computer program product implemented.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Claims (9)
1. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load, it is characterised in that: this method step is such as
Under:
Step 1: based on net load prediction result a few days ago, after objective function optimization obtains SOC sequence and the peak regulation of energy-storage system
It is flow-optimized to complete energy storage energy for dominant eigenvalues；
Step 2: dominant eigenvalues after peak regulation obtained in the first step are extended to contact power interval；
Step 3: being obtained in net load power and the first step based on the accuracy in a few days rolling forecast higher than precision of prediction a few days ago
SOC sequence correct the actual charge/discharge power of energy-storage system in the dominant eigenvalues section of second step and complete energy storage peak shaving
Control.
2. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 1, special
Sign is: flow-optimized the specific method is as follows for energy storage energy in the first step:
(1) wind power based on power distribution network historical load power and corresponding power distribution network historical juncture carries out load and wind respectively
The prediction a few days ago of electrical power, and calculate net load prediction result a few days ago
(2) with the net load prediction result a few days ago in (one) stepBased on carry out energy storage charge/discharge power sequence optimization
Calculation optimization energy storage power flow obtains the dominant eigenvalues P after energy storage peak shavingGWith the SOC sequence of energy-storage system.
3. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 2, special
Sign is: optimizing the dominant eigenvalues after energy storage power flow is adjusted with energy storage described in step (2), low put down is to the maximum extent
Peak regulation target, shown in peak regulation objective function such as formula (1):
Wherein, N is the time step number in estimation range；For the predicted value a few days ago of t moment net load；PBIt (t) is day front lay
The t moment energy storage charge/discharge power drawn.
4. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 3, special
Sign is: after setting peak regulation target, setting the bound of energy storage charge and discharge safety value power to carrying out in energy storage charge and discharge process
Power constraint, power constraint relational expression indicate are as follows:
Wherein, PBNFor the rated power of energy storage；△ t is sample time resolution；ηminAnd ηmaxRespectively setting energy storage SOC is minimum
With maximum safety value；EtotFor energy storage total capacity；E (t) is the real surplus electricity of t moment energy storage.
5. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 4, special
Sign is: according to optimization energy storage power flow, obtaining the dominant eigenvalues P after energy storage peak shavingGOperation curve and energy-storage system
The mode of SOC sequence is as follows:
SOC(t)=SOC(t-1)+PB(t)Δt/Etot
Wherein, PGIt (t) is t moment dominant eigenvalues；SOCIt (t-1) was the SOC value of energy-storage system at the end of a upper period；SOC
It (t) is the SOC value of energy-storage system at the end of current slot.
6. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 5, special
Sign is: in second step by dominant eigenvalues after peak regulation obtained in the first step be extended to contact power interval mode it is as follows:
In dominant eigenvalues PGThreshold epsilon is added on the basis of operation curve1And ε2It constructs interconnection and runs power interval [Pthrl,
Pthrh], shown in computation rule such as formula (3):
Wherein, PthrlFor the lower limit of power interval；PthrhFor the upper limit of power interval；ε1And ε2The interconnection respectively set is to upper
Lower boundary vertical direction distance, ε1, ε2> 0.
7. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 6, special
Sign is: the specific method is as follows for third step:
(A) wind power of load power of the based on power distribution network history and corresponding power distribution network historical juncture carry out respectively load and
The in a few days rolling forecast of wind power, and calculate in a few days net load rolling forecast value
(B) is based in (A) step the in a few days net load power of rolling forecastEnergy-storage system SOC sequence obtained in the first step
Energy-storage system dominant eigenvalues P is modified in the dominant eigenvalues section of column and second step buildingGThe reference value of operation curve
(C) is according to modified reference valueThe charge/discharge power P of energy storage is acquired using following formulaBrea:
8. a kind of energy storage peak shaving control method based on the prediction of multiple time scale model net load according to claim 7, special
Sign is: step (B) reference valueCalculating the specific method is as follows:
1. obtaining the actual soc-value S of current time energy-storage systemrea(t)；If Srea(t)≤0.1||Srea(t) >=0.9, energy storage
It is failure to actuate；If 0.1 < Srea(t) 0.9 <, into next step；
2. calculated using following formula is to reach t+1 moment energy storage SOC value S in the next stageOC(t+1), the charge/discharge that energy storage needs
Power
3. above-mentioned steps 2. on the basis of takeCharge/discharge power of the 1/d as next stage energy storage
4. in conjunction in a few days net load rolling forecast valueNext stage dominant eigenvalues are calculated with the contact power interval of setting
Reference value are as follows:
