CN102751725B - A kind of power distribution network overload method for recognizing risk state of power - Google Patents
A kind of power distribution network overload method for recognizing risk state of power Download PDFInfo
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Abstract
The present invention discloses a kind of power distribution network overload method for recognizing risk state of power, namely the historical load information before adopting power distribution network t in certain a period of time, load prediction information after t load real-time measurement information and t sometime in section, by equivalent load method from actuality aspect, the calculated load index in continuation aspect and foresight aspect, generate overload index severity grade, and with overload index severity grade for foundation, to actuality aspect, the overload index of continuation aspect and foresight aspect is analyzed, according to power distribution network overload risk status determining step, judge whether electrical network is in overload risk status in t, and carry out the dynamic Continuous Tracking of power distribution network overload risk status and identification.This method is applicable to identification and the early warning of overload risk status in power distribution network self-healing control process.
Description
Technical field
The present invention relates to distribution system analysis and control technology field, be specifically related to a kind of power distribution network overload method for recognizing risk state of power.
Background technology
In power distribution network self-healing control, power supply capacity weighs an important indicator of power distribution network high-quality and efficient, economic reliability service, and power distribution network whether running overload weighs the whether sufficient importance of power supply capacity.Along with the fast development of local economy, user power utilization load is also in continuous growth, the burden of grid equipment also constantly increases, the risk classifications that overload risk one of having become that power distribution network faces is important, how to find overload risk early, to avoid the serious running overload of power distribution network, it is an important research content in the assessment of power distribution network self-healing control running status.
At present, the achievement in research of overload risk assessment aspect is a lot of, but all mainly lays particular emphasis on the possibility that occurs overload risk from planning angle, static angular and the order of severity is comprehensively analyzed.In actual applications, mainly carry out evaluated load level from overload multiple and permission overload time two aspect, the accuracy of its evaluation result and reliability are all very poor.
Summary of the invention
For the deficiency of existing achievement in research, the present invention proposes a kind of overload method for recognizing risk state of power, from operation angle, comprehensive employing historical load information, actual measurement information on load, load prediction information, comprehensive Dynamic Identification is carried out to the overload risk that power distribution network faces, the accuracy of power distribution network overload Risk Identification, reliability can be improved, provide foundation for power distribution network carries out overload risk Initiative Defense.
A kind of power distribution network overload method for recognizing risk state of power provided by the invention, its improvements are, described method is: the historical load information before adopting power distribution network t in certain a period of time, load prediction information after t load real-time measurement information and t sometime in section, by equivalent load method from actuality aspect, the calculated load index in continuation aspect and foresight aspect, generate overload index severity grade, and with described overload index severity grade for foundation, to described actuality aspect, the overload index of continuation aspect and foresight aspect is analyzed, according to power distribution network overload risk status determining step, judge whether electrical network is in overload risk status in t, and carry out the dynamic Continuous Tracking of power distribution network overload risk status and identification.
Wherein, described actuality refers to the one side that overload risk has occurred; The overload index steps calculating described actuality aspect is:
According to the historical load information in the Δ t1 time before t, calculate the equivalent load in the Δ t1 time and overload index, with the Overload in the Δ t1 time before judging t.
Wherein, described continuation refers to that overload risk is occurring and the one side that will continue; The overload index steps calculating described continuation aspect is:
According to the historical load information of the t2 of Δ for the previous period of t and and t after the prediction information on load of Δ t3 in a period of time, calculate the equivalent load in the Δ t2+ Δ t3 time and overload index, and in conjunction with the actual measurement information on load of t, to judge t overload and continued case thereof.
Wherein, described foresight refers to one side overload risk occurring in the future or overload risk can not occur; The overload index steps calculating described foresight aspect is:
According to the prediction information on load in the Δ t4 time after t, calculate the equivalent load in the Δ t4 time and overload index, with the Overload in the Δ t4 time after judging t.
Wherein, described power distribution network overload risk status determining step is as follows:
(1) if actuality overload index, continuation overload index and foresight overload index are all without overload phenomenon, then judge that electrical network is in normal operating condition;
(2) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon not serious, residue index all without overload phenomenon, then judges that electrical network is in normal operating condition;
(3) if actuality overload index, continuation overload index and foresight overload index all occur that overload phenomenon is not serious, then judge that current electric grid is not in overload risk status, provides overload phenomenon warning message;
(4) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon comparatively serious, then judge that current electric grid is in overload risk status, provides overload Risk-warning information;
(5) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon serious, then judge that current electric grid is in overload risk status, provide overload Risk-warning information, and formulate overload risk-aversion control strategy.
Wherein, judge whether power distribution network is in overload risk status in t, if:
Judge that power distribution network is in normal condition, then judge whether index exceeding standard, if without index exceeding standard, then the load prediction information after historical load information, t load real-time measurement information and t before again obtaining power distribution network t in certain a period of time sometime in section; If there is index exceeding standard, then the accumulative index exceeding standard duration, and the index duration is stored and carries out the identification of the risk status of power distribution network overload next time;
Judge that power distribution network exists overload phenomenon, but when not reaching risk status, then the accumulative index exceeding standard duration, and the index duration is stored and carries out the identification of the risk status of power distribution network overload next time;
Judge that power distribution network exists overload risk, and according to overload risk class determination methods, judge that overload risk is not serious, only carry out overload risk alarm, the accumulative index exceeding standard duration simultaneously, the index duration is stored, and carries out the identification of the risk status of power distribution network overload next time.
Judge that power distribution network exists overload risk, and according to overload risk class determination methods, if overload risk is serious, then while carrying out overload risk alarm, and provide overload risk-aversion control strategy; Simultaneously the accumulative index exceeding standard duration, the index duration is stored, and proceeds the continuous identification of overload risk status.
Wherein, described overload index comprises:
1. overload multiple index K---for reflecting that single load monitoring point exceedes the degree of permissible load, computing formula is;
2. overload time index T is allowed---for reflecting overload duration length, reflect overload degree with overload multiple index;
Wherein, the corresponding corresponding permission overload time index limit value of overload multiple criterion limit value.
3. overload multiple is to voltage influence exponential sensitivity index A---and for reflecting the degree that the rate of qualified voltage that overload causes reduces, its calculation expression is:
A＝f(K,ΔR
U)；
Wherein, Δ R
ufor rate of qualified voltage change; K is overload multiple.
4. overload multiple is to line loss Intrusion Index sensitivity index B---and be used for the order of severity reflecting that the line loss rate that causes of overload raises, its calculation expression is:
B＝f(K,ΔR
Line-loss)；
Wherein, Δ R
line-lossfor line loss rate change; K is overload multiple.
5. overload rate index R
over-load---for reflecting single load monitoring point overload time degree in monitoring time section, its expression formula is:
6. comprehensive overload rate index CR
over-load---be used for reflecting locally or the size of overall overload scope, its expression formula is:
Wherein, the step calculating equivalent load is:
If have n discrete load before or after t in Δ T time, load value is respectively P
1, P
2..., P
n, adopt following formulae discovery to go out the equivalent negative charge values P of t
t:
(1) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(2) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(3) geometric mean method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(4) harmonic-mean method is utilized to ask secondary equivalent load P
mcomputing formula as follows:
Wherein, described load prediction isoeffect curve is according to described formula 1)-formula 4) curve that is linked to be of the not equivalent negative charge values in the same time that calculates.The present invention also can first off-line according to formula 1)-4) calculate equivalent load and draw load prediction isoeffect curve, then by load prediction isoeffect curve application on site (being namely applied to the equivalent load of foresight aspect), the time in line computation is saved.
Compared with the prior art, beneficial effect of the present invention is:
The comprehensive historical load information of the method for the invention, actual measurement information on load, load prediction information, realize multi-time Scales, various dimensions, dynamic overload Risk Identification, acquired results comprehensively, accurately, reliably, the Initiative Defense realizing overload risk for power distribution network self-healing control provides reliable basis.
Multiple load point in any Δ T period are converted into an equivalent load point by the calculating equivalent load that the present invention proposes, thus reach simplification simulation calculating number of times, the object of more visual and clear observation load dynamic trend.And it makes use of arithmetic average method, square mean number method, geometric mean method and harmonic-mean fado kind average method to obtain equivalent load, its amount of calculation is little, simple to operate.
Accompanying drawing explanation
Fig. 1 is a kind of power distribution network overload Risk Identification flow chart provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
A kind of power distribution network overload method for recognizing risk state of power provided by the invention, its be adopt power distribution network t before (this time period, user oneself determined in certain a period of time, be generally 1min ~ 30min) historical load information, after t load real-time measurement information and t, (this time period, user oneself determined in section sometime, be generally 1min ~ 30min) load prediction information, by equivalent load method from actuality aspect, the calculated load index in continuation aspect and foresight aspect, generate overload index severity grade, and with described overload index severity grade for foundation, to described actuality aspect, the overload index of continuation aspect and foresight aspect is analyzed, according to power distribution network overload risk status determining step, judge whether electrical network is in overload risk status in t, and carry out the dynamic Continuous Tracking of power distribution network overload risk status and identification.Power distribution network overload Risk Identification flow process as shown in Figure 1, specifically comprises the steps:
(1) obtain power distribution network t before historical load information in certain a period of time, t load real-time measurement information, load prediction information after t sometime in section;
(2) by the historical load data required for the calculating of equivalent load method and load prediction data;
(3) calculate the overload index of actuality, continuation, foresight three aspects, generate overload index severity grade;
(4) with overload index severity grade for foundation, judge actuality, continuation, foresight overload index grade;
(5) according to power distribution network overload risk status identification step, judge whether current time electrical network is in overload risk status.
(6) if judge that electrical network is in normal condition, then judge whether index exceeding standard, if without index exceeding standard, then return step (1); If there is index exceeding standard, then the accumulative index exceeding standard duration, and the index duration is stored, return step (1) simultaneously.
(7) if judge that electrical network exists overload phenomenon, but overload risk status is not reached, i.e. when overload phenomenon severity grade is 1 grade, time, the then accumulative index exceeding standard duration, and the index duration is stored, return step (1) simultaneously.
(8) if judge that electrical network exists overload risk, i.e. overload phenomenon severity grade be 2 grades or 3 grades time, if when overload phenomenon severity grade is 2 grades, continue the accumulative index exceeding standard duration, and the index duration is stored, return step (1) simultaneously and proceed the continuous identification of overload risk status.
(9) if judge that electrical network exists overload risk, i.e. overload phenomenon severity grade be 2 grades or 3 grades time, if when overload phenomenon severity grade is 3 grades, then while carrying out overload risk alarm, and provide overload risk-aversion control strategy; Meanwhile, continue the accumulative index exceeding standard duration, and the index duration is stored, return step (1) simultaneously and proceed the continuous identification of overload risk status.
Wherein:
I. described overload index comprises:
1. overload multiple index K---be used for reflecting that single load monitoring point exceedes the degree of permissible load, computing formula is;
2. overload time index T is allowed---be used for reflecting overload duration length, reflect overload degree with overload multiple index comprehensive.
Wherein, the corresponding corresponding permission overload time index limit value of certain overload multiple criterion limit value.
3. overload multiple is to voltage influence exponential sensitivity index A---and be used for the degree reflecting that the rate of qualified voltage that causes of overload reduces, its calculation expression is:
A＝f(K,ΔR
U)
Wherein, Δ R
ufor rate of qualified voltage change; K is overload multiple.
4. overload multiple is to line loss Intrusion Index sensitivity index B---and be used for the order of severity reflecting that the line loss rate that causes of overload raises, its calculation expression is:
B＝f(K,ΔR
Line-loss)
Wherein, Δ R
line-lossfor line loss rate change; K is overload multiple.
5. overload rate index R
over-load---be used for reflecting single load monitoring point overload time degree in monitoring time section.
6. comprehensive overload rate index CR
over-load---be used for reflecting locally or the size of overall overload scope.
II. in step (3),
Described actuality refers to the one side that overload risk has occurred; The overload index steps calculating described actuality aspect is:
Before adopting t, (this time period, user oneself determined Δ t1, be generally 1min ~ 30min) historical load information in the time, calculate the equivalent load in the Δ t1 time and overload index, with the Overload in the Δ t1 time before weighing t;
Described continuation refers to that overload risk is occurring and will continue for some time the one side of (determining according to Δ t3); The overload index steps calculating described continuation aspect is:
(this time period, user oneself determined the t2 of Δ for the previous period of employing t, be generally 1min ~ 30min) historical load information and, after t in a period of time Δ t3 (this time period, user oneself determined, be generally 1min ~ 30min) prediction information on load, calculate the equivalent load in the Δ t2+ Δ t3 time and overload index, and with the actual measurement information on load of t, comprehensively to weigh t overload and continued case thereof;
Described foresight refers to one side overload risk occurring in the future or overload risk can not occur; The overload index steps calculating described foresight aspect is:
After adopting t, (this time period, user oneself determined Δ t4, be generally 1min ~ 30min) prediction information on load in the time, calculate the equivalent load in the Δ t4 time and overload index, with the Overload in the Δ t4 time after weighing t.Wherein, the equivalent load of foresight aspect according to the described load prediction isoeffect curve value of off-line generation, also can calculate online.
III., in step (3), the step calculating equivalent load is:
The equivalent negative charge values P of certain moment t
tsize and selected time interval Δ T relevant with the Equivalent calculation method that adopts.If have n discrete load before or after t in Δ T time, load value is respectively P
1, P
2..., P
n, following 4 kinds of methods can be adopted to calculate the equivalent negative charge values P of t
t:
(1) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(2) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(3) geometric mean method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(4) harmonic-mean method is utilized to ask secondary equivalent load P
mcomputing formula as follows:
IV. overload index severity grade is divided into 4 grades, and rank is higher, and overload phenomenon is more serious, its respectively:
(1) without overload phenomenon
Definition: without overload phenomenon, this is 0 grade of overload, and power distribution network is in normal operating condition;
Determination methods: all overload indexs, all in normal range (NR), without out-of-limit, are then in 0 grade of overload; 0 grade of overload judges that typical case is as shown in table 1.
(2) overload phenomenon is not serious
Definition: overload phenomenon is not serious, and this is 1 grade of overload, does not think that power distribution network enters overload risk status, only carries out overload early-warning;
Determination methods: allow overload multiple index limits if only have overload multiple index overrun but do not exceed, other overload indexs all in allowable value, are then in 1 grade of overload; 1 grade of overload judges that typical case is as shown in table 1.
(3) overload phenomenon is more serious
Definition: overload phenomenon is comparatively serious, and this is 2 grades of overloads, thinks that power distribution network enters overload risk status, and only carries out overload Risk-warning, without the need to carrying out risk-aversion control;
Determination methods: if overload multiple index exceedes allow overload multiple index limits, and allow overload time index also to exceed allowable value, other overload index all in allowable value, is then in 2 grades of overloads; 2 grades of overloads judge that typical case is as shown in table 1.
(4) overload phenomenon is serious
Definition: overload phenomenon is serious, and this is 3 grades of overloads, thinks that power distribution network enters overload risk status, and carries out overload Risk-warning, and formulates overload risk-aversion control strategy;
Determination methods: if overload multiple index exceedes allow overload multiple index limits, and allow overload time index also to exceed allowable value, have at least an overload index to exceed allowable value in other overload index, be then in 3 grades of overloads; 4 grade overloads judge as shown in table 1.
Table 1
V. in step (5), power distribution network overload risk status identification step comprises:
(1) if actuality overload index, continuation overload index, foresight overload index are 0 grade of overload, then think that electrical network is in normal operating condition.
(2) if actuality overload index, continuation overload index, foresight overload index all have at least a kind of overload index to be 1 grade of overload, and all the other indexs are 0 grade of overload, then think that electrical network is in normal operating condition.
(3) if actuality overload index, continuation overload index, foresight overload index are 1 grade of overload, then do not think that current electric grid is in overload risk status, now, only provide overload phenomenon warning message, do not think overload risk.
(4) if actuality overload index, continuation overload index, foresight overload index have at least a kind of overload index to be 2 grades of overloads, then think that current electric grid is in overload risk status, provide overload Risk-warning information simultaneously, but without the need to carrying out overload risk-aversion control;
(5) if actuality overload index, continuation overload index, foresight overload index have at least a kind of overload index to be 3 grades of overloads, then think that current electric grid is in overload risk status, provide overload Risk-warning information simultaneously, and overload risk-aversion control strategy need be formulated, for traffic control personnel provide overload risk-aversion to control foundation.
In practical application, can formulate according to above-mentioned design the overload risk judgment method meeting special requirement according to actual needs.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit, although with reference to above-described embodiment to invention has been detailed description, those of ordinary skill in the field are to be understood that: still can modify to the specific embodiment of the present invention or equivalent replacement, and not departing from any amendment of spirit and scope of the invention or equivalent replacement, it all should be encompassed in the middle of right of the present invention.
Claims (4)
1. a power distribution network overload method for recognizing risk state of power, it is characterized in that, described method is: the historical load information before adopting power distribution network t in certain a period of time, load prediction information after t load real-time measurement information and t sometime in section, by equivalent load method from actuality aspect, the calculated load index in continuation aspect and foresight aspect, generate overload index severity grade, and with described overload index severity grade for foundation, to described actuality aspect, the overload index of continuation aspect and foresight aspect is analyzed, according to power distribution network overload risk status determining step, judge whether electrical network is in overload risk status in t, and carry out the dynamic Continuous Tracking of power distribution network overload risk status and identification,
Described actuality refers to the one side that overload risk has occurred; The overload index steps calculating described actuality aspect is:
According to the historical load information in the Δ t1 time before t, calculate the equivalent load in the Δ t1 time and overload index, with the Overload in the Δ t1 time before judging t;
Described continuation refers to that overload risk is occurring and the one side that will continue; The overload index steps calculating described continuation aspect is:
According to the historical load information of the t2 of Δ for the previous period of t and and t after the prediction information on load of Δ t3 in a period of time, calculate the equivalent load in the Δ t2+ Δ t3 time and overload index, and in conjunction with the actual measurement information on load of t, to judge t overload and continued case thereof;
Described foresight refers to one side overload risk occurring in the future or overload risk can not occur; The overload index steps calculating described foresight aspect is:
According to the prediction information on load in the Δ t4 time after t, calculate the equivalent load in the Δ t4 time and overload index, with the Overload in the Δ t4 time after judging t;
Described power distribution network overload risk status determining step is as follows:
(1) if actuality overload index, continuation overload index and foresight overload index are all without overload phenomenon, then judge that electrical network is in normal operating condition;
(2) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon not serious, residue index all without overload phenomenon, then judges that electrical network is in normal operating condition;
(3) if actuality overload index, continuation overload index and foresight overload index all occur that overload phenomenon is not serious, then judge that current electric grid is not in overload risk status, provides overload phenomenon warning message;
(4) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon comparatively serious, then judge that current electric grid is in overload risk status, provides overload Risk-warning information;
(5) if actuality overload index, continuation overload index and foresight overload index have at least a kind of overload phenomenon serious, then judge that current electric grid is in overload risk status, provide overload Risk-warning information, and formulate overload risk-aversion control strategy;
Judge whether power distribution network is in overload risk status in t, if:
Judge that power distribution network is in normal condition, then judge whether index exceeding standard, if without index exceeding standard, then the load prediction information after historical load information, t load real-time measurement information and t before again obtaining power distribution network t in certain a period of time sometime in section; If there is index exceeding standard, then the accumulative index exceeding standard duration, and the index duration is stored and carries out the identification of the risk status of power distribution network overload next time;
Judge that power distribution network exists overload phenomenon, but when not reaching risk status, then the accumulative index exceeding standard duration, and the index duration is stored and carries out the identification of the risk status of power distribution network overload next time;
Judge that power distribution network exists overload risk, and according to overload risk class determination methods, judge that overload risk is not serious, only carry out overload risk alarm, the accumulative index exceeding standard duration simultaneously, the index duration is stored, and carries out the identification of the risk status of power distribution network overload next time
Judge that power distribution network exists overload risk, and according to overload risk class determination methods, if overload risk is serious, then while carrying out overload risk alarm, and provide overload risk-aversion control strategy; Simultaneously the accumulative index exceeding standard duration, the index duration is stored, and proceeds the continuous identification of overload risk status;
Described overload index comprises:
1. overload multiple index K---for reflecting that single load monitoring point exceedes the degree of permissible load, computing formula is;
2. overload time index T is allowed---for reflecting overload duration length, reflect overload degree with overload multiple index;
Wherein, the corresponding corresponding permission overload time index limit value of overload multiple criterion limit value;
3. overload multiple is to voltage influence exponential sensitivity index A---and for reflecting the degree that the rate of qualified voltage that overload causes reduces, its calculation expression is:
A＝f(K,ΔR
U)；
Wherein, Δ R
ufor rate of qualified voltage change; K is overload multiple;
4. overload multiple is to line loss Intrusion Index sensitivity index B---and be used for the order of severity reflecting that the line loss rate that causes of overload raises, its calculation expression is:
B＝f(K,ΔR
Line-loss)；
Wherein, Δ R
line-lossfor line loss rate change; K is overload multiple;
5. overload rate index R
over-load---for reflecting single load monitoring point overload time degree in monitoring time section, its expression formula is:
6. comprehensive overload rate index CR
over-load---be used for reflecting locally or the size of overall overload scope, its expression formula is:
2. power distribution network overload method for recognizing risk state of power as claimed in claim 1, is characterized in that, the step calculating equivalent load is:
If have n discrete load before or after t in Δ T time, load value is respectively P
1, P
2..., P
n, adopt following formulae discovery to go out the equivalent negative charge values P of t
t:
(1) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(2) arithmetic average method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(3) geometric mean method is utilized to ask secondary equivalent load P
tcomputing formula as follows:
(4) harmonic-mean method is utilized to ask secondary equivalent load P
mcomputing formula as follows:
3. power distribution network overload method for recognizing risk state of power as claimed in claim 1, is characterized in that, the described load prediction isoeffect curve value that the equivalent load of described foresight aspect generates according to off-line.
4. power distribution network overload method for recognizing risk state of power as claimed in claim 3, it is characterized in that, described load prediction isoeffect curve is according to described formula 1)-formula 4) curve that is linked to be of the not equivalent negative charge values in the same time that calculates.
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| CN103065266B (en) * | 2012-12-20 | 2014-10-22 | 中国电力科学研究院 | Power distribution network system data self-healing interactive method |
| CN103049826B (en) * | 2013-01-06 | 2016-05-11 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Automated system is safeguarded in operation of power networks |
| CN104979903B (en) * | 2015-05-12 | 2017-10-13 | 贵州电力试验研究院 | A kind of centralized control center patrols dimension analysis method and device |
| CN110555573A (en) * | 2018-05-30 | 2019-12-10 | 中国电力科学研究院有限公司 | Distribution transformer burnout risk early warning method and system |
| CN109191283A (en) * | 2018-08-30 | 2019-01-11 | 成都数联铭品科技有限公司 | Method for prewarning risk and system |
| JP6991410B1 (en) * | 2021-02-26 | 2022-01-13 | 三菱電機株式会社 | Voltage management device, voltage command device, power system monitoring system, measuring device, voltage management method and voltage management program |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102063651A (en) * | 2010-11-10 | 2011-05-18 | 中国电力科学研究院 | Urban power grid risk evaluation system based on on-line data acquisition |
| CN102255309A (en) * | 2011-07-15 | 2011-11-23 | 中国电力科学研究院 | Self-healing control method of centralized distribution network |
| CN102289582A (en) * | 2011-08-10 | 2011-12-21 | 中国电力科学研究院 | Method for recognizing risk state of power distribution network |
-
2012
- 2012-07-13 CN CN201210243260.2A patent/CN102751725B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102063651A (en) * | 2010-11-10 | 2011-05-18 | 中国电力科学研究院 | Urban power grid risk evaluation system based on on-line data acquisition |
| CN102255309A (en) * | 2011-07-15 | 2011-11-23 | 中国电力科学研究院 | Self-healing control method of centralized distribution network |
| CN102289582A (en) * | 2011-08-10 | 2011-12-21 | 中国电力科学研究院 | Method for recognizing risk state of power distribution network |
Non-Patent Citations (1)
| Title |
|---|
| 互联电力***可靠性评估的改进等效模型;汪兴强;《电工技术学报》;20110930;第26卷(第9期);201-207 * |
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| CN102751725A (en) | 2012-10-24 |
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