CN105279617A - Method for calculating reliability influence of power distribution network project to be built on power network - Google Patents
Method for calculating reliability influence of power distribution network project to be built on power network Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention discloses a method for calculating the reliability influence of a power distribution network project to be built on a power network, and the method comprises following steps: collecting operating data of the power distribution network; dividing the power distribution network into regional blocks; estimating the main circuit length of circuits inside the regional blocks, the main circuit diameter, the number of branch circuits, branch circuit length, branch circuit diameter, the number of distribution transformers, and capacity parameter; calculating the reliable parameter of each regional block, and constructing and simplifying a network model; calculating load category factors: calculating load distribution coefficient; constructing a multi-element load model; and completing quantitative calculation of the reliability of the power distribution network. According to the invention, the thought of regional blocks is adopted; by utilizing the existing parameter to estimate the regional block parameter, the power distribution network model is simplified; the limitations that the basic parameter is hard to be collected and that the load state is single during the reliability quantitative process are overcome; by fully utilizing the experience of a basis operating worker, the data collecting amount is reduced and the operation performance is strong; and by utilizing theoretical analysis method to perform quantitative calculation of the reliability of the project to be built, the reliability influence can be quantified rapidly.
Description
Technical field
The present invention is specifically related to the computing method that a kind of power distribution network project yet to be built affects electric network reliability.
Background technology
Along with the development of national economy technology and the raising of national life level, electric energy has become one of energy the most indispensable in people's daily life.Therefore, power supply reliability just becomes the primary goal of electrical network.Simultaneously, State Grid Corporation of China also clearly proposes " to improve power supply reliability for target, promotes idea of development, planning of persisting in reunification, unified standard; construction and upgrading develop simultaneously, and all-round construction is rational in infrastructure, the Modern power distribution net of advanced technology, flexibility and reliability, economical and efficient." power distribution network thinking of development.The power supply reliability work pendulum of power distribution network is in the top priority of company power distribution net development.
National grid all will carry out the construction of power distribution network every year, with improve power distribution network efficiency, improve residential electricity consumption condition and living standard.At the beginning of the construction of power distribution network project, just need to consider the impact of distribution network construction project on distribution network reliability.Existing distribution network reliability computing method, because the basic data needed collects difficulty, therefore can only carry out Calculation of Reliability analysis to specific network structure; On the other hand, existing reliability calculation method and theory are all analyze specific load condition, truly can not reflect diversity and the polytrope of power distribution network running status, cause the result of calculating comprehensively, truly can not reflect actual distribution network reliability level.
Summary of the invention
The object of the present invention is to provide and a kind ofly can truly reflect according to operation of power networks data information the computing method that the power distribution network project yet to be built of distribution network reliability affects electric network reliability under all types of loading condition.
The computing method that this power distribution network provided by the invention project yet to be built affects electric network reliability, comprise the steps:
S1. the basic run book of power distribution network before and after power distribution network project construction yet to be built is collected;
S2. according to the data that step S1 collects, by arbitrary without switch isolation and the element set be interconnected is defined as region unit in all for power distribution network circuits;
S3. all region units are obtained to step S2, circuit backbone length, backbone wire diameter, branch's number, branch line length, branch line wire diameter, distribution transforming number of units and attaching capacity parameter in the block of discreet area;
S4. utilize the parameter that step S3 obtains, calculate the dependability parameter of regional block according to following formula:
In formula
be respectively backbone, branch line, the average time for repair of breakdowns of distribution transforming (containing fuse) and average year fault correction time;
S5. according to the region unit that step S2 obtains, and the connection line between region unit, structure simplified network model;
S6. according to the region unit that step S2 obtains, the Overload Class of each region unit is determined, and according to the following formula calculated load classification factor:
In formula
be the Overload Class factor of the i-th type load,
be the load of the i-th type load, P is the attaching capacity of region unit;
S7. the power load distributing coefficient of regional block is calculated:
In formula
for region unit S
ithe attaching capacity estimated,
for the total volume of circuit, P is the burden with power of circuit,
for the normalized Overload Class factor, calculated by the Overload Class factor of region units all in circuit:
S8. power distribution network typical case day k-factor is collected, the polynary load model of structure first section of circuit and region unit:
The polynary load model of circuit head end is:
P
j＝K·E
P in formula
jfor the payload of any time point j of each region unit, K is typical case's day k-factor, and E is typical case day electricity E;
The polynary load model of region unit is:
In formula
for the payload of any time point j of each region unit,
for the power load distributing coefficient of this region unit, P
jfor the payload of any time point j of each region unit;
S9. the polynary load model that the dependability parameter of region unit, the simplified network model of step S5 acquisition and the step S8 that obtain according to S4 obtain, the Quantitative Reliability completing power distribution network calculates;
Described power distribution network project yet to be built also comprises the steps: the computing method that electric network reliability affects
S10. following three formulas are utilized to calculate power distribution network project yet to be built to the quantization influence of reliability:
Amount when Δ SAIDI is line outage in formula; Δ SAIFI is line outage number of users; Δ AENS is that line outage lacks delivery.
