CN109274131A - New energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory - Google Patents

New energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory Download PDF

Info

Publication number
CN109274131A
CN109274131A CN201811074389.9A CN201811074389A CN109274131A CN 109274131 A CN109274131 A CN 109274131A CN 201811074389 A CN201811074389 A CN 201811074389A CN 109274131 A CN109274131 A CN 109274131A
Authority
CN
China
Prior art keywords
new energy
max
power unit
digestion capability
indicated
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
Application number
CN201811074389.9A
Other languages
Chinese (zh)
Other versions
CN109274131B (en
Inventor
张振宇
马晓伟
段乃欣
褚云龙
王智伟
王文倬
潘璐璐
张钢
苏彪
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
STATE GRID NORTHWEST CHINA GRID Co Ltd
Original Assignee
STATE GRID NORTHWEST CHINA GRID Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by STATE GRID NORTHWEST CHINA GRID Co Ltd filed Critical STATE GRID NORTHWEST CHINA GRID Co Ltd
Priority to CN201811074389.9A priority Critical patent/CN109274131B/en
Publication of CN109274131A publication Critical patent/CN109274131A/en
Application granted granted Critical
Publication of CN109274131B publication Critical patent/CN109274131B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a kind of new energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory, comprising the following steps: step 1, new energy digestion capability non-sequential computation model is established based on system under evaluation;Step 2, the probability distribution that new energy abandons electric electric power is calculated;Step 3, it calculates new energy and abandons electric rate λ, the quantitative evaluation that electricity rate λ completes new energy digestion capability is abandoned by new energy.Quantitative estimation method of the invention can provide guidance for management and running real work;Traditional time stimulatiom process is substituted using convolutional calculation, it can be to avoid repeated samples in traditional Monte-carlo Simulation Method, the process of calculating, under the premise of not influencing precision, computational efficiency is increased substantially, provides effective way for RES(rapid evaluation system) new energy digestion capability.

