CN103904687A - Hybrid energy system configuration and output smoothing method oriented towards power grid load data - Google Patents

Hybrid energy system configuration and output smoothing method oriented towards power grid load data Download PDF

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CN103904687A
CN103904687A CN201410133309.8A CN201410133309A CN103904687A CN 103904687 A CN103904687 A CN 103904687A CN 201410133309 A CN201410133309 A CN 201410133309A CN 103904687 A CN103904687 A CN 103904687A
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李鹏
宋永端
李遥
马小平
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Beijing Jiaotong University
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Abstract

The invention provides a hybrid energy system configuration and output smoothing method oriented towards power grid load data. A data classification optimizing processing method is designed according to the difference of time intervals of the power grid load data, and particularly an efficient and robust configuration method is introduced for short time data, a robust and smooth reference curve is generated as a short-time power energy output reference instruction of a hybrid energy system when photovoltaic and stored energy complementary power supply meets the demands of power grid loads, and therefore not only is the conventional power energy requirement met, but also the smoothness and stability of power energy supplied by the system are ensured, and power supply quality is improved.

Description

Towards energy mix system configuration and the output smoothing method of electrical network load data
Technical field
The present invention relates to new energy field, particularly relate to a kind of energy mix system towards electrical network load data.
Background technology
Traditional energy is combined with new forms of energy and form the important technology branch that energy mix system is future source of energy development.Photovoltaic generation is the important way of efficiently utilizing solar energy resources, but the stochastic volatility being easily affected by the external environment and produce, therefore, it is combined and form extensive grid-connected photovoltaic energy-storage system with large capacity energy-accumulating power station (energy-storage system), can effectively realize the fluctuation of peak load shifting and output electric energy and stabilize, improve the quality of power supply.
For grid-connected photovoltaic energy-storage system, according to its towards electrical network load data difference, the target of its optimization is also different.The present invention is intended to the short time data for electrical network load, discloses a kind of energy mix system configuration and output smoothing method.
From currently available technology, for energy mix system, the main target of its photovoltaic and energy-storage system allocation and optimization is as follows: adopt inverter to realize energy-storage system stabilizing photovoltaic output pulsation in conjunction with control strategy, then grid-connected, thereby avoid the impact to electrical network, concrete technology comprises topology design, maximal power tracing strategy, controller design, unsteady flow optimization etc.Its essence is that first to optimize photovoltaic output grid-connected again, but not from the design angle of generating reference curve, considers the problem of utilizing of electrical network load data in short-term.
Summary of the invention
For above the deficiencies in the prior art, the present invention is by the difference to electrical network load data (data and short time data when length), and then classified use, the decision-making of design energy resource system allocation and optimization, especially for short time data, design a kind of collocation method of efficient, robust, in ensureing that the complementary power supply of photovoltaic and energy storage meets electrical network loading demand, generate the foundation that " the level and smooth reference curve of robust " exported in short-term as energy mix system, optimization system output quality accordingly, improves for electrical stability peace slip.
Technical problem to be solved by this invention is to provide a kind of energy mix system towards electrical network load data, in order to optimize the electric energy output quality of this system, improves for electrical stability peace slip.
In order to address the above problem, the invention discloses a kind of energy mix system configuration towards electrical network load data and output smoothing method, its method comprises:
A, obtain electrical network load data.
