CN108074035A - More scene distribution formula photovoltaics access power distribution network operation risk assessment method system - Google Patents
More scene distribution formula photovoltaics access power distribution network operation risk assessment method system Download PDFInfo
- Publication number
- CN108074035A CN108074035A CN201711206448.9A CN201711206448A CN108074035A CN 108074035 A CN108074035 A CN 108074035A CN 201711206448 A CN201711206448 A CN 201711206448A CN 108074035 A CN108074035 A CN 108074035A
- Authority
- CN
- China
- Prior art keywords
- scene
- photovoltaic
- distribution network
- power
- mrow
- 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
- 238000009826 distribution Methods 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000012502 risk assessment Methods 0.000 title claims abstract description 12
- 238000005070 sampling Methods 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000005315 distribution function Methods 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 4
- 238000011156 evaluation Methods 0.000 claims description 4
- 230000004075 alteration Effects 0.000 claims description 3
- 238000000342 Monte Carlo simulation Methods 0.000 description 13
- 238000002474 experimental method Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000005259 measurement Methods 0.000 description 3
- 240000002853 Nelumbo nucifera Species 0.000 description 2
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 2
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- 244000131316 Panax pseudoginseng Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 230000002146 bilateral effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000000053 physical method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- Water Supply & Treatment (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- General Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
Appraisal procedure proposed by the present invention mainly from the node voltage deviation ratio that is brought on power distribution network and percent harmonic distortion after distributed photovoltaic access influence and caused by power loss be described, simultaneously, consider the characteristic of photovoltaic output, comprehensive assessment has been carried out to the operation risk of the distributed photovoltaic access system under more scenes, above-mentioned methods of risk assessment considers the probabilistic model of photovoltaic output, according to different types of typical photovoltaic output model, photovoltaic is obtained by Monte-Carlo step to contribute, and then COMPREHENSIVE CALCULATING is carried out to the power distribution network operation risk under different scenes, it realizes and comprehensive assessment is carried out to the distributed photovoltaic access power distribution network operation risk under more scenes.
Description
Technical field
The present invention relates to distributed photovoltaic access electric power system operation risk assessment technical field more particularly to more of one kind
Scape distributed photovoltaic accesses power distribution network operation risk assessment method system.
Background technology
At present, the intelligent grid using distribution intelligence as important symbol is widely studied, and safe and reliable receiving wind
Electricity, photovoltaic generation distributed power supply are then one of critical functions of following intelligent network distribution.
The access of distributed photovoltaic will change distribution network structure and trend, traditional radial distribution networks become more power supplys
System will bring certain risk to the operation of power distribution network, control.These characteristics of distributed photovoltaic cause it in reliability and wind
Traditional stand-by power supply cannot be fully equivalent in the assessment of danger, existing distribution network reliability is difficult to continue with methods of risk assessment
It is applicable in, it is necessary to establish the power distribution network risk assessment index containing distributed photovoltaic, the power distribution network risk for studying distributed photovoltaic is commented
Estimate method.
On the other hand, photovoltaic is the intermittent renewable energy, and as ambient weather factor influences, power generation has fluctuation
And randomness, Qualitative research method is no longer applicable in tradition really.
The content of the invention
It is necessary to propose a kind of more scene distribution formula photovoltaic access power distribution network operation risk assessment method systems.