Description

New energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory
Technical field
The invention belongs to electric power network control field, in particular to a kind of new energy based on Probability Statistics Theory dissolves energy Power non-sequential quantitative estimation method.
Background technique
Currently, domestic and foreign scholars, which have been directed to new energy digestion capability, expands a series of researchs, however existing research at Fruit is difficult for actual electric network regulation operation work and provides reference, and reason mainly has following two aspect:
First, existing research is conceived to new energy installation construction plan and its optimal generation scheme with conventional power unit more, To conventional power unit peak regulation rate, power plant for self-supply's ratio and direct current in actual motion send outside plan etc. factors how quantization influence new energy Research in terms of digestion capability is then less, can not propose guidance instruction to power scheduling practical application;
Second, current most of algorithms researched and proposed are using the time stimulatiom method based on Monte Carlo simulation as base Plinth, in actually calculating, repeated samples and time stimulatiom are more time-consuming, and efficiency is lower.
Summary of the invention
The purpose of the present invention is to provide a kind of, and the new energy digestion capability non-sequential quantization based on Probability Statistics Theory is commented Method is estimated, to solve above-mentioned technical problem.Quantitative estimation method of the invention can provide for management and running real work Guidance;Traditional time stimulatiom process is substituted using convolutional calculation, can improve operation efficiency in the case where not influencing precision.
In order to achieve the above objectives, the invention adopts the following technical scheme:
A kind of new energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory, comprising the following steps:
Step 1, the timing computation model of new energy digestion capability is established based on system under evaluation;
New energy digestion capability Pn(t) calculation formula are as follows:
Pn(t)=Pl,max(t)-Pg,min(t)
In formula, Pl,max(t) t moment system loading, P are indicatedg,min(t) t moment conventional power unit minimum technology power output is indicated;
New energy abandons electric power Pn,ab(t) calculation formula are as follows:
In formula, Pn,max(t) t moment new energy theoretical maximum power output, P are indicatedn(t) it is dissolved for the new energy of system t moment Ability;
Step 2, the probability distribution that new energy abandons electric electric power is calculated;
New energy abandons electric electric power Pn,ab(t) probability-distribution function fZ(z) by Pn,max(t) and Pn(t) probability density function is done Convolution obtains, expression formula are as follows:
Wherein fX(x) P is indicatedn,max(t) probability density function, fY(y) P is indicatedn(t) probability density function;
Step 3, it calculates new energy and abandons electric rate λ, commented by the quantization that new energy abandons electricity rate λ completion new energy digestion capability Estimate;New energy abandons electric rate λ calculation formula are as follows:
In formula,WithRespectively indicate Pn,ab(t) and Pn,max(t) mean value, it is close that the two passes through its probability respectively Degree function acquires, calculation formula are as follows:
F in formulaX(x) P is indicatedn,max(t) probability density function, fY(y) P is indicatedn(t) probability density function.
Further, when considering conventional power unit peak regulation rate β, the calculation formula of the minimum technology power output of conventional power unit are as follows:
Pg,min(t)=Pg,max(t)×(1-β)
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedg,max(t) t moment conventional power unit is indicated most Big technology power output, β are conventional power unit peak regulation rate.
Further, when considering conventional power unit peak regulation rate β and power plant for self-supply's proportion omegab, the minimum technology power output of conventional power unit Calculation formula are as follows:
Pg,min(t)=Pg,max(t)×(1-β)×(1-ω)+Pg,max(t)×ω
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedg,max(t) t moment conventional power unit is indicated most Big technology power output, β are conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
Further, when considering to send outside for a long time in conventional power unit peak regulation rate β, power plant for self-supply's proportion omegab and direct current, conventional machine The calculation formula of the minimum technology power output of group are as follows:
Pg,min(t)=(Pl,max(t)+Pw)×(1+α)×(1-β)×(1-ω)+(Pl,max(t)+Pw)×(1+α)×ω
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedwFor electricity sent outside, Pl,max(t) when indicating t Etching system load, α are the conventional power unit percentage reserve of system, and β is conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
Further, when considering short-term spot exchange, thermoelectricity minimum technology power output is not influenced.
It further, further include step 4;
Step 4, by the quantitative evaluation of new energy digestion capability and given target component, calculating system is receptive new What energy installation or system needed sends scale and peak regulation rate outside.
Compared with prior art, the invention has the following advantages:
