CN103904687B - Energy mix system towards network load data configures and output smoothing method - Google Patents
Energy mix system towards network load data configures and output smoothing method Download PDFInfo
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- CN103904687B CN103904687B CN201410133309.8A CN201410133309A CN103904687B CN 103904687 B CN103904687 B CN 103904687B CN 201410133309 A CN201410133309 A CN 201410133309A CN 103904687 B CN103904687 B CN 103904687B
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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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
The invention provides a kind of energy mix system towards network load data to configure and output smoothing method.Time interval according to network load data is different, a kind of data Classified optimization of design processes and method, especially for short time data, introduce a kind of efficient, collocation method of robust, ensureing that photovoltaic and energy storage complementation are powered while meeting network load demand, generate " robust smooths reference curve " output reference instruction of electric energy in short-term as energy mix system, thus conventional electrical energy demands can not only be met, and the flatness of the supplied electric energy of the system that ensure that and stability, improve power supply quality.
Description
Technical field
The present invention relates to new energy field, particularly relate to a kind of mixing energy towards network load data
Origin system.
Background technology
Traditional energy is combined with new forms of energy and forms the weight that energy mix system is future source of energy development
Want technology branch.Photovoltaic generation is the important way efficiently utilizing solar energy resources, but easily by extraneous ring
The stochastic volatility that border affects and produces, therefore, by itself and Large Copacity energy-accumulating power station (energy-storage system)
Combine formation large-scale grid connection photovoltaic energy storage system, can effectively realize peak load shifting and output electric energy
Fluctuation stabilize, improve the quality of power supply.
For grid-connected photovoltaic energy-storage system, according to its towards network load data different, it optimizes
Target the most different.It is contemplated that for the short time data of network load, open a kind of energy mix
System configuration and output smoothing method.
From the point of view of currently available technology, for energy mix system, its photovoltaic and energy-storage system configuration and
The main target optimized is as follows: uses inverter to combine control strategy and realizes energy-storage system to photovoltaic output
Stabilizing of fluctuation, the most grid-connected, thus avoid the impact to electrical network, concrete technology include topology design,
The design of maximal power tracing strategy, controller, unsteady flow optimization etc..Its essence is first to optimize photovoltaic output
The most grid-connected, but not from the design angle of generating reference curve, it is considered to the profit of network load data in short-term
Use problem.
Summary of the invention
For above the deficiencies in the prior art, the present invention is by difference (number time long of network load data
According to and short time data), and then classified use, design energy resource system configuration and Optimal Decision-making, especially pin
To short time data, design a kind of efficient, collocation method of robust, ensureing that photovoltaic and energy storage complementation supply
While electricity meets network load demand, generate " robust smooths reference curve " as energy mix system
The foundation exported in short-term, optimizes system output quality accordingly, improves for electrical stability peace slip.
The technical problem to be solved is to provide a kind of energy mix towards network load data
System, exports quality in order to optimize the electric energy of this system, improves for electrical stability peace slip.
In order to solve the problems referred to above, the invention discloses a kind of energy mix system towards network load data
Under unified central planning putting and output smoothing method, its method includes:
A, acquisition network load data.
B, judge that network load data type is " data time long " or " short time data ", acquired in native system
Network load data include " hour level " data and " minute level " data, wherein " hour level " data belong to
Data time long, " minute level " data belong to short time data.
C " if data time long ", then enter " data processing module time long ": data analysis electricity when utilizing long
Net loading demand, configures traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, meets electrical network generally and bears
The demand carried.This module belongs to traditional system configuration strategy, and the present invention no longer describes in detail.
D " if short time data ", then enter " short time data processing module ": utilize " short time data " to generate
" robust smooths reference curve " exports reference instruction as the electric energy in short-term of energy mix system, thus realizes
Smoothing of electric energy output, optimizes system output quality accordingly, improves for electrical stability.Comprise the following steps that
(seeing Fig. 3 signal):
Step1. " smoothing interval " length n is set；And take vector initial value: smoothed curve vector psmooth=0,
Weighted vector w=I, wherein 0 and I is respectively zero vector and unit vector；
Step2. data vector p to be smoothed is obtained；
Step3. constructing variable vector λ=[λi-2+2cos]=[((i-1) π/n)], wherein i=1 ... n；
Step4. counting variable k=1 is set；
Step5. setting accuracy tol=+ ∞；
Step6. judge whether tol is less than setting value Tol expected from systemset, i.e. tol ＜ Tolset:
If it is not, then perform Step7-1；
The most then perform Step8-1；
Step7-1. variables D CTp=DCT (w ο (p-p is calculatedsmooth)+psmooth), wherein DCT represents discrete
Cosine transform, symbol ο represents Schur and amasss computing；
Step7-2. introduce auxiliary parameter s, and then calculate matrix parameter
Step7-3. the smooth vector of renewal is calculatedWherein
IDCT represents inverse discrete cosine transform；
Step7-4. system variable GCVs=n to be optimized is calculated | | w1/2ο(p-psmooth)||2/(n-Tr)2；
Step7-5. calculating it is optimized: seek the optimal value of parameter s so that GCVs is minimum；
Step7-6. assignment: p is carried outsmooth=psmooth_update；
Step7-7. update Return and perform Step6；
Step8-1. the bias vector err=p-p of smooth output is calculatedsmooth；
Step8-2. calculating median variable MAD=median (err-median (err)), wherein median is " square
Battle array seeks median " function；
Step8-3. vector is calculated
Step8-4. the norm of vector u is judged | ui| whether meet | ui| ＜ 4.685；
The most then perform Step8-5；
If it is not, then perform Step8-6；
Step8-5. weight w is calculatedi=(1-(| ui|/4.685)2)2；
Step8-6. assignment wi=0.
Step8-7. assignment w=[wi]。
Step8-8. counting variable: k=k+1 is updated.
Step8-9. determine whether to meet k ＞ 2:
The most then perform Step9；
Step4 is performed if it is not, then return；
Step9. this circulation terminates, the vector p after output smoothingsmooth_updateConstruct that " robust smooths reference
Curve ", need to smooth if any new data, go to perform Step2.Compared with prior art, the present invention has
Advantages below:
A kind of energy mix system towards network load data that the present invention provides configures and output smoothing
Method, the time interval according to network load data is different, and a kind of data Classified optimization of design processes and side
Method, especially introduces " short time data processing module ", generates " robust smooths reference curve " as energy mix
The foundation that system exports in short-term, makes energy mix system can not only meet conventional electrical energy demands, and ensures
The flatness of system supplied electric energy and stability, improve power supply quality and optimize system output matter accordingly
Amount.
Accompanying drawing explanation
Fig. 1 is a kind of energy mix system towards network load data described in the embodiment of the present invention
Flow chart；
Fig. 2 is a kind of energy mix system towards network load data described in the embodiment of the present invention
System global structure schematic diagram；
Fig. 3 is a kind of energy mix system towards network load data described in the embodiment of the present invention
Realize schematic flow sheet.
Detailed description of the invention
Understandable, below in conjunction with the accompanying drawings for enabling the above-mentioned purpose of the present invention, feature and advantage to become apparent from
The present invention is further detailed explanation with detailed description of the invention.
With reference to Fig. 1, it is shown that the flow chart of a kind of energy mix system towards network load data, institute
The method of stating specifically includes:
Step S101, acquisition network load data.
Step S102, judge that network load data type is " data time long " or " short time data ": this is
Network load data acquired in system include " hour level " data and " minute level " data, wherein " hour level "
Data when data belong to long, " minute level " data belong to short time data.
Step S103 " if data time long ", then enter " data processing module time long ": number when utilizing long
According to analyzing network load demand, configure traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, full generally
The demand of foot network load.This module belongs to traditional system configuration strategy, and the present invention no longer describes in detail.
Step S104 " if short time data ", then enter " short time data processing module ": utilize and " count in short-term
According to " generation " robust smooths reference curve " as energy mix system electric energy in short-term export reference instruction, from
And realize the smooth of electric energy output, optimize system output quality accordingly, improve for electrical stability.