Wherein,For the ultra-short term predicted value of t+1 moment net load；
5. for the reference value for the next stage dominant eigenvalues being calculatedJoin section in the power of formula (3) setting
The calculated result of formula (4) can be used directly in the interior period；For the reference value for the next stage system operation being calculatedThe not period in the power ginseng section of formula (3) setting, ifSo reference value is set as
Pthrh(t+1)；IfSo reference value is set as Pthrl(t+1)；Modified next stage system operation
Reference value are as follows:
9. a kind of energy storage peak shaving control system based on the prediction of multiple time scale model net load, it is characterised in that: the system includes storage
It can energy stream optimization module, contact power interval expansion module and correction module；
Energy storage energy stream optimization module based on net load prediction result a few days ago obtain energy-storage system SOC sequence and peak regulation after get in touch with
It is flow-optimized to complete energy storage energy for linear heat generation rate；
It gets in touch with power interval expansion module and dominant eigenvalues after peak regulation obtained in energy storage energy stream optimization module is extended to connection
Network power interval；
Net load power and energy storage energy flow-optimized mould of the correction module based on the in a few days rolling forecast higher than precision of prediction a few days ago
The amendment energy-storage system in the dominant eigenvalues section that contact power interval expansion module is formed of SOC sequence obtained in block is practical
Charge/discharge power complete energy storage peak shaving control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910422270.4A CN110311424B (en) | 2019-05-21 | 2019-05-21 | Energy storage peak regulation control method based on dual-time-scale net load prediction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910422270.4A CN110311424B (en) | 2019-05-21 | 2019-05-21 | Energy storage peak regulation control method based on dual-time-scale net load prediction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110311424A true CN110311424A (en) | 2019-10-08 |
| CN110311424B CN110311424B (en) | 2023-01-20 |
Family
ID=68075400
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910422270.4A Active CN110311424B (en) | 2019-05-21 | 2019-05-21 | Energy storage peak regulation control method based on dual-time-scale net load prediction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110311424B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112465662A (en) * | 2020-10-13 | 2021-03-09 | 国网山东省电力公司电力科学研究院 | Calculation method and system for dynamically predicting peak regulation interval of thermal power generating unit |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040068412A1 (en) * | 2002-10-03 | 2004-04-08 | Docomo Communications Laboratories Usa, Inc. | Energy-based nonuniform time-scale modification of audio signals |
| CN103872694A (en) * | 2014-02-26 | 2014-06-18 | 山东大学 | Capacity optimization and auxiliary peak regulation method for regional wind power plant group energy storage power station |
| WO2014176930A1 (en) * | 2013-05-03 | 2014-11-06 | 国家电网公司 | Short-term operation optimization method for electric power system having large-scale wind power |
| CN104915737A (en) * | 2015-06-30 | 2015-09-16 | 国网山东省电力公司济南供电公司 | Coordinating economic dispatching method for power system containing large-scale wind power based on risk control |
| CN104933516A (en) * | 2015-05-27 | 2015-09-23 | 华南理工大学 | Multi-time-scale power system robustness scheduling system design method |
| CN106099960A (en) * | 2016-07-18 | 2016-11-09 | 华中科技大学 | A kind of method of small power station group of planes composition distributed energy storage system |
| CN106682808A (en) * | 2016-09-20 | 2017-05-17 | 北京恒泰实达科技股份有限公司 | Online rolling optimization scheduling model |
| CN106992556A (en) * | 2017-05-24 | 2017-07-28 | 南方电网科学研究院有限责任公司 | A kind of Optimization Scheduling complementary based on AC-battery power source Multiple Time Scales |
| CN107017630A (en) * | 2017-05-18 | 2017-08-04 | 南京师范大学 | A kind of electric power demand side response method of Multiple Time Scales |
| CN107480833A (en) * | 2017-09-05 | 2017-12-15 | 清华大学 | A kind of wind-powered electricity generation electricity generation system peak modulation capacity appraisal procedure |
| CN107800153A (en) * | 2017-11-09 | 2018-03-13 | 国网甘肃省电力公司电力科学研究院 | A kind of electric heating energy of electric accumulation of heat consumption wind-powered electricity generation rolls Robust Scheduling method |
| CN109524958A (en) * | 2018-11-08 | 2019-03-26 | 国网浙江省电力有限公司经济技术研究院 | Consider the electric system flexibility Optimization Scheduling of depth peak regulation and demand response |
| CN109672216A (en) * | 2018-11-26 | 2019-04-23 | 南瑞集团有限公司 | One kind being based on polyfactorial active distribution network hierarchical control method and system |
-
2019
- 2019-05-21 CN CN201910422270.4A patent/CN110311424B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040068412A1 (en) * | 2002-10-03 | 2004-04-08 | Docomo Communications Laboratories Usa, Inc. | Energy-based nonuniform time-scale modification of audio signals |
| WO2014176930A1 (en) * | 2013-05-03 | 2014-11-06 | 国家电网公司 | Short-term operation optimization method for electric power system having large-scale wind power |
| CN103872694A (en) * | 2014-02-26 | 2014-06-18 | 山东大学 | Capacity optimization and auxiliary peak regulation method for regional wind power plant group energy storage power station |
| CN104933516A (en) * | 2015-05-27 | 2015-09-23 | 华南理工大学 | Multi-time-scale power system robustness scheduling system design method |