A kind of more scene distribution formula photovoltaic access power distribution network operation risk assessment method systems, comprise the following steps：
The first step determines the probability that photovoltaic output scene and each scene occur, scene is numbered (i=1 ... S)；
Second step, for the photovoltaic power curve of scene i, using the probability of parameter identification method calculating photovoltaic power curve
Distributed constant, so as to obtain the photovoltaic output probability-distribution function f of scene ii；
3rd step, according to the photovoltaic output probability-distribution function of scene i, sampling obtains photovoltaic output, if jth time is sampled
The photovoltaic arrived is contributed as Pj；
4th step, the photovoltaic output P obtained by jth time samplingj, sample obtained photovoltaic output P according to jth timejRespectively into
The Load flow calculation and harmonic flow calculation of row power distribution network obtain the node voltage deviation ratio and voltage distortion rate of power distribution network, calculate
Node voltage power loss and voltage distortion rate power loss caused by voltage deviation rate is out-of-limit and voltage distortion rate is out-of-limit, into
And the operation risk desired value r of jth time photovoltaic access power distribution network is calculatedj；
Whether the 5th step, judgement sampling number reach maximum, if so, in next step, if it is not, then j=j+1, and return
3rd step；
6th step, judges whether scene number reaches maximum, if so, in next step, if it is not, then i=i+1, and return
Second step；
The distributed photovoltaic access power distribution network fortune that more scenes are considered under each scene is calculated according to the following formula for 7th step
Row risk indicator r；
In formula, r is the power networks risk comprehensive evaluation index for considering the quality of voltage under more scenes, and i is i-th
Scape, piFor the corresponding scene probability of occurrence of i-th of scene, for a certain given area, counted by local meteorological department's big data
It obtains, for constant, Δ UiFor the node voltage deviation ratio of PCC points, THDiFor the node voltage aberration rate of PCC points, P (Δ Ui) and P
(THDi) it is respectively node voltage power loss caused by node voltage deviation ratio is out-of-limit and the out-of-limit caused work(of voltage distortion rate
Rate is lost.
The node voltage deviation ratio and percent harmonic distortion that the present invention mainly brings power distribution network after distributed photovoltaic access
Influence and caused by power loss be described, simultaneously, it is contemplated that photovoltaic contribute characteristic, to the distributed photovoltaic under more scenes
The operation risk of access system has carried out comprehensive assessment.Methods of risk assessment considers the probabilistic model of photovoltaic output, according to not
The typical photovoltaic output model of same type obtains photovoltaic by Monte-Carlo step and contributes, and then to the distribution under different scenes
Network operation risk carries out COMPREHENSIVE CALCULATING, realizes that carrying out synthesis to the distributed photovoltaic access power distribution network operation risk under more scenes comments
Estimate.
Description of the drawings
Fig. 1 is power distribution network schematic diagram of the somewhere containing distributed generation resource in the embodiment of the present invention.
Fig. 2 is to consider that the distributed photovoltaic of more scenes accesses power distribution network operation risk calculation process schematic diagram in the present invention.
Fig. 3 is power distribution network line chart used by test system of the present invention.
Fig. 4 is the typical daily output graph of the first typical scene in somewhere in the embodiment of the present invention.
Fig. 5 is the typical daily output graph of second of typical scene in somewhere in the embodiment of the present invention.
Fig. 6 is the typical daily output graph of the third typical scene in somewhere in the embodiment of the present invention.
Fig. 7 is the typical daily output graph of the 4th kind of typical scene in somewhere in the embodiment of the present invention.
Specific embodiment
It in order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to making further in conjunction with the embodiments
It is bright, for those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings
Obtain other attached drawings.
The present invention is to access power distribution network based on one side distributed photovoltaic to be on most significant influence caused by power distribution network
Influence to quality of voltage mainly includes two aspect of node voltage deviation ratio and voltage distortion rate, is on the other hand due to photovoltaic
Power generation is intermittent energy source, and contributing, there is stochastic volatility and weather condition, season and moment etc. to have important relationship, deposit
In a variety of output scenes, it is therefore desirable to carry out considering analysis after considering the operating condition under different scenes.
(1) the node voltage deviation ratio of system
The power distribution network in China is mostly closed loop design open loop operation, so can be equivalent for the power distribution network in normal operation
For single supply radiativity network, as shown in Figure 1.Ignore the admittance of feeder line herein, load is born using the three-phase symmetrical of power invariability
Lotus model.Distributed generation resource has the characteristics that economic, environmental protection, should multi output active power as far as possible.Simultaneously in view of access
Distributed generation resource single-machine capacity in power distribution network is smaller, does not have power regulation ability generally, distributed wind turbine and photovoltaic are usual
It is operated in constant dc power control pattern, therefore using distributed generation resource as being analyzed with the PQ nodes of firm power factor.
In equivalent single supply radiativity power distribution network shown in Fig. 1, node 0 is commonly connected for power distribution network and higher level's power transmission network
Point (i.e. PCC points), 1~n of node are the node in power distribution network.Be connected on each node of model shown in figure distributed generation resource and
Load, by the distributed generation resource of some node and load power be arranged to 0 represent be not connected on the node distributed generation resource and
Load.
Distributed generation resource is directly connected on load bus, with load uncertainty direction on the contrary, so having certain counteracting load
Effect, the load with negative value can be construed as, the voltage deviation rate at access distributed generation resource posterior nodal point k can represent
For shown in following formula：
In formula：R and X represents resistance and the reactance of feeder line, PDG+jQDGFor the output power of distributed generation resource, PL+jQLIt is negative
The power of lotus, Pj+jQjFor the power that feeder line ij flows through, feeder line ij is the feeder line between two nodes in power grid.
National standard GB/T12325-2008《Power quality-supply voltage deviation》In the limit value of supply voltage deviation ratio is provided
It is as follows：
1) the sum of 35kV and the positive and negative absolute value of the bias of more than supply voltage are no more than the 10% of nominal voltage.(such as electricity of powering
In pressure during lower deviation jack per line (being positive or negative), by larger absolute value of the bias as measurement foundation)；
2) 20kV and following three phase supply voltage deviation rate are ± the 7% of nominal voltage；
3) 220V single phase power supplies voltage deviation rate is+the 7% of nominal voltage, -10%；
It is smaller to supply terminals capacity of short circuit, power supply distance is longer and has the use of particular/special requirement to supply voltage deviation ratio
Family, by supplying, electricity consumption bilateral agreement determines.
Therefore, in the distribution network systems of distributed photovoltaic system access, node voltage should meet following constraints,
UN(1-ε1)≤Ui≤UN(1+ε2) (2)
In formula：UNFor the nominal voltage of system；ε1、ε2For the tolerance rate of national regulations.
(2) voltage distortion rate caused by harmonic wave
One photo-voltaic power supply can be regarded as a kind of nonlinear-load to distribution feeder harmonic, become through overpower
The photovoltaic of parallel operation access power grid can generate harmonic current, if photovoltaic is sufficiently large in the harmonic current sometime generated, distribution
The voltage distortion of net will be above standard as defined in distortion limit value.
After distributed generation resource access power grid in addition to synchronous machine, the harmonic voltage of points of common connection should meet GB/T
14549-1993《Power quality public electric wire net harmonic wave》Regulation, as shown in table 1.
Table 1：
With reference to system node voltage deviation rate and voltage distortion rate index, propose to consider that the distributed photovoltaic under more scenes connects
Enter power distribution network operation risk comprehensive evaluation index and its calculation formula is as follows：
In formula, r is the power networks risk comprehensive evaluation index for considering the quality of voltage under more scenes, and i is i-th
Scape, piFor the corresponding scene probability of occurrence of i-th of scene, for a certain given area, counted by local meteorological department's big data
It obtains, for constant, Δ UiFor the node voltage deviation ratio of PCC points, THDiFor the node voltage aberration rate of PCC points, P (Δ Ui) and P
(THDi) it is respectively node voltage power loss caused by node voltage deviation ratio is out-of-limit and the out-of-limit caused work(of voltage distortion rate
Rate is lost.
It can be assessed for the operation risk of above more scene distribution formula photovoltaic access power distribution networks based on Monte Carlo Method,
It is as follows：
The first step determines the probability that photovoltaic output scene and each scene occur, scene is numbered (i=1 ... S)；
Second step, for the photovoltaic power curve of scene i, using the probability of parameter identification method calculating photovoltaic power curve
Distributed constant, so as to obtain the photovoltaic output probability-distribution function fi of scene i；
3rd step, according to the photovoltaic output probability-distribution function of scene i, sampling obtains photovoltaic output, if jth time is sampled
The photovoltaic arrived is contributed as Pj；
4th step, the photovoltaic output P obtained by jth time samplingj, sample obtained photovoltaic output P according to jth timejRespectively into
The Load flow calculation and harmonic flow calculation of row power distribution network obtain the node voltage deviation ratio and voltage distortion rate of power distribution network, calculate
Node voltage power loss and voltage distortion rate power loss caused by voltage deviation rate is out-of-limit and voltage distortion rate is out-of-limit, into
And the operation risk desired value r of jth time photovoltaic access power distribution network is calculatedj；
Whether the 5th step, judgement sampling number reach maximum, if so, in next step, if it is not, then j=j+1, and return
3rd step；
6th step, judges whether scene number reaches maximum, if so, in next step, if it is not, then i=i+1, and return
Second step；
The distributed photovoltaic access power distribution network fortune that more scenes are considered under each scene is calculated according to the following formula for 7th step
Row risk indicator r.
The typical scene that photovoltaic is contributed can be analyzed by clustering method and obtained, and typical day can also be provided by meteorological department
Light irradiance curve under the conditions of gas is converted to the power curve under the conditions of typical weather by power producing characteristics.Known photovoltaic goes out
The typical scene of power is the premise and basis condition analyzed herein.
Under a kind of definite photovoltaic output typical scene, photovoltaic output accordingly obeys a certain definite probability distribution,
Have more scholar both at home and abroad and study confirmation, photovoltaic is contributed obeys Beta distributions within a few houres.It is also distributed herein using Beta
It contributes to photovoltaic and carries out probability description.According to specific probability distribution, Monte Carlo simulation approach may be employed, to light under the scene
The power distribution network of volt access carries out Load flow calculation and harmonic flow calculation, voltage deviation rate and voltage distortion rate is obtained, so as to obtain
Power distribution network operation risk index under the scene.
The basic principle and step of Monte Carlo simulation approach are mainly as follows：
It is most intuitively general to form the measurement of data probability theory for theory of the Monte Carlo method based on probability and quantity
It reads, i.e., the generation of one event may be with many possible outcomes, then can be the definition of probability of an event
The quantity that event occurs is to the ratio of be likely to occur result.Monte Carlo method has identical principle with this method, only
But the reverse procedure of the principle, i.e., the number that measurement event occurs, and the probability occurred according to this as the event.Act is most
Simply example will measure the ratio that certain block area accounts for entire space, it is only necessary to arbitrarily be drawn a little at random in space, and calculate
The number for entering the point of this block area accounts for the ratio of all the points.Such as the value calculated with Monte Carlo method, simulate the result of calculating
It has been infinitely close to.The reliability of Monte Carlo method is based on two very important theorems, the i.e. law of large numbers in probability theory
And central-limit theorem.Law of great number ensures that the estimate that Monte Carlo method calculates can be received with the increase of number realization
It holds back in actual value；And central-limit theorem then gives the scope of simulation error after limited number of time simulated experiment.
The convergency factor of Monte Carlo method isComparatively convergence rate is slower, it means that if
Standard deviation, which narrows down to original half, to be needed number realization increasing to original four times；Increase the required precision of a decimal point
Experiment number increases as original 100 times.It is mainly comprised the following steps：
(1) construct or describe probabilistic process
For inherently having the problem of random nature, such as PARTICLE TRANSPORT FROM problem, mainly correctly describe and simulate this
Probabilistic process for not originally being the certain problem of random nature, for example calculates definite integral, must just construct a people in advance
For probabilistic process, its some parameters are exactly the solution of required problem.It will be converted without the problem of random nature
For random nature the problem of.
(2) realize to be distributed from known probability and sample
After constructing probabilistic model, since various probabilistic models can be regarded as by various probability distribution structures
Into, therefore the stochastic variable (or random vector) of known probability distribution is generated, just become and realize that Monte-carlo Simulation is real
The basic means tested, this is also the reason for Monte Carlo method is referred to as random sampling.Most simple, most basic, most important one
A probability distribution is being uniformly distributed (or distributed rectangular) on (0,1).Random number is exactly with this equally distributed random
Variable.Random number sequence is exactly the overall Simple sample for having this distribution, that is, one has this distribution
Mutually independent random variable sequence.Random number is led to the problem of, is exactly the sampling problem from this distribution.On computers,
Random number can be generated with physical method, but it is expensive, it is impossible to it repeats, it is inconvenient for use.Another method is with mathematics recursion
Formula generates.The sequence so generated, it is different from real random number sequence, so referred to as pseudo random number or pseudorandom number sequence
Row.But, show that it has similar property with real random number or random number sequence by a variety of statistical checks, therefore
It can be used using it as real random number.There are various methods by known distribution random sampling, with being uniformly distributed from (0,1)
Sampling is different, these methods are all realized by means of random sequence, that is to say, that are all premised on generating random number
's.The basic tool of Monte Carlo simulation is realized it can be seen that random number is for we.
(3) various estimators are established
It is, in general, that constructing after probabilistic model simultaneously can therefrom sample, that is, after realizing simulated experiment, we will determine one
A stochastic variable, as it is required the problem of solution, we it be referred to as unbiased esti-mator.Various estimators are established, are equivalent to mould
The result of draft experiment is investigated and registered, and therefrom obtains the solution of problem.
Below by taking the Rural Power Distribution Network of somewhere as an example, distributed photovoltaic access is calculated with reference to a variety of sunrise scenes in this area
The operation risk assessment index r of power distribution network.
The system branch parameter and bus load data of this area's network system are as shown in table 2,
Table 2：
It is 150% to set distributed photovoltaic permeability, is accessed in power distribution network end, and access node number is 18,19,22,23.
This area's whole year photovoltaic power curve is analyzed, obtains four quasi-representative photovoltaic output power curves, as Fig. 4-
Shown in Fig. 7.Known photovoltaic, which is contributed, obeys the Beta probability distribution of two parameter, and four kinds of typical days are obtained using least-square analysis
α under gas field scape, β parameter, the results are shown in Table 3, and table 3 is the photovoltaic output probability Distribution Model ginseng under typical weather scene
Number：
Table 3：
By operation risk index proposed by the present invention and method, obtained result of calculation, as shown in table 4：
Table 4：
Specifically, the distributed photovoltaic operation risk calculating under more weather scenes of this area is as follows：
The first step, it is typical scene 1 to select scene, and probability of occurrence 0.25 samples to obtain photovoltaic by Monte Carlo Method
Power generating value, and obtain out-of-limit caused power loss P (the Δ U of voltage deviation rate by Load flow calculation and harmonic flow calculationi)=
1.4408MW, power loss P (Δ THD caused by voltage distortion rate caused by harmonic wavei)=2.256MW, then in typical scene 1
Risk indicator be exactly
R=pi·(P(ΔUi)+P(THDi))=0.25 × (1.4408+2.256)=0.9242MW
Similarly, the risk indicator under other scenes is calculated.
Finally, the distributed photovoltaic operation risk under more weather scenes is
Module or unit in device of the embodiment of the present invention can be combined, divided and deleted according to actual needs.
The above disclosure is only the preferred embodiments of the present invention, cannot limit the right model of the present invention with this certainly
It encloses, one of ordinary skill in the art will appreciate that realize all or part of flow of above-described embodiment, and will according to right of the present invention
Made equivalent variations are sought, still falls within and invents covered scope.
Claims (1)
1. a kind of more scene distribution formula photovoltaic access power distribution network operation risk assessment method systems, it is characterised in that including following step
Suddenly：
The first step determines the probability that photovoltaic output scene and each scene occur, scene is numbered (i=1 ... S)；
Second step, for the photovoltaic power curve of scene i, using the probability distribution of parameter identification method calculating photovoltaic power curve
Parameter, so as to obtain the photovoltaic output probability-distribution function f of scene ii；
3rd step, according to the photovoltaic output probability-distribution function of scene i, sampling obtains photovoltaic output, if what jth time sampling obtained
Photovoltaic is contributed as Pj；
4th step, the photovoltaic output P obtained by jth time samplingj, sample obtained photovoltaic output P according to jth timejMatched somebody with somebody respectively
The Load flow calculation and harmonic flow calculation of power grid obtain the node voltage deviation ratio and voltage distortion rate of power distribution network, calculate by electricity
The out-of-limit caused node voltage power loss out-of-limit with voltage distortion rate of pressure deviation ratio and voltage distortion rate power loss, Jin Erji
It calculates and obtains the operation risk desired value r of jth time photovoltaic access power distribution networkj；
Whether the 5th step, judgement sampling number reach maximum, if so, in next step, if it is not, then j=j+1, and return to the 3rd
Step；
6th step, judges whether scene number reaches maximum, if so, in next step, if it is not, then i=i+1, and return to second
Step；
The distributed photovoltaic access distribution network operation wind that more scenes are considered under each scene is calculated according to the following formula for 7th step
Dangerous index r；
<mrow>
<mi>r</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>S</mi>
</munderover>
<mo>{</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>&CenterDot;</mo>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mo>(</mo>
<mrow>
<msub>
<mi>&Delta;U</mi>
<mi>i</mi>
</msub>
</mrow>
<mo>)</mo>
<mo>+</mo>
<mi>P</mi>
<mo>(</mo>
<mrow>
<msub>
<mi>THD</mi>
<mi>i</mi>
</msub>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>}</mo>
</mrow>
In formula, r is the power networks risk comprehensive evaluation index for considering the quality of voltage under more scenes, and i is i-th of scene, piFor
The corresponding scene probability of occurrence of i-th of scene for a certain given area, is counted to obtain, is by local meteorological department's big data
Constant, Δ UiFor the node voltage deviation ratio of PCC points, THDiFor the node voltage aberration rate of PCC points, P (Δ Ui) and P (THDi)
The respectively out-of-limit caused node voltage power loss of node voltage deviation ratio and the out-of-limit caused power loss of voltage distortion rate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711206448.9A CN108074035B (en) | 2017-11-27 | 2017-11-27 | Multi-scene distributed photovoltaic access power distribution network operation risk assessment method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711206448.9A CN108074035B (en) | 2017-11-27 | 2017-11-27 | Multi-scene distributed photovoltaic access power distribution network operation risk assessment method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108074035A true CN108074035A (en) | 2018-05-25 |
| CN108074035B CN108074035B (en) | 2021-09-14 |
Family
ID=62157631
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711206448.9A Active CN108074035B (en) | 2017-11-27 | 2017-11-27 | Multi-scene distributed photovoltaic access power distribution network operation risk assessment method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108074035B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108805745A (en) * | 2018-06-06 | 2018-11-13 | 浙江大学 | A kind of flexibility appraisal procedure of power distribution network |
| CN109165846A (en) * | 2018-08-23 | 2019-01-08 | 国网上海市电力公司 | A kind of power distribution network methods of risk assessment containing distributed photovoltaic power |
| CN111130098A (en) * | 2019-12-30 | 2020-05-08 | 国网辽宁省电力有限公司电力科学研究院 | Risk assessment method for power distribution network system with distributed power supplies |