The present invention has comprehensively considered the factors such as conventional power unit control characteristic and new energy installation accounting in actual motion, not Under the premise of influencing computational accuracy, new energy digestion capability assessment is reduced to a non-sequential computational problem, and establish non- Timing computation model;Probability Distribution Model based on new energy theory power output and system consumption space, is directly calculated using convolution Obtain the probability Distribution Model of new energy digestion capability.On the one hand quantitative estimation method of the invention avoids traditional Monte Carlo Repeated samples in analogy method, calculating process, on the other hand using convolutional calculation instead of traditional time-domain-simulation process, Under the premise of not influencing precision, computational efficiency is increased substantially.
Further, by means of the present invention, disappearing without network constraint system new energy based on peak modulation capacity can be established It receives theoretical model, and considers the new energy consumption model that power plant for self-supply, direct current send outside, pass through the analysis to new energy power producing characteristics Research can analyze new energy installation, load, conventional power unit peak regulation rate, power plant for self-supply's ratio and direct current and send outside and new energy abandoning Relationship between electric rate can carry out pool optimization to the operating parameter in the work of actual electric network operation plan, is conducive to The grid operation mode of new energy consumption.
Detailed description of the invention
Fig. 1 is that the new energy in quantitative estimation method of the invention dissolves theoretical schematic block diagram.
Specific embodiment
Invention is further described in detail in the following with reference to the drawings and specific embodiments.
Referring to Fig. 1, a kind of new energy digestion capability non-sequential quantitative evaluation based on Probability Statistics Theory of the invention Method, comprising the following steps:
Step 1, the timing computation model of new energy digestion capability is established based on system under evaluation;
New energy digestion capability Pn(t) calculation formula are as follows:
Pn(t)=Pl,max(t)-Pg,min(t)
In formula, Pl,max(t) t moment system loading, P are indicatedg,min(t) t moment conventional power unit minimum technology power output is indicated;
New energy abandons electric power Pn,ab(t) calculation formula are as follows:
In formula, Pn,max(t) t moment new energy theoretical maximum power output, P are indicatedn(t) it is dissolved for the new energy of system t moment Ability;
Step 2, the probability distribution that new energy abandons electric electric power is calculated;
Pn,max(t) only, P related with resourcen(t) only related with the load of system and start-up mode, they are mutually indepedent Stochastic variable, according to probability theory, new energy abandons electric electric power Pn,ab(t) probability-distribution function fZ(z) by Pn,max(t) and Pn(t) Probability density function do convolution acquisition, expression formula are as follows:
Wherein fX(x) P is indicatedn,max(t) probability is close Spend function, fY(y) P is indicatedn(t) probability density function.
Step 3, it calculates new energy and abandons electric rate λ, commented by the quantization that new energy abandons electricity rate λ completion new energy digestion capability Estimate;New energy abandons electric rate λ calculation formula are as follows:
In formula,WithRespectively indicate Pn,ab(t) and Pn,max(t) mean value, it is close that the two passes through its probability respectively Degree function acquires, calculation formula are as follows:
F in formulaX(x) P is indicatedn,max(t) probability density function, fY(y) P is indicatedn(t) probability density function.
Step 4, by the quantitative evaluation of new energy digestion capability and given target component, calculating system is receptive new What energy installation or system needed sends scale and peak regulation rate outside.
Wherein, when considering conventional power unit peak regulation rate β, the calculation formula of the minimum technology power output of conventional power unit are as follows:
Pg,min(t)=Pg,max(t)×(1-β)
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedg,max(t) t moment conventional power unit is indicated most Big technology power output, β are conventional power unit peak regulation rate.
When considering conventional power unit peak regulation rate β and power plant for self-supply's proportion omegab, the calculating of the minimum technology power output of conventional power unit is public Formula are as follows:
Pg,min(t)=Pg,max(t)×(1-β)×(1-ω)+Pg,max(t)×ω
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedg,max(t) t moment conventional power unit is indicated most Big technology power output, β are conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
When considering to send outside for a long time in conventional power unit peak regulation rate β, power plant for self-supply's proportion omegab and direct current, the minimum skill of conventional power unit The calculation formula of art power output are as follows:
Pg,min(t)=(Pl,max(t)+Pw)×(1+α)×(1-β)×(1-ω)+(Pl,max(t)+Pw)×(1+α)×ω
Wherein, Pg,min(t) t moment conventional power unit minimum technology power output, P are indicatedwFor electricity sent outside, Pl,max(t) when indicating t Etching system load, α are the conventional power unit percentage reserve of system, and β is conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
And when considering short-term spot exchange, it does not need to increase thermoelectricity booting to guarantee electricity sent outside, i.e., to thermoelectricity minimum Technology power output does not influence.
Embodiment 1