| CN104915737A (en) * | 2015-06-30 | 2015-09-16 | 国网山东省电力公司济南供电公司 | Coordinating economic dispatching method for power system containing large-scale wind power based on risk control |
| CN106099960A (en) * | 2016-07-18 | 2016-11-09 | 华中科技大学 | A kind of method of small power station group of planes composition distributed energy storage system |
| CN106682808A (en) * | 2016-09-20 | 2017-05-17 | 北京恒泰实达科技股份有限公司 | Online rolling optimization scheduling model |
| CN107017630A (en) * | 2017-05-18 | 2017-08-04 | 南京师范大学 | A kind of electric power demand side response method of Multiple Time Scales |
| CN106992556A (en) * | 2017-05-24 | 2017-07-28 | 南方电网科学研究院有限责任公司 | A kind of Optimization Scheduling complementary based on AC-battery power source Multiple Time Scales |
| CN107480833A (en) * | 2017-09-05 | 2017-12-15 | 清华大学 | A kind of wind-powered electricity generation electricity generation system peak modulation capacity appraisal procedure |
| CN107800153A (en) * | 2017-11-09 | 2018-03-13 | 国网甘肃省电力公司电力科学研究院 | A kind of electric heating energy of electric accumulation of heat consumption wind-powered electricity generation rolls Robust Scheduling method |
| CN109524958A (en) * | 2018-11-08 | 2019-03-26 | 国网浙江省电力有限公司经济技术研究院 | Consider the electric system flexibility Optimization Scheduling of depth peak regulation and demand response |
| CN109672216A (en) * | 2018-11-26 | 2019-04-23 | 南瑞集团有限公司 | One kind being based on polyfactorial active distribution network hierarchical control method and system |
Non-Patent Citations (4)
| Title |
|---|
| XIAOQING BAI等: "《Bidirectional coordinating dispatch of large-scale V2G in a future smart grid using complementarity optimization》", 《INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS》 * |
| 张亚超等: "《含大规模风电的电力***多时间尺度源荷协调调度模型研究》", 《高电压技术》 * |
| 李春燕等: "计及风电功率预测误差的需求响应多时间尺度优化调度", 《电网技术》 * |
| 王晓东等: "《基于双时间尺度净负荷预测的储能调峰控制策略》", 《太阳能学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112465662A (en) * | 2020-10-13 | 2021-03-09 | 国网山东省电力公司电力科学研究院 | Calculation method and system for dynamically predicting peak regulation interval of thermal power generating unit |
| CN112465662B (en) * | 2020-10-13 | 2023-04-07 | 国网山东省电力公司电力科学研究院 | Calculation method and system for dynamically predicting peak regulation interval of thermal power generating unit |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110311424B (en) | 2023-01-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wang et al. | Energy management and optimization of vehicle-to-grid systems for wind power integration | |
| Cao et al. | Battery energy storage sizing based on a model predictive control strategy with operational constraints to smooth the wind power | |
| Abdeltawab et al. | Market-oriented energy management of a hybrid wind-battery energy storage system via model predictive control with constraint optimizer | |
| Luo et al. | Coordinated operational planning for wind farm with battery energy storage system | |
| CN102664423B (en) | Wind power station energy storage capacity control method based on particle swarm optimization | |
| CN104993522B (en) | A kind of active distribution network Multiple Time Scales coordination optimization dispatching method based on MPC | |
| CN103337001B (en) | Consider the wind farm energy storage capacity optimization method of optimal desired output and state-of-charge | |
| CN110311421A (en) | Micro-capacitance sensor Multiple Time Scales energy management method based on Demand Side Response | |
| CN109345019B (en) | Improved particle swarm algorithm-based micro-grid economic dispatching optimization strategy | |
| CN106777487B (en) | A kind of photovoltaic plant containing energy-storage system is credible capacity calculation methods and system | |
| CN104779631A (en) | Method and system for tracking wind and electric output plans through energy storage based on predictive power of wind and electricity | |
| CN105205549B (en) | Opportunity constraint planning-based optical storage system tracking day-ahead plan scheduling method | |
| KR20190023791A (en) | System and Method of Simplified Robust Optimal Operation of Microgrids by Band of Wirtual Equivalent Load Variation Considering the Uncertainty of Renewable Generation and Loads | |
| CN111009895B (en) | Microgrid optimal scheduling method, system and equipment | |
| CN105140936A (en) | Micro-grid frequency modulation control method with lowest power generation cost | |
| CN109978242A (en) | The photovoltaic power generation cluster power forecasting method and device of scale are risen based on statistics | |
| CN103248065B (en) | Charging-discharging control method of cell energy storing system in wind power plant | |
| CN108009681B (en) | Method for improving wind power consumption based on power grid load peak period curve | |
| Chen et al. | Energy storage sizing for dispatchability of wind farm | |
| CN109378856A (en) | Wind based on rolling optimization-storage hybrid power plant power swing stabilizes strategy and analogy method | |
| CN105515031B (en) | A kind of microgrid energy storage real-time control method based on prediction data amendment | |
| CN110365058A (en) | Isolated micro-capacitance sensor running optimizatin method based on simulated annealing particle swarm algorithm | |
| Zhu et al. | Real-time control of energy storage devices in future electric power systems | |
| CN114336762A (en) | Day-ahead scheduling energy storage configuration optimization method for wind-solar power generation and power grid load fluctuation | |
| CN103679284A (en) | Accommodated wind power accessed fixed interval rolling scheduling method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |