CN107196333A - Distributed photovoltaic assemblage classification method based on modularization index - Google Patents
Distributed photovoltaic assemblage classification method based on modularization index Download PDFInfo
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- H02J3/383—
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
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Abstract
The present invention relates to a kind of distributed photovoltaic assemblage classification method based on modularization index, including：Electrical distance between calculate node；Adjacency matrix between calculate node；The degree of calculate node；Computing module index；Resolution ability of the idle resource to overvoltage in computing cluster；Resolution ability of the energy storage to remaining overvoltage in computing cluster；Resolution ability of the photovoltaic to remaining overvoltage in computing cluster；Computing cluster pressure regulation capacity index；Calculate the colony integrated performance indications of distributed photovoltaic power generation based on modularization index and region voltage regulating power；Assemblage classification is carried out according to These parameters.
Description
Technical field
Drawn the present invention relates to a kind of distributed photovoltaic power generation cluster based on modularization index and region voltage regulating power
Divide method.
Background technology
With the raising of distributed photovoltaic power generation permeability in power distribution network, power distribution network stable operation faces lot of challenges,
Wherein trend is fallen to send and is particularly acute with voltage out-of-limit problem.Overvoltage not only limit power distribution network and receive distributed photovoltaic permeability
Ability, and seriously threaten the safe and stable operation of power distribution network.At present, accessed in some regional power distribution networks a large amount of
Distributed photovoltaic so that the pressure regulation problem faced in local distribution network operation is on the rise.
Current voltage control mode is broadly divided into three major types：Centralized control, using global optimization as target, but investment
Cost is high, communication burden weight；Control mode on the spot, with fast-response speed and Low investment cost advantage, but pressure regulation is limited in one's ability；
Distributed control mode, by regional coordination, improves voltage regulation capability and cost of investment, but effect of optimization is limited.
For above-mentioned deficiency, distributed photovoltaic power generation is subjected to assemblage classification, voltage control is carried out based on this, can
Coordinate comprehensive centralized Control, the advantage of control and distributed AC servo system on the spot between group by the way that point group is autonomous, with great potential.Pin
To assemblage classification control, existing assemblage classification index mainly has following two：
(1) many attribute cluster integrated performance indexs, optimum partition scheme is can determine using partitioning algorithm.But this refers to
The voltage power coupled relation between node is not considered in mark.
(2) corporations' detection algorithm is based on, modularization index is improved, it is considered to reactive voltage sensitivity and region reactive balance
Degree.But the index ignores influence of the active power to node voltage.
In addition, above-mentioned assemblage classification mode all lacks the consideration of region voltage ability of regulation and control and regulation and control cost, thus cluster
The reasonability of division is not enough, and clustered control effect is limited.
The content of the invention
In view of the above-mentioned problems, the purpose of the present invention is to overcome the deficiencies in the prior art, with reference to distributed photovoltaic feature, propose
A kind of distributed photovoltaic power generation assemblage classification method, carries out global voltage quick using the assemblage classification method of the present invention, can be with
Electrical distance and the controllable ability of region voltage can be taken into full account, effectively reduction voltage control cost.Technical scheme
It is as follows：
A kind of distributed photovoltaic assemblage classification method based on modularization index, comprises the following steps：
(1) τ is set as weight coefficient, and τ/(1- τ) characterizes the active ratio for participating in voltage-regulation and utilizing reactive-load compensation merely,
SVPAnd SVQActive and reactive voltage sensitivity matrix respectively between node, electrical distance between calculate node i and j Similarly；
(2) adjacency matrix between calculate node：Adjacency matrix A between nodeijFor electrical distance e between nodeijFunction, Aij
=1-eij/maxeij, its value is between [0,1]；
(3) degree of calculate node：ki=∑jAij, it is the degree of node i, m=∑si∑jAij/ 2, for all node weights it
The half of sum；
(4) computing module index：Modularization index ρ0It is degree of association overall target, ρ between the degree of association and group in group0Can
Ensure the strong electrical link between group's interior nodes,
Wherein,
(5) resolution ability of the idle resource to overvoltage in computing cluster：
Wherein, Δ ViFor the Over High-Limit Voltage amount of voltage highest node i in cluster k, more its value is 0, Q to voltage in limited timel
(j) Reactive Power Margin for being node j；
(6) resolution ability of the energy storage to remaining overvoltage in computing cluster；
Wherein, Δ ViFor the Over High-Limit Voltage amount of voltage highest node i in cluster k, more its value is 0, P to voltage in limited timeinj
(j) active power nargin is absorbed for node j energy storage；
(7) resolution ability of the photovoltaic to remaining overvoltage in computing cluster：
Wherein, Δ ViFor the Over High-Limit Voltage amount of voltage highest node i in cluster k, more its value is 0, P to voltage in limited timedec
(j) the active maximum reduction for the controllable photovoltaic for being node j, when reactive-load compensation and energy storage pressure regulation scarce capacity, reduces controllable light
Volt it is active still when can not eliminate overvoltage,As the penalty function in assemblage classification performance indications, for ensureing collection
Controllable ability of the resource to voltage in group；
(8) computing cluster pressure regulation capacity index：For cluster Ci, cluster pressure regulation capacity index is as follows：To make cluster voltage control cost minimization, Relationship of Coefficients is 1=α ＞ β ＞ γ ＞ 0, is determined
The sequencing of three kinds of regulating measures, and by idle, energy storage and the cost determination of photovoltaic, three's value influence assemblage classification knot
Really；
(9) the colony integrated performance of distributed photovoltaic power generation based on modularization index and region voltage regulating power is calculated to refer to
Mark is as follows：
Clustering performance index ρimThe bigger assemblage classification performance of value it is better；
(10) assemblage classification is carried out according to These parameters.
The present invention is directed to the grid-connected feature of distributed photovoltaic power generation, compared with prior art with advantages below：
(1) propose that the colony integrated performance of distributed photovoltaic power generation based on modularization index and region voltage regulating power refers to
Mark, assemblage classification is carried out according to this index.
(2) colony integrated performance indications are based on corporations' detection algorithm, consider electrical distance and region voltage between node
Controllable ability and regulation and control cost, the global total voltage control cost minimization after making point group's optimization autonomous.
(3) number of clusters can be optimized by colony integrated performance indications and be determined.
Brief description of the drawings
Fig. 1 is the assemblage classification result of the 10kV circuit of the present invention.
Table 1 is the whole network net power for being compressed into 10 scenes
Table 2 is the voltage-regulation resource of setting
Table 3 is modularization index ρ0With clustering performance index ρimContrast
Table 4 is the pressure regulation Cost comparisons of different assemblage classification results
Table 5 is the influence for increasing reactive power compensation planning to assemblage classification result and pressure regulation cost
Table 6 is the influence for increasing stored energy capacitance and reduction energy storage cost to assemblage classification result and pressure regulation cost
Embodiment
The present invention will be described with reference to the accompanying drawings and examples.
(1) assemblage classification integrated performance index
In view of active S between nodeVPWith reactive voltage sensitivity matrix SVQDisproportionate, electrical distanceWherein Similarly.τ is weight coefficient, τ/(1- τ)
The active ratio for participating in voltage-regulation and utilizing reactive-load compensation merely is characterized, the probability statistics based on historical data are determined.Region
(most roof photovoltaics become for the main reactive power compensator in cluster of the controllable ability of voltage, energy storage and controllable medium-sized photovoltaic converter
Flow device capacity smaller without possessing pressure regulation ability) to the recovery capability sign of voltage out-of-limit amount.It is proposed by the present invention to be based on module
The colony integrated performance indications of distributed photovoltaic power generation for changing index and region voltage regulating power are as follows：
Clustering performance index ρimThe bigger assemblage classification performance of value it is better.Wherein AijFor the adjacency matrix between node, for section
Electrical distance e between pointijFunction, Aij=1-eij/maxeij, its value is between [0,1].eijIt is true by voltage sensibility matrix
It is fixed.ki=∑jAij, it is the degree of node i.M=∑si∑jAij/ 2, for the half of all node weights sums.
Modularization index ρ0It is degree of association overall target between the degree of association and group in group,
ρ0It ensure that the strong electrical link between group interior nodes.With cluster CiExemplified by, cluster pressure regulation capacity index is as follows：Wherein,
Represent that idle resource is to the resolution ability of overvoltage in cluster,
Represent that energy storage is to the resolution ability of remaining overvoltage in cluster,
Represent resolution ability of the photovoltaic to remaining overvoltage in cluster.Wherein, Δ ViFor voltage highest node i in cluster k
Over High-Limit Voltage amount, voltage more prescribe a time limit its value be 0.Ql(j)、PinjAnd P (j)dec(j) be respectively node j Reactive Power Margin,
Energy storage absorbs active power nargin and the active maximum reduction of controllable photovoltaic.To make cluster voltage control cost minimization, coefficient
Relation is 1=α ＞ β ＞ γ ＞ 0, determines the sequencing of three kinds of regulating measures, and determined by the cost of idle, energy storage and photovoltaic
It is fixed, three's value influence assemblage classification result.When reactive-load compensation and energy storage pressure regulation scarce capacity, reduce controllable photovoltaic it is active according to
It is old when can not eliminate overvoltage,As the penalty function in assemblage classification performance indications, for ensureing resource pair in cluster
The controllable ability of voltage.
(2) example explanation
7 day datas (per 15min) to distribution as shown in Figure 1 are compressed, it is ensured that error is compressible into 10 below 1%
Scene is as shown in table 1.
The maximum circuit partition scheme of clustering performance index is made using tabu search algorithm search.The side of this assemblage classification
Formula ensure that the connectedness of cluster internal node, and can limit cluster scale by constraints.Utilize modularization exponent pair
Above-mentioned 10 scenes carry out assemblage classification, and the division result of 10 scenes is identical, as shown in Figure 1.This explanation assemblage classification knot
Fruit is relevant with parameter of double--layer grids, is influenceed smaller by power flow changing.
Region voltage regulating power is considered simultaneously, and assemblage classification is carried out to 10 scenes using integrated performance index.Assuming that
The degree of energy storage electric cost 0.7 yuan/kWh, photovoltaic unit 0.8 yuan/kWh of active power cost, accordingly, standardization setting β=0.8, γ=
0.7。
Set voltage-regulation resource as shown in table 2.
The assemblage classification result of 10 scenes is constant：Node 5 and 22 punishes group.As shown in table 3 and Fig. 1.
1. the pressure regulation cost of different assemblage classification results is contrasted.
Pressure regulation cost is set to Reactive Power Pricing for 100 yuan/MVar, and energy storage charge power electricity price is 700 yuan/MW, photovoltaic
Active electricity price is 800 yuan/MW, and active power loss electricity price is 400 yuan/MW.Voltage control method is to eliminate group merely with resource in group
Internal overvoltage, photovoltaic after first idle energy storage again, the sequencing of same class resource is determined by voltage sensibility size.Set before being based on
Voltage-regulation resource, overvoltage controls are carried out to two voltage out-of-limit scenes 1 and 7, and calculate pressure regulation cost, as shown in table 4.
As can be seen from Table 4：Although the mode regardless of group can call the idle and energy storage regulating measure of the overall situation, because
For electrical distance between node farther out, the voltage regulation result of unit power is simultaneously bad, and pressure regulation cost can on the contrary increased；Assemblage classification model
The outer resource of the nearer group of electrical distance can not be used by enclosing too small (7 and 22 points of groups), cause pressure regulation cost higher；Utilize carried cluster
Integrated performance index instructs assemblage classification, can effectively reduce the autonomous pressure regulation cost of cluster voltage.Web-based exercise changes in table
It is negative, is, because energy storage and photovoltaic reduce the active power sent on circuit, to cause line loss to reduce.
2. increase influence of the reactive power compensation planning to assemblage classification result and pressure regulation cost
Increase reactive power compensation planning, the assemblage classification result of scene 1 and 7 is constant, be still node 5 and 22 points of groups, pressure regulation into
This influence is as shown in table 5.From the result of table 5, appropriate increase region reactive power compensation planning can effectively reduce voltage control
Cost.
3. increase the influence of stored energy capacitance and reduction energy storage cost to assemblage classification result and pressure regulation cost
Increase after stored energy capacitance, the assemblage classification result of scene 1 and 7 is constant, is still node 5 and 22 points of groups, pressure regulation cost
It is in a slight decrease；If energy storage degree electricity cost is reduced to 0.6 yuan/below kWh, assemblage classification result will change, and scene 1 is by line
Road 4 and 22 points of groups, scene 7 are constant.As shown in table 6.
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Claims (1)
1. a kind of distributed photovoltaic assemblage classification method based on modularization index, comprises the following steps：
(1) τ is set as weight coefficient, and τ/(1- τ) characterizes the active ratio for participating in voltage-regulation and utilizing reactive-load compensation merely, SVPWith
SVQActive and reactive voltage sensitivity matrix respectively between node, electrical distance between calculate node i and j Similarly；
(2) adjacency matrix between calculate node：Adjacency matrix A between nodeijFor electrical distance e between nodeijFunction, Aij=1-
eij/maxeij, its value is between [0,1]；
(3) degree of calculate node：ki=∑jAij, it is the degree of node i, m=∑si∑jAij/ 2, for the one of all node weights sums
Half；
(4) computing module index：Modularization index ρ0It is degree of association overall target, ρ between the degree of association and group in group0It ensure that
Strong electrical link between group's interior nodes,
Wherein,
(5) resolution ability of the idle resource to overvoltage in computing cluster：
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(6) resolution ability of the energy storage to remaining overvoltage in computing cluster；
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(7) resolution ability of the photovoltaic to remaining overvoltage in computing cluster：
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The active maximum reduction of node j controllable photovoltaic, when reactive-load compensation and energy storage pressure regulation scarce capacity, reduces having for controllable photovoltaic
Work(remains unchanged when can not eliminate overvoltage,As the penalty function in assemblage classification performance indications, for ensureing that cluster is domestic-investment
Controllable ability of the source to voltage；
(8) computing cluster pressure regulation capacity index：For cluster Ci, cluster pressure regulation capacity index is as follows：To make cluster voltage control cost minimization, Relationship of Coefficients is 1=α ＞ β ＞ γ ＞ 0, is determined
The sequencing of three kinds of regulating measures, and by idle, energy storage and the cost determination of photovoltaic, three's value influence assemblage classification knot
Really；
(9) the colony integrated performance indications of distributed photovoltaic power generation based on modularization index and region voltage regulating power are calculated such as
Under：
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Clustering performance index ρimThe bigger assemblage classification performance of value it is better；
(10) assemblage classification is carried out according to These parameters.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107834596A (en) * | 2017-11-10 | 2018-03-23 | 东南大学 | Distributed photovoltaic cluster method for dynamically partitioning based on operation of power networks state aware |
| CN110380450A (en) * | 2019-08-13 | 2019-10-25 | 南方电网科学研究院有限责任公司 | A kind of photovoltaic control method, device, equipment and computer readable storage medium |
| CN110429656A (en) * | 2019-09-06 | 2019-11-08 | 南方电网科学研究院有限责任公司 | A kind of distributed energy cluster control method and device |
| CN110932288A (en) * | 2019-11-25 | 2020-03-27 | 国网安徽省电力有限公司六安供电公司 | Decentralized voltage optimization method based on distributed power generation cluster |
| CN112491057A (en) * | 2020-10-10 | 2021-03-12 | 东北电力大学 | Distributed energy storage control method with aim of eliminating node voltage out-of-limit of power distribution network |
| CN116865343A (en) * | 2023-09-01 | 2023-10-10 | 国网天津市电力公司滨海供电分公司 | Model-free self-adaptive control method, device and medium for distributed photovoltaic power distribution network |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140327313A1 (en) * | 2013-05-01 | 2014-11-06 | Tigo Energy, Inc. | System and method for low-cost, high-efficiency solar panel power feed |
| CN104361403A (en) * | 2014-10-27 | 2015-02-18 | 国家电网公司 | Optimal grouping configuration method of distributed generations and microgrid |
| CN105098762A (en) * | 2014-05-09 | 2015-11-25 | 国家电网公司 | Island dividing method for power distribution network having distributed power sources |
| CN105914788A (en) * | 2016-05-27 | 2016-08-31 | 南京工程学院 | Photovoltaic grid-connected inverter low-voltage ride-through control system |
-
2017
- 2017-06-07 CN CN201710422585.XA patent/CN107196333B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140327313A1 (en) * | 2013-05-01 | 2014-11-06 | Tigo Energy, Inc. | System and method for low-cost, high-efficiency solar panel power feed |
| CN105098762A (en) * | 2014-05-09 | 2015-11-25 | 国家电网公司 | Island dividing method for power distribution network having distributed power sources |
| CN104361403A (en) * | 2014-10-27 | 2015-02-18 | 国家电网公司 | Optimal grouping configuration method of distributed generations and microgrid |
| CN105914788A (en) * | 2016-05-27 | 2016-08-31 | 南京工程学院 | Photovoltaic grid-connected inverter low-voltage ride-through control system |
Non-Patent Citations (1)
| Title |
|---|
| 段天元: "含高渗透间歇性能源的哈密电网电压稳定性分析", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107834596A (en) * | 2017-11-10 | 2018-03-23 | 东南大学 | Distributed photovoltaic cluster method for dynamically partitioning based on operation of power networks state aware |
| CN107834596B (en) * | 2017-11-10 | 2021-03-19 | 东南大学 | Distributed photovoltaic cluster dynamic partitioning method based on power grid operation state perception |
| CN110380450A (en) * | 2019-08-13 | 2019-10-25 | 南方电网科学研究院有限责任公司 | A kind of photovoltaic control method, device, equipment and computer readable storage medium |
| CN110380450B (en) * | 2019-08-13 | 2021-03-12 | 南方电网科学研究院有限责任公司 | Photovoltaic control method, device, equipment and computer readable storage medium |
| CN110429656A (en) * | 2019-09-06 | 2019-11-08 | 南方电网科学研究院有限责任公司 | A kind of distributed energy cluster control method and device |
| CN110932288A (en) * | 2019-11-25 | 2020-03-27 | 国网安徽省电力有限公司六安供电公司 | Decentralized voltage optimization method based on distributed power generation cluster |
| CN110932288B (en) * | 2019-11-25 | 2021-05-25 | 国网安徽省电力有限公司六安供电公司 | Decentralized voltage optimization method based on distributed power generation cluster |
| CN112491057A (en) * | 2020-10-10 | 2021-03-12 | 东北电力大学 | Distributed energy storage control method with aim of eliminating node voltage out-of-limit of power distribution network |
| CN116865343A (en) * | 2023-09-01 | 2023-10-10 | 国网天津市电力公司滨海供电分公司 | Model-free self-adaptive control method, device and medium for distributed photovoltaic power distribution network |
| CN116865343B (en) * | 2023-09-01 | 2024-03-29 | 国网天津市电力公司滨海供电分公司 | Model-free self-adaptive control method, device and medium for distributed photovoltaic power distribution network |
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