Referring to FIG. 1, a kind of quantitative estimation method of new energy digestion capability based on Probability Statistics Theory of the invention, It is calculated quickly, can be instructed the operating parameter in the work of actual electric network operation plan, specifically includes the following steps:
Step 1, the optimized evaluation model based on regional power grid new energy characteristic.
Firstly, defining shown in the wave characteristic γ such as formula (1) of new energy power output:
γ=| Pt-Pt-Δt|/S (1)
In formula (1), Pt-Pt-ΔtFor the difference of two neighboring sampled point new energy power output, S is new energy installed capacity;Wave Dynamic characteristic γ parameter reflects the rate of change of new energy in a short time.
By for statistical analysis in the wave characteristic of different periods to regional power grid (by taking Northwest Grid as an example) new energy It was found that: for Northwest Grid, when Δ t=15 minutes, wave characteristic γ value is under most situations (99.5%) Less than 5%;That is, it is believed that the rate of change of every 15 minutes new energy power output is not more than the 5% of its installed capacity. Currently, the generator connecting in parallel with system administrative provisions of national grid generally require conventional power unit regulations speed be more than or equal to 2% nominal output/ Minute, i.e., its 15 minutes regulating powers should be greater than 30% nominal output;There are also 10,000,000 kilowatts or more in Northwest Grid to have fastly The Hydropower Unit of fast responding ability can quickly be adjusted in 15 minutes between 0-100%, therefore conventional power unit in Northwest Grid Regulating power can satisfy new energy power output variation, that is to say, that Northwest Grid new energy digestion capability quantitative evaluation In calculating, conventional power unit Climing constant can be ignored.
By above-mentioned analysis it is found that new energy digestion capability quantitative appraisement model t moment state just and last moment T-1 is unrelated, can be reduced to a non-sequential computation model, at this point, system new energy power output is only by new energy theory function Rate and consumption space determine, as shown in formula (2):
Wherein, Pl,max(t) t moment system loading, P are indicatedg,min(t) t moment conventional power unit minimum technology power output is indicated, Pn,max(t) t moment new energy theoretical maximum power output is indicated.Generation of electricity by new energy is wind-powered electricity generation or photovoltaic power generation.In formula (2), when new energy When theory power output in source is less than or equal to system new energy digestion capability, it is theoretical that the new energy maximum output of t period is equal to new energy Power output;When new energy theory power output is greater than system new energy digestion capability, it is new that the new energy maximum output of t period is equal to system Energy consumption ability.
It can also be by abandoning electric electric power statement, system new energy abandons electric electric power Pn,ab(t) calculation formula are as follows:
In above formula, Pn(t) space, P are dissolved for t moment system new energyn,max(t) go out for t moment new energy theoretical maximum Power.
Step 2, the foundation and calculating of new energy digestion capability probability Distribution Model.
According to the new energy rapid qualitative evaluation model provided in formula (2), it can be seen that new energy digestion capability mainly takes Space certainly is dissolved in new energy theory power output and system, and by formula (2) it can be seen that new energy digestion capability can be written as it The linear expression that theory is contributed with system consumption space, and new energy theory power output and system consumption space are that satisfaction is certain general Rate distribution and mutually independent random variables, then new energy can be established using convolution based on the probability-distribution function of both The probability Distribution Model of source digestion capability, as the effective tool of quantitative evaluation new energy digestion capability.
The probability Distribution Model of new energy theory power output can be obtained based on new energy statistics rule and wind, light installation situation It arrives.For the probability Distribution Model in system consumption space, can acquire by the following method.
From formula (2) as can be seen that in actual electric network operation, new energy dissolves space mainly by the minimum technology of conventional power unit Power output and system loading determine.And for the minimum technology of conventional power unit power output for, mainly with conventional power unit peak regulation rate, from Long-term and stock sends correlation outside in standby power plant's ratio, direct current.
Establish conventional power unit peak regulation rate β, power plant for self-supply's proportion omegab, long-term in direct current and stock is sent outside and new energy consumption is empty Between between quantitative relationship model.
The relationship of the minimum technology of conventional power unit peak regulation rate β and conventional power unit power output are as follows:
Pg,min=Pg,max×(1-β) (4)
Wherein, Pg,minIt contributes for the minimum technology of t moment conventional power unit, Pg,maxFor thermoelectricity maximum technology power output, β is normal Advise peak load regulation rate.
From the point of view of current grid operating conditions, the power plant for self-supply of access system does not participate in peak-load regulating generally, then formula (4) becomes For
Pg,min=Pg,max×(1-β)×(1-ω)+Pg,max×ω (5)
Wherein, Pg,minIt contributes for the minimum technology of t moment conventional power unit, Pg,maxFor thermoelectricity maximum technology power output, β is normal Peak load regulation rate is advised, ω is power plant for self-supply's ratio.
It is sent outside for a long time in direct current and needs to increase thermoelectricity booting to guarantee electricity sent outside, i.e., it is equivalent to while increasing system Load and thermoelectricity start-up mode, then considering that sending rear system hair electric equilibrium constraint in direct current outside for a long time becomes
Pn(t)=Pl,max(t)+Pw-Pg,min(t) (6)
Wherein, PnIt (t) is the practical power generating value of system t moment new energy, Pl,max(t) t moment system loading, P are indicatedg,min (t) t moment conventional power unit minimum technology power output, P are indicatedwFor electricity sent outside.
Direct current stock is sent outside, main purpose is to increase direct current when abandonment abandoning optical phenomenon occurs in system and send function outside Rate is to guarantee that new energy dissolves;So not needing to increase thermoelectricity booting, i.e., system minimum technology power output is not influenced.
The new energy digestion capability quantitative evaluation schematic diagram provided according to Fig. 1, determine system convention peak load regulation rate, from After standby power plant's ratio and DC operation mode arrange, in conjunction with system loading rate, upper reserve factor and load prediction results, so that it may The timing curve in reflection system consumption space is obtained, its probability-distribution function is then obtained.
So far, the probability-distribution function in new energy consumption space and new energy theory power output can be obtained.Due in actual motion, New energy theory power output and system consumption space are to meet certain probability distribution and mutually independent random variables, then according to new Energy consumption mechanism can obtain formula (7) establishment:
Wherein fx(x) P is indicatedn,max(t) probability density function, fY(y) P is indicatedn(t) probability density function;
New energy abandons electric rate λ calculation formula are as follows:
In formula,WithRespectively indicate Pn,ab(t) and Pn,max(t) mean value, it is close that the two passes through its probability respectively Degree function acquires:
From formula (8) as can be seen that in the probability-distribution function f for acquiring the electric electric power of new energy abandoningZ(z) go out with new energy theory The probability-distribution function f of powerY(y) after, it can further obtain new energy and averagely abandon electrical power and new energy average theory power output, Then it directly calculates new energy and abandons electric rate λ.
It can be seen that the new energy digestion capability quantitative appraisement model solution side based on probability statistics from above-mentioned solution procedure Method can be to avoid repeated samples in traditional Monte-carlo Simulation Method, the process of calculating, under the premise of not influencing precision, greatly Amplitude improves computational efficiency, provides effective way for RES(rapid evaluation system) new energy digestion capability.
The present invention contributes statistical data according to new energy in actual motion, in conjunction with current conventional power unit regulation performance situation, Propose new energy digestion capability non-sequential computation model;Space is dissolved according to new energy theory power output type and system new energy Probability-distribution function establishes the probability-distribution function that system new energy abandons electric electric power in conjunction with convolution theory, then obtains system abandoning Electric rate provides effective way for RES(rapid evaluation system) new energy digestion capability.By the research of project key technology, base is established Theoretical model is dissolved without network constraint system new energy in peak modulation capacity, and considers the new energy that power plant for self-supply, direct current send outside Model is dissolved, and by the analysis and research to new energy power producing characteristics, proposes the Optimization Solution algorithm of the model.It is basic herein On, analysis new energy installation, load, conventional power unit peak regulation rate, power plant for self-supply's ratio and direct current, which are sent outside, abandons electric rate with new energy Between relationship.On this basis, for given target component, the receptive new energy installation of calculating system or system need Send scale, peak regulation rate etc. outside, also have positive directive significance for systems organization.Quantitative estimation method of the invention is with new energy Based on source statistics rule and power grid consumption space, according to Probability Statistics Theory, quickly to power grid new energy digestion capability into Row quantum chemical method.Therefore, mainly solution field is in dispatching of power netwoks operation work for this research, is dispatched with short-term, ultra-short term It is target that plan, which promotes new energy digestion capability, removes the principal element of Long-term planning and conventional power unit generation schedule, is based on adjusting The analysis of peak energy power mainly considers that power plant for self-supply, direct current send new energy consumption quantitative model outside, research conventional power unit peak regulation rule, Power plant for self-supply's ratio, transregional direct current send outside, upper reserve factor etc. abandons the influence of electric rate to new energy, is management and running real work Guidance is provided;Meanwhile traditional time stimulatiom process is substituted using convolutional calculation and is mentioned significantly in the case where not influencing precision High operation efficiency.

Claims (6)

1. a kind of new energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory, which is characterized in that including Following steps:
Step 1, the timing computation model of new energy digestion capability is established based on system under evaluation;
New energy digestion capability Pn(t) calculation formula are as follows:
Pn(t)=PL, max(t)-PG, min(t)
In formula, PL, max(t) t moment system loading, P are indicatedG, min(t) t moment conventional power unit minimum technology power output is indicated;
New energy abandons electric power PN, ab(t) calculation formula are as follows:
In formula, PN, max(t) t moment new energy theoretical maximum power output, P are indicatednIt (t) is the new energy digestion capability of system t moment;
Step 2, the probability distribution that new energy abandons electric electric power is calculated;
New energy abandons electric electric power PN, ab(t) probability-distribution function fZ(z) by PN, max(t) and Pn(t) probability density function does convolution It obtains, expression formula are as follows:
Wherein fX(x) P is indicatedN, max(t) probability density function, fY(y) P is indicatedn(t) probability density function;
Step 3, it calculates new energy and abandons electric rate λ, the quantitative evaluation that electricity rate λ completes new energy digestion capability is abandoned by new energy;Newly The energy abandons electric rate λ calculation formula are as follows:
In formula,WithRespectively indicate PN, ab(t) and PN, max(t) mean value, the two pass through its probability density function respectively It acquires, calculation formula are as follows:
F in formulaX(x) P is indicatedN, max(t) probability density function, fY(y) P is indicatedn(t) probability density function.
2. a kind of new energy digestion capability non-sequential quantitative evaluation side based on Probability Statistics Theory according to claim 1 Method, which is characterized in that when considering conventional power unit peak regulation rate β, the calculation formula of the minimum technology power output of conventional power unit are as follows:
PG, min(t)=PG, max(t)×(1-β)
Wherein, PG, min(t) t moment conventional power unit minimum technology power output, P are indicatedG, max(t) t moment conventional power unit maximum skill is indicated Art power output, β are conventional power unit peak regulation rate.
3. a kind of new energy digestion capability non-sequential quantitative evaluation side based on Probability Statistics Theory according to claim 1 Method, which is characterized in that when considering conventional power unit peak regulation rate β and power plant for self-supply's proportion omegab, the minimum technology power output of conventional power unit Calculation formula are as follows:
PG, min(t)=PG, max(t)×(1-β)×(1-ω)+PG, max(t)×ω
Wherein, PG, min(t) t moment conventional power unit minimum technology power output, P are indicatedG, max(t) t moment conventional power unit maximum skill is indicated Art power output, β are conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
4. a kind of new energy digestion capability non-sequential quantitative evaluation side based on Probability Statistics Theory according to claim 1 Method, which is characterized in that when considering to send outside for a long time in conventional power unit peak regulation rate β, power plant for self-supply's proportion omegab and direct current, conventional power unit The calculation formula of minimum technology power output are as follows:
PG, min(t)=(PL, max(t)+Pw)×(1+α)×(1-β)×(1-ω)+(PL, max(t)+Pw)×(1+α)×ω
Wherein, PG, min(t) t moment conventional power unit minimum technology power output, P are indicatedwFor electricity sent outside, PL, max(t) t moment system is indicated System load, α are the conventional power unit percentage reserve of system, and β is conventional power unit peak regulation rate, and ω is power plant for self-supply's ratio.
5. a kind of new energy digestion capability non-sequential quantitative evaluation side based on Probability Statistics Theory according to claim 4 Method, which is characterized in that when considering short-term spot exchange, thermoelectricity minimum technology power output is not influenced.
6. a kind of new energy digestion capability non-sequential quantitative evaluation side based on Probability Statistics Theory according to claim 1 Method, which is characterized in that further include step 4;
Step 4, pass through the quantitative evaluation of new energy digestion capability and given target component, the receptive new energy of calculating system What installation or system needed sends scale and peak regulation rate outside.
CN201811074389.9A 2018-09-14 2018-09-14 Probability statistics theory-based non-time sequence quantitative evaluation method for new energy consumption capability Active CN109274131B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811074389.9A CN109274131B (en) 2018-09-14 2018-09-14 Probability statistics theory-based non-time sequence quantitative evaluation method for new energy consumption capability