| CN112290602A (en) * | 2020-11-10 | 2021-01-29 | 上海电气工程设计有限公司 | Micro-grid comprehensive operation method and system with heavy oil generator set and photovoltaic |
| CN112380490A (en) * | 2020-09-09 | 2021-02-19 | 浙江华云信息科技有限公司 | Voltage fluctuation evaluation method for accessing distributed power supply to transformer area |
| CN113629778A (en) * | 2021-08-06 | 2021-11-09 | 国网安徽省电力有限公司经济技术研究院 | Design method of distributed photovoltaic power distribution network light storage system |
| CN115102168A (en) * | 2022-08-24 | 2022-09-23 | 山东大学 | Time-varying current evaluation method and system considering distributed photovoltaic harmonic coupling |
| CN117350549A (en) * | 2023-12-04 | 2024-01-05 | 国网江苏省电力有限公司经济技术研究院 | Distribution network voltage risk identification method, device and equipment considering output correlation |
| CN117638878A (en) * | 2023-11-16 | 2024-03-01 | 国网安徽省电力有限公司铜陵供电公司 | Relay protection analysis method for distributed photovoltaic access power distribution network based on probability model |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102594216A (en) * | 2012-03-21 | 2012-07-18 | 江西省电力科学研究院 | Probability assessment method of effects of distributed photovoltaic power supply access |
| CN105186514A (en) * | 2015-10-20 | 2015-12-23 | 南京南瑞集团公司 | Distribution network safety evaluating and early warning method after large scale distributed photovoltaic grid connected |
| US9507367B2 (en) * | 2012-04-09 | 2016-11-29 | Clemson University | Method and system for dynamic stochastic optimal electric power flow control |
| CN107039995A (en) * | 2016-11-28 | 2017-08-11 | 国网湖北省电力公司宜昌供电公司 | A kind of distributed photovoltaic power access planing method for considering power quality problem |
-
2017
- 2017-11-27 CN CN201711206448.9A patent/CN108074035B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102594216A (en) * | 2012-03-21 | 2012-07-18 | 江西省电力科学研究院 | Probability assessment method of effects of distributed photovoltaic power supply access |
| US9507367B2 (en) * | 2012-04-09 | 2016-11-29 | Clemson University | Method and system for dynamic stochastic optimal electric power flow control |
| CN105186514A (en) * | 2015-10-20 | 2015-12-23 | 南京南瑞集团公司 | Distribution network safety evaluating and early warning method after large scale distributed photovoltaic grid connected |
| CN107039995A (en) * | 2016-11-28 | 2017-08-11 | 国网湖北省电力公司宜昌供电公司 | A kind of distributed photovoltaic power access planing method for considering power quality problem |
Non-Patent Citations (2)
| Title |
|---|
| 崔红芬等: "《多接入点分布式光伏发电系统与配电网交互影响研究》", 《电力系统保护与控制》 * |
| 黎嘉明等: "《光伏发电功率持续时间特性的概率分布定量分析》", 《电力系统自动化》 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108805745B (en) * | 2018-06-06 | 2021-10-29 | 浙江大学 | Flexibility evaluation method for power distribution network |
| CN108805745A (en) * | 2018-06-06 | 2018-11-13 | 浙江大学 | A kind of flexibility appraisal procedure of power distribution network |
| CN109165846A (en) * | 2018-08-23 | 2019-01-08 | 国网上海市电力公司 | A kind of power distribution network methods of risk assessment containing distributed photovoltaic power |
| CN111130098A (en) * | 2019-12-30 | 2020-05-08 | 国网辽宁省电力有限公司电力科学研究院 | Risk assessment method for power distribution network system with distributed power supplies |
| CN111130098B (en) * | 2019-12-30 | 2023-03-24 | 国网辽宁省电力有限公司电力科学研究院 | Risk assessment method for power distribution network system with distributed power supplies |
| CN112380490A (en) * | 2020-09-09 | 2021-02-19 | 浙江华云信息科技有限公司 | Voltage fluctuation evaluation method for accessing distributed power supply to transformer area |
| CN112380490B (en) * | 2020-09-09 | 2023-08-29 | 浙江华云信息科技有限公司 | Voltage fluctuation evaluation method for access of transformer area to distributed power supply |
| CN112290602A (en) * | 2020-11-10 | 2021-01-29 | 上海电气工程设计有限公司 | Micro-grid comprehensive operation method and system with heavy oil generator set and photovoltaic |
| CN112290602B (en) * | 2020-11-10 | 2024-03-26 | 上海电气工程设计有限公司 | Micro-grid comprehensive operation method and system with heavy oil generator set and photovoltaic |
| CN113629778A (en) * | 2021-08-06 | 2021-11-09 | 国网安徽省电力有限公司经济技术研究院 | Design method of distributed photovoltaic power distribution network light storage system |
| CN113629778B (en) * | 2021-08-06 | 2023-07-21 | 国网安徽省电力有限公司经济技术研究院 | Design method of distributed photovoltaic power distribution network optical storage system |