With reference to Fig. 2, it is shown that the system global structure schematic diagram of the present invention, main thought is:
Electric energy supply source totally three part of laod network: " conventional power generation systems " (coal-fired etc. non-new forms of energy),
" photovoltaic generating system " and " energy-storage system ".Wherein an electric energy output part for photovoltaic generating system is the most defeated
To load, another part transfers to energy-storage system.
Meanwhile, network load data will deliver to " data classification judges " module, deliver to " short after judging
Time data processing module " (present invention) or " data processing module time long ", the most again through other are a series of
Processing module (non-invention is described in detail), obtains final electric energy output and delivers to laod network.
With reference to Fig. 3, it is shown that the method for the present invention realizes schematic flow sheet, concretely comprises the following steps:
Step1. " smoothing interval " length n is set；And take vector initial value: smoothed curve vector psmooth=0,
Weighted vector w=I, wherein 0 and I is respectively zero vector and unit vector；
Step2. data vector p to be smoothed is obtained；
Step3. constructing variable vector λ=[λi-2+2cos]=[((i-1) π/n)], wherein i=1 ... n；
Step4. counting variable k=1 is set；
Step5. setting accuracy tol=+ ∞；
Step6. judge whether tol is less than setting value Tol expected from systemset, i.e. tol ＜ Tolset:
If it is not, then perform Step7-1；
The most then perform Step8-1；
Step7-1. variables D CTp=DCT (w ο (p-p is calculatedsmooth)+psmooth), wherein DCT represents discrete
Cosine transform, symbol ο represents Schur and amasss computing；
Step7-2. introduce auxiliary parameter s, and then calculate matrix parameter
Step7-3. the smooth vector of renewal is calculatedWherein
IDCT represents inverse discrete cosine transform；
Step7-4. system variable GCVs=n to be optimized is calculated | | w1/2ο(p-psmooth)||2/(n-Tr)2；
Step7-5. calculating it is optimized: seek the optimal value of parameter s so that GCVs is minimum；
Step7-6. assignment: p is carried outsmooth=psmooth_update；
Step7-7. update Return and perform Step6；
Step8-1. the bias vector err=p-p of smooth output is calculatedsmooth；
Step8-2. calculating median variable MAD=median (err-median (err)), wherein median is " square
Battle array seeks median " function；
Step8-3. vector is calculated
Step8-4. the norm of vector u is judged | ui| whether meet | ui| ＜ 4.685；
The most then perform Step8-5；
If it is not, then perform Step8-6；
Step8-5. weight w is calculatedi=(1-(| ui|/4.685)2)2；
Step8-6. assignment wi=0.
Step8-7. assignment w=[wi]。
Step8-8. counting variable: k=k+1 is updated.
Step8-9. determine whether to meet k ＞ 2:
The most then perform Step9；
Step4 is performed if it is not, then return；
Step9. this circulation terminates, the vector p after output smoothingsmooth_updateConstruct that " robust smooths reference
Curve ", need to smooth if any new data, go to perform Step2.
Above a kind of energy mix system towards network load data provided by the present invention is configured and
Output smoothing method is described in detail, and specific case used herein is to the principle of the present invention and reality
The mode of executing is set forth, the explanation of above example be only intended to help to understand the method for the present invention and
Core concept；Simultaneously for one of ordinary skill in the art, according to the thought of the present invention, specifically
All will change on embodiment and range of application, in sum, this specification content should not be understood
For limitation of the present invention.