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811074389.9A CN109274131B (en) 2018-09-14 2018-09-14 Probability statistics theory-based non-time sequence quantitative evaluation method for new energy consumption capability

Publications (2)

Publication Number Publication Date
CN109274131A true CN109274131A (en) 2019-01-25
CN109274131B CN109274131B (en) 2022-03-25

Family

ID=65189074

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811074389.9A Active CN109274131B (en) 2018-09-14 2018-09-14 Probability statistics theory-based non-time sequence quantitative evaluation method for new energy consumption capability

Country Status (1)

Country Link
CN (1) CN109274131B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110401220A (en) * 2019-07-26 2019-11-01 北京华建网源电力设计研究院有限公司 A kind of extensive new energy consumption level evaluation method and system
CN111030189A (en) * 2019-12-06 2020-04-17 国网辽宁省电力有限公司经济技术研究院 Wind power and photovoltaic consumption prediction and early warning method
CN112134273A (en) * 2020-08-06 2020-12-25 国家电网公司西北分部 New energy incorporation power system standby method and device based on risk control
CN112258064A (en) * 2020-10-29 2021-01-22 国网甘肃省电力公司电力科学研究院 New energy consumption capacity assessment method based on technology and market flexibility unified framework

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106410780A (en) * 2015-07-28 2017-02-15 中国电力科学研究院 New energy source acceptance space discrete probability sequence calculation method
CN106410859A (en) * 2015-07-28 2017-02-15 中国电力科学研究院 Random production simulation-based new energy grid connection admitting ability calculation method
JP2017070134A (en) * 2015-10-01 2017-04-06 新日鐵住金株式会社 Power prediction method
CN107274028A (en) * 2017-06-23 2017-10-20 国网山东省电力公司经济技术研究院 A kind of many wind fields based on mixing Copula functions are exerted oneself Forecasting Methodology
CN107681691A (en) * 2017-09-30 2018-02-09 太原理工大学 The wind-electricity integration system operation reliability appraisal procedure of meter and uncertain factor
CN107944757A (en) * 2017-12-14 2018-04-20 上海理工大学 Electric power interacted system regenerative resource digestion capability analysis and assessment method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106410780A (en) * 2015-07-28 2017-02-15 中国电力科学研究院 New energy source acceptance space discrete probability sequence calculation method
CN106410859A (en) * 2015-07-28 2017-02-15 中国电力科学研究院 Random production simulation-based new energy grid connection admitting ability calculation method
JP2017070134A (en) * 2015-10-01 2017-04-06 新日鐵住金株式会社 Power prediction method
CN107274028A (en) * 2017-06-23 2017-10-20 国网山东省电力公司经济技术研究院 A kind of many wind fields based on mixing Copula functions are exerted oneself Forecasting Methodology
CN107681691A (en) * 2017-09-30 2018-02-09 太原理工大学 The wind-electricity integration system operation reliability appraisal procedure of meter and uncertain factor
CN107944757A (en) * 2017-12-14 2018-04-20 上海理工大学 Electric power interacted system regenerative resource digestion capability analysis and assessment method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张振宇: "基于统计学特征的新能源纳入西北电网备用研究", 《电网技术》 *
舒印彪: "新能源消纳关键因素分析及解决措施研究", 《中国电机工程学报》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110401220A (en) * 2019-07-26 2019-11-01 北京华建网源电力设计研究院有限公司 A kind of extensive new energy consumption level evaluation method and system
CN111030189A (en) * 2019-12-06 2020-04-17 国网辽宁省电力有限公司经济技术研究院 Wind power and photovoltaic consumption prediction and early warning method
CN112134273A (en) * 2020-08-06 2020-12-25 国家电网公司西北分部 New energy incorporation power system standby method and device based on risk control
CN112258064A (en) * 2020-10-29 2021-01-22 国网甘肃省电力公司电力科学研究院 New energy consumption capacity assessment method based on technology and market flexibility unified framework