B, judge that electrical network load data type is " long time data " or " short time data ", the electrical network load data that native system obtains comprises " hour level " data and " minute level " data, data when wherein " hour level " data belong to long, " minute level " data belong to short time data.
If C " data when length " enters " data processing module when length ": data analysis electrical network loading demand while utilizing length, configure traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, meet generally the demand of electrical network load.This module belongs to traditional system configuration strategy, and the present invention no longer describes in detail.
D " if short time data ", enter " short time data processing module ": utilize the in short-term electric energy output reference instruction of " short time data " generation " the level and smooth reference curve of robust " as energy mix system, thereby realize the level and smooth of electric energy output, optimization system output quality accordingly, improves for electrical stability.Concrete steps following (referring to Fig. 3 signal):
Step1. set " smoothing interval " length n; And get vector initial value: smoothed curve vector p smooth=0, weighted vector w=I, wherein 0 and I be respectively zero vector and unit vector;
Step2. obtain and treat level and smooth data vector p;
Step3. constructing variable vector λ=[λ i]=[-2+2cos ((i-1) π/n)], wherein i=1 ... n;
Step4. set counting variable k=1;
Step5. setting accuracy tol=+ ∞;
Step6. judge whether tol is less than the set point Tol of system expection set, i.e. tol<Tol set:
If not, carry out Step7-1;
If so, carry out Step8-1;
Step7-1. calculate variable
Figure BDA0000486877880000022
wherein DCT represents discrete cosine transform, and symbol o represents that Schur amasss computing;
Step7-2. introduce auxiliary parameter s, and then compute matrix parameter
Figure BDA0000486877880000021
Step7-3. calculate the level and smooth vector upgrading
Figure BDA0000486877880000031
wherein IDCT represents inverse discrete cosine transform;
Step7-4. calculate system variable to be optimized
Figure BDA0000486877880000034
Step7-5. be optimized calculating: seek the optimal value of parameter s, make GCVs minimum;
Step7-6. carry out assignment: p smooth=p smooth_update;
Step7-7. upgrade tol = | | p smooth - p smooth _ update | | | | p smooth _ update | | , Return and carry out Step6;
Step8-1. calculate the bias vector err=p-p of level and smooth output smooth;
Step8-2. calculate median variable MAD=median (| err-median (err) |), wherein median is " square
Battle array is asked median " function;
Step8-3. compute vectors u = 1 1.4826 MAD 2 ( 1 + 16 s ) 4 2 ( 1 + 16 s ) - 1 + 1 + 16 s err ;
Step8-4. judge the norm of vector u | u i| whether meet | u i| <4.685;
If so, carry out Step8-5;
If not, carry out Step8-6;
Step8-5. calculate weight w i=(1-(u i/ 4.685) 2) 2;
Step8-6. assignment w i=0.
Step8-7. assignment w=[w i].
Step8-8. upgrade counting variable: k=k+1.
Step8-9. determine whether and meet k>2:
If so, carry out Step9;
If not, return and carry out Step4;
Step9. this circulation finishes, the vector p after output smoothing smooth_updateconstruct " the level and smooth reference curve of robust ", need smoothly if any new data, go to and carry out Step2.Compared with prior art, the present invention has the following advantages:
A kind of energy mix system configuration towards electrical network load data provided by the invention and output smoothing method, according to the time interval difference of electrical network load data, design a kind of Data classification optimization process and method, especially introduce " short time data processing module ", generate the foundation that " the level and smooth reference curve of robust " exported in short-term as energy mix system, make energy mix system can not only meet conventional power requirement, and ensure flatness and the stability of electric energy that system is supplied to have improved power supply quality optimization system output quality accordingly.
Brief description of the drawings
Fig. 1 is the flow chart of a kind of energy mix system towards electrical network load data described in the embodiment of the present invention;
Fig. 2 is the system global structure schematic diagram of a kind of energy mix system towards electrical network load data described in the embodiment of the present invention;
Fig. 3 is the realization flow schematic diagram of a kind of energy mix system towards electrical network load data described in the embodiment of the present invention.
Embodiment
For above-mentioned purpose of the present invention, feature and advantage can be become apparent more, below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.
With reference to Fig. 1, show a kind of flow chart of the energy mix system towards electrical network load data, described method specifically comprises:
Step S101, obtain electrical network load data.
Step S102, judge that electrical network load data type is " long time data " or " short time data ": the electrical network load data that native system obtains comprises " hour level " data and " minute level " data, data when wherein " hour level " data belong to long, " minute level " data belong to short time data.
If step S103 " data when length " enters " data processing module when length ": data analysis electrical network loading demand while utilizing length, configure traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, meet generally the demand of electrical 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 ", enter " short time data processing module ": utilize the in short-term electric energy output reference instruction of " short time data " generation " the level and smooth reference curve of robust " as energy mix system, thereby realize the level and smooth of electric energy output, optimization system output quality accordingly, improves for electrical stability.
With reference to Fig. 2, show system global structure schematic diagram of the present invention, main thought is:
The electric energy of laod network is supplied with source totally three parts: " conventional power generation systems " (coal-fired etc. non-new forms of energy), " photovoltaic generating system " and " energy-storage system ".Wherein the electric energy of a photovoltaic generating system output part directly transfers to load, and another part transfers to energy-storage system.
Meanwhile, electrical network load data will be delivered to " Data classification judgement " module, after judgement, deliver to " short time data processing module " (the present invention) or " data processing module when length ", pass through again afterwards other a series of processing modules (non-the present invention describes in detail), obtain final electric energy output and deliver to laod network.
With reference to Fig. 3, show method realization flow schematic diagram of the present invention, concrete steps are:
Step1. set " smoothing interval " length n; And get vector initial value: smoothed curve vector p smooth=0, weighted vector w=I, wherein 0 and I be respectively zero vector and unit vector;
Step2. obtain and treat level and smooth data vector p;
Step3. constructing variable vector λ=[λ i]=[-2+2cos ((i-1) π/n)], wherein i=1 ... n;
Step4. set counting variable k=1;
Step5. setting accuracy tol=+ ∞;
Step6. judge whether tol is less than the set point Tol of system expection set, i.e. tol<Tol set:
If not, carry out Step7-1;
If so, carry out Step8-1;
Step7-1. calculate variable
Figure BDA0000486877880000055
wherein DCT represents discrete cosine transform, and symbol o represents that Schur amasss computing;
Step7-2. introduce auxiliary parameter s, and then compute matrix parameter
Figure BDA0000486877880000051
Step7-3. calculate the level and smooth vector upgrading
Figure BDA0000486877880000052
wherein IDCT represents inverse discrete cosine transform;
Step7-4. calculate system variable to be optimized
Figure BDA0000486877880000056
Step7-5. be optimized calculating: seek the optimal value of parameter s, make GCVs minimum;
Step7-6. carry out assignment: p smooth=p smooth_update;
Step7-7. upgrade tol = | | p smooth - p smooth _ update | | | | p smooth _ update | | , Return and carry out Step6;
Step8-1. calculate the bias vector err=p-p of level and smooth output smooth;
Step8-2. calculate median variable MAD=median (| err-median (err) |), wherein median is " Matrix Calculating median " function;
Step8-3. compute vectors u = 1 1.4826 MAD 2 ( 1 + 16 s ) 4 2 ( 1 + 16 s ) - 1 + 1 + 16 s err ;
Step8-4. judge the norm of vector u | u i| whether meet | u i| <4.685;
If so, carry out Step8-5;
If not, carry out Step8-6;
Step8-5. calculate weight w i=(1-(u i/ 4.685) 2) 2;
Step8-6. assignment w i=0.
Step8-7. assignment w=[w i].
Step8-8. upgrade counting variable: k=k+1.
Step8-9. determine whether and meet k>2:
If so, carry out Step9;
If not, return and carry out Step4;
Step9. this circulation finishes, the vector p after output smoothing smooth_updateconstruct " the level and smooth reference curve of robust ", need smoothly if any new data, go to and carry out Step2.
Above a kind of energy mix system configuration towards electrical network load data provided by the present invention and output smoothing method are described in detail, applied specific case herein principle of the present invention and execution mode are set forth, the explanation of above embodiment is just for helping to understand method of the present invention and core concept thereof; , for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention meanwhile.

Claims (3)

1. towards energy mix system configuration and the output smoothing method of electrical network load data, it is characterized in that, this output smoothing method comprises the steps:
1) obtain electrical network load data;
2) judge that described data type is " data when length " or " short time data ";
3) if " data when length " utilize " data when length " to analyze electrical network loading demand, configuration traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, the demand of guarantee electrical network load;
4) if " short time data " utilized the in short-term electric energy output reference instruction of " short time data " generation " the level and smooth reference curve of robust " as energy mix system, thereby realized the level and smooth of electric energy output.
2. a kind of energy mix system configuration towards electrical network load data according to claim 1 and output smoothing method, is characterized in that, the method for the level and smooth reference curve of described generation robust is:
Step1. set " smoothing interval " length n; And get vector initial value: smoothed curve vector p smooth=0, weighted vector w=I, wherein 0 and I be respectively zero vector and unit vector;
Step2. obtain and treat level and smooth data vector p;
Step3. constructing variable vector λ=[λ i]=[-2+2cos ((i-1) π/n)], wherein i=1 ... n;
Step4. set counting variable k=1;
Step5. setting accuracy tol=+ ∞;
Step6. judge whether tol is less than the set point Tol of system expection set, i.e. tol<Tol set:
If not, carry out Step7-1;
If so, carry out Step8-1;
Step7-1. calculate variable
Figure FDA0000486877870000013
wherein DCT represents discrete cosine transform, and symbol ο represents that Schur amasss computing;
Step7-2. introduce auxiliary parameter s, and then compute matrix parameter
Figure FDA0000486877870000011
Step7-3. calculate the level and smooth vector upgrading
Figure FDA0000486877870000012
wherein IDCT represents inverse discrete cosine transform;
Step7-4. calculate system variable to be optimized
Step7-5. be optimized calculating: seek the optimal value of parameter s, make GCVs minimum;
Step7-6. carry out assignment: p smooth=p smooth_update;
Step7-7. upgrade tol = | | p smooth - p smooth _ update | | | | p smooth _ update | | , Return and carry out Step6;
Step8-1. calculate the bias vector err=p-p of level and smooth output smooth;
Step8-2. calculate median variable MAD=median (| err-median (err) |), wherein median is " Matrix Calculating median " function;
Step8-3. compute vectors u = 1 1.4826 MAD 2 ( 1 + 16 s ) 4 2 ( 1 + 16 s ) - 1 + 1 + 16 s err ;
Step8-4. judge the norm of vector u | u i| whether meet | u i| <4.685;
If so, carry out Step8-5;
If not, carry out Step8-6;
Step8-5. calculate weight w i=(1-(u i/ 4.685) 2) 2;
Step8-6. assignment w i=0.
Step8-7. assignment w=[w i].
Step8-8. upgrade counting variable: k=k+1.
Step8-9. determine whether and meet k>2:
If so, carry out Step9;
If not, return and carry out Step4;
Step9. this circulation finishes, the vector p after output smoothing smooth_updateconstruct " the level and smooth reference curve of robust ", need smoothly if any new data, go to and carry out Step2.
3. towards an energy mix system for electrical network load data, it is characterized in that, this energy resource system comprises:
Data classification judge module, classifies to the electrical network load data obtaining, and judges that data type is " data when length " or " short time data ";
When long, data processing module utilizes " data when length " to analyze electrical network loading demand, configures traditional energy, photovoltaic, three kinds of electricity generation modules of energy storage, ensures the demand of electrical network load;
Short time data processing module is utilized the in short-term electric energy output reference instruction of " short time data " generation " the level and smooth reference curve of robust " as energy mix system, thereby realizes the level and smooth of electric energy output.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105184077A (en) * 2015-09-06 2015-12-23 河南师范大学 Excessively-close-range particle-swarm exponential method for optimizing efficiency of resonant electric energy transmitting 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
JP2012070611A (en) * 2010-06-11 2012-04-05 Tabuchi Electric Co Ltd Isolated operation detection method, power conditioner and distributed power supply system
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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Publication number Priority date Publication date Assignee Title
JP2012070611A (en) * 2010-06-11 2012-04-05 Tabuchi Electric Co Ltd Isolated operation detection method, power conditioner and distributed power supply system
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

Cited By (2)

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Publication number Priority date Publication date Assignee Title
CN105184077A (en) * 2015-09-06 2015-12-23 河南师范大学 Excessively-close-range particle-swarm exponential method for optimizing efficiency of resonant electric energy transmitting system
CN105184077B (en) * 2015-09-06 2018-07-31 河南师范大学 Cross short distance low-resonance electric energy transmission system improving efficiency population index method

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