| CN115102168A (en) * | 2022-08-24 | 2022-09-23 | 山东大学 | Time-varying current evaluation method and system considering distributed photovoltaic harmonic coupling |
| CN115102168B (en) * | 2022-08-24 | 2023-04-11 | 山东大学 | Time-varying current evaluation method and system considering distributed photovoltaic harmonic coupling |
| CN117638878A (en) * | 2023-11-16 | 2024-03-01 | 国网安徽省电力有限公司铜陵供电公司 | Relay protection analysis method for distributed photovoltaic access power distribution network based on probability model |
| CN117350549A (en) * | 2023-12-04 | 2024-01-05 | 国网江苏省电力有限公司经济技术研究院 | Distribution network voltage risk identification method, device and equipment considering output correlation |
| CN117350549B (en) * | 2023-12-04 | 2024-02-23 | 国网江苏省电力有限公司经济技术研究院 | Distribution network voltage risk identification method, device and equipment considering output correlation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108074035B (en) | 2021-09-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108074035A (en) | More scene distribution formula photovoltaics access power distribution network operation risk assessment method system | |
| CN102593829B (en) | Method and device for determining transmission section in consideration of key branch circuit | |
| CN108306303A (en) | A kind of consideration load growth and new energy are contributed random voltage stability assessment method | |
| CN106684915A (en) | Wind-hydrogen coupling power generation system optimization method and device thereof | |
| CN107145707A (en) | It is a kind of to count and photovoltaic is exerted oneself the power distribution network transformer planing method of uncertain and overall life cycle cost | |
| CN106354985A (en) | Power distribution system reliability assessment method considering distributed power supply | |
| Wu et al. | Reliability evaluation of the solar power system based on the Markov chain method | |
| Zhang et al. | Data-driven sizing planning of renewable distributed generation in distribution networks with optimality guarantee | |
| CN110532642A (en) | A kind of calculation method that integrated energy system probability can flow | |
| CN115017854A (en) | Method for calculating maximum allowable capacity of DG (distributed generation) of power distribution network based on multidimensional evaluation index system | |
| CN114336628A (en) | Photovoltaic power supply access distribution network safety evaluation method based on random power flow | |
| Yang et al. | A two-stage scenario generation method for wind-solar joint power output considering temporal and spatial correlations | |
| CN109993368A (en) | Power forecasting method based on unusual spectral factorization and shot and long term memory network | |
| de Lima Vianna et al. | A General Analysis of the Distributed Generation Impact on Electrical Energy Planning | |
| Aibin et al. | Reliability evaluation of distribution network with distributed generation based on latin hypercube sequential sampling | |
| Han et al. | An assessment approach of the power system vulnerability considering the uncertainties of wind power integration | |
| CN109861293A (en) | The appraisal procedure that photovoltaic uncertainty influences electric system small-signal stability | |
| Kim et al. | Probabilistic estimation of wind generating resources based on the spatio-temporal penetration scenarios for power grid expansions | |
| Guocheng et al. | Reliability analysis method for microgrid with intermittent distributed generations | |
| Du et al. | Hosting capacity assessment in distribution networks considering wind–photovoltaic–load temporal characteristics | |
| CN106546824A (en) | Based on the system harmonic impedance method of estimation of electrical network containing photovoltaic that variable coefficient is returned | |
| Tan et al. | Estimation method of line loss rate in low voltage area based on mean shift clustering and BP neural network | |
| CN110456223A (en) | A kind of power distribution network short circuit current measuring method containing distributed generation resource and electric car | |
| Tao et al. | Time series probabilistic power flow calculation of distribution network based on nonparametric kernel density estimation | |
| Ji et al. | Analysis and Assessment of Operation Risk for Power System with Photovoltaic Power Stations |
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 |