Also Published As

Publication number Publication date
CN109274131B (en) 2022-03-25

Similar Documents

Publication Publication Date Title
CN109274131A (en) New energy digestion capability non-sequential quantitative estimation method based on Probability Statistics Theory
CN103151803B (en) Method for optimizing wind power system-contained unit and backup configuration
CN106230028B (en) A kind of Multipurpose Optimal Method of wind-powered electricity generation-water-storage association system
Nazir et al. Optimization configuration of energy storage capacity based on the microgrid reliable output power
Zhang et al. A regulating capacity determination method for pumped storage hydropower to restrain PV generation fluctuations
CN114336702B (en) Wind-solar storage station group power distribution collaborative optimization method based on double-layer random programming
EP2610986A1 (en) A method for determining a power outage probability of an electrical power grid, a method for an adaptation of a power generation capacity and a method for determining an energy storage unit size
CN104065168B (en) A kind of dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring
CN108009681B (en) Method for improving wind power consumption based on power grid load peak period curve
CN110783959B (en) New forms of energy power generation system's steady state control system
KR20190112441A (en) Energy management system and enetgy management method thereof and energy operation system
CN105279707A (en) Probabilistic production simulation method comprehensively considering load and wind power temporal characteristic
CN115392547A (en) Virtual power plant energy comprehensive control platform based on data analysis
CN117077974A (en) Virtual power plant resource optimal scheduling method, device, equipment and storage medium
CN103023019A (en) Method and system for analyzing reserve capacity of power grid
Zhao et al. Research on reliability evaluation of power generation system with solar thermal power
CN109378857A (en) A kind of load peak moment wind-powered electricity generation reliability forecasting Risk Calculation method
Mu et al. Risk-constrained multi-period planning for park-level integrated energy system based on CVaR method
Zhou et al. System level assessment of PV and energy storage: Application to the Great Britain power system
Han et al. Increasing the installation capacity of PV with PEMFC backup within a residential community
Pan et al. A multi-source coordinated spinning reserve capacity optimization considering wind and photovoltaic power uncertainty
Wang et al. Optimization Configuration for Energy Storage of Renewable Energy Power Stations Participating in Primary Frequency Regulation Service Based on Markov Decision Process
CN116073449B (en) Controllable photovoltaic participation peak shaving method based on low carbon benefit and uncertainty
Shi et al. Optimization Scheduling Strategy with Multi-Agent Training Data Rolling Enhancement for Regional Power Grid Considering Operation Risk and Reserve Availability
Wang et al. Research on optimal equivalent capacity of wind farms based on probabilistic forecasting for power system planning

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