Claims (2)
1. the energy mix system output smoothing method towards network load data, it is characterised in that
This output smoothing method comprises the steps:
1) network load data are obtained；
2) judge that described data type is " data time long " or " short time data ", described " number time long
According to " it is " hour level " data in described network load data, described " short time data " is described electricity
" minute level " data in net load data；
3) if " data time long ", then utilizing " data time long " to analyze network load demand, configuration passes
The system energy, photovoltaic, three kinds of electricity generation modules of energy storage, it is ensured that the demand of network load；
4) if " short time data ", then " short time data " generation " robust smooths reference curve " is utilized
Electric energy in short-term as energy mix system exports reference instruction, thus realizes the smooth of electric energy output；
The method of described generation " robust smooths reference curve " is:
Step1. " smoothing interval " length n is set；And take vector initial value: smoothed curve vector psmooth=0,
Weighted vector w=I, wherein 0 and I is respectively zero vector and unit vector；
Step2. data vector p to be smoothed is obtained；
Step3. constructing variable vector λ=[λi-2+2cos]=[((i-1) π/n)], wherein i=1 ... n；
Step4. counting variable k=1 is set；
Step5. setting accuracy tol=+ ∞；
Step6. judge whether tol is less than setting value Tol expected from systemset, i.e. tol ＜ Tolset:
If it is not, then perform Step7-1；
The most then perform Step8-1；
Step7-1. variables D CTp=DCT (w ο (p-p is calculatedsmooth)+psmooth), wherein DCT represents discrete
Cosine transform, symbol ο represents Schur and amasss computing；
Step7-2. introduce auxiliary parameter s, and then calculate matrix parameter
Step7-3. the smooth vector of renewal is calculatedWherein
IDCT represents inverse discrete cosine transform；
Step7-4. system variable GCV to be optimized is calculateds=n | | w1/2ο(p-psmooth)||2/(n-Tr)2；
Step7-5. calculating it is optimized: seek the optimal value of auxiliary parameter s so that GCVs is minimum；
Step7-6. assignment: p is carried outsmooth=psmooth_update；
Step7-7. updateReturn and perform Step6；
Step8-1. the bias vector err=p-p of smooth output is calculatedsmooth；
Step8-2. calculating median variable MAD=median (| err-median (err) |), wherein median is " square
Battle array seeks median " function；
Step8-3. vector is calculated
Step8-4. the norm of vector u is judged | ui| whether meet | ui| ＜ 4.685；
The most then perform Step8-5；
If it is not, then perform Step8-6；
Step8-5. weight w is calculatedi=(1-(| ui|/4.685)2)2, perform Step8-7；
Step8-6. assignment wi=0；
Step8-7. assignment w=[wi]；
The most more New count parameter: k=k+1；
Step8-9. determine whether to meet k ＞ 2:
The most then perform Step9；
Step4 is performed if it is not, then return；
Step9. this circulation terminates, output smoothing vector psmooth_updateConstruct " robust smooth reference song
Line ", need to smooth if any new data, go to perform Step2.
2. implement the energy mix system towards network load data of method described in claim 1,
It is characterized in that, this energy resource system includes:
The network load data obtained are classified, it is judged that data type is by data classification judge module
" data time long " or " short time data "；
Data processing module utilization " data time long " analysis network load demand time long, configuration traditional energy,
Photovoltaic, three kinds of electricity generation modules of energy storage, it is ensured that the demand of network load；
Short time data processing module utilizes " short time data " generation " robust smooths reference curve " as mixed
Close the output reference instruction of electric energy in short-term of energy resource system, thus realize the smooth of electric energy output.
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| CN102377248A (en) * | 2011-10-10 | 2012-03-14 | 南方电网科学研究院有限责任公司 | Method for optimizing capacity of energy storage system in case of fluctuation of smooth and renewable energy sources electricity generation output |
| CN102694391A (en) * | 2012-05-31 | 2012-09-26 | 国电南瑞科技股份有限公司 | Day-ahead optimal scheduling method for wind-solar storage integrated power generation system |
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| CN102377248A (en) * | 2011-10-10 | 2012-03-14 | 南方电网科学研究院有限责任公司 | Method for optimizing capacity of energy storage system in case of fluctuation of smooth and renewable energy sources electricity generation output |
| CN102694391A (en) * | 2012-05-31 | 2012-09-26 | 国电南瑞科技股份有限公司 | Day-ahead optimal scheduling method for wind-solar storage integrated power generation system |
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