The basic run book of the power distribution network described in step S1, comprises the network structure of power distribution network, the distribution line length of power distribution network and load current, the average time for repair of breakdowns of distribution line and average year fault correction time, distribution line load type, total attaching capacity of power distribution network, power distribution network typical case day k-factor and typical case's day electricity.
Connection line described in step S5, for classifying according to overhead transmission line and cable line: the interconnected type of overhead transmission line comprises multi-joint network, simply connected network, radial fashion; The interconnected type of cable line comprises dicyclic, monocyclic, twinshot, injection formula form; Circuit that is built on stilts and cable mixed type is turned for the low circuit determination connection line type of ability with trunk wire diameter.
Overload Class described in step S6 comprises city load and rural area load.
Described city load comprises industrial class city, resident's class city and commercial city.
Described rural area load comprises market town, town government location, the combination area of city and country or the II class village group of relying on I class village group of economic and technological development zone, small processing industry or agricultural production comparatively flourishing, and based on the III class village group of rural area basic production with life.
The Quantitative Reliability of described power distribution network calculates, and calculates for adopting Failure Mode Effective Analysis method.
The computing method that this power distribution network provided by the invention project yet to be built affects electric network reliability, adopt the thought of subregion block, existing parameter is utilized to carry out region unit parameter prediction, and electricity distribution network model is suitably simplified, therefore overcome underlying parameter in distribution network reliability quantizing process and collect the limitation such as difficult, load condition is single; Meanwhile, the experience of basic operations staff should be made full use of in the process of parameter prediction and load distribution, make to collect data few and want easy to understand, strong operability; Final employing theoretical analysis method carries out Quantitative Reliability calculating to power distribution network project yet to be built, realizes the rapid qualitative of power distribution network planning scheme to reliability effect.
Accompanying drawing explanation
Fig. 1 is method flow schematic diagram of the present invention.
Fig. 2 is the parameter prediction schematic diagram of simplified network model of the present invention.
Fig. 3 is the schematic diagram of polynary load model of the present invention.
Embodiment
As shown in Figure 1, be method flow schematic diagram of the present invention: the computing method that this power distribution network provided by the invention project yet to be built affects electric network reliability, comprise the steps:
S1. the basic run book of power distribution network before and after power distribution network project construction yet to be built is collected:
The basic run book of described power distribution network, comprises the network structure of power distribution network, the distribution line length of power distribution network and load current, the average time for repair of breakdowns of distribution line and average year fault correction time, distribution line load type, total attaching capacity of power distribution network, power distribution network typical case day k-factor and typical case's day electricity.
S2. according to the data that step S1 collects, by arbitrary without switch isolation and the element set be interconnected is defined as region unit in all for power distribution network circuits;
S3. all region units are obtained to step S2, circuit backbone length, backbone wire diameter, branch's number, branch line length, branch line wire diameter, distribution transforming number of units and attaching capacity parameter in the block of discreet area:
Backbone length estimates the length referring to backbone in estimation region block, more accurately estimates by consulting account data, also shaft tower quantity and average span can carry out comparatively guestimate according to basic unit operations staff experience and in calmodulin binding domain CaM block.
Backbone wire diameter estimates the average wire diameter referring to backbone in estimation region block, calculates, also can estimate all kinds of wire diameter length according to basic unit's operations staff's experience and calculate by consulting account data and carrying out the average wire diameter of backbone.
Branch's number estimates the number referring to estimation region Kuai Nei secondary branch, three grades and do not include estimation range in inferior division.Obtaining by consulting account data, also can estimate to obtain according to basic unit operations staff experience.
Branch line length estimates the length referring to branch line in estimation region block, more accurately estimates by consulting account data, also shaft tower quantity and average span can carry out comparatively guestimate according to basic unit operations staff experience and in calmodulin binding domain CaM block.
Branch line wire diameter estimates the average wire diameter referring to each branch line in estimation region block, calculates, also can estimate all kinds of wire diameter length according to basic unit's operations staff's experience and calculate by consulting account data and carrying out the average wire diameter of branch line.
Distribution transforming number of units estimates the number of units referring to distribution transforming in estimation region block, obtains by consulting account data, also can estimate to obtain according to basic unit operations staff experience.
Attaching capacity is estimated the installed capacity referred in estimation region block and is accessed with outside the access capacity that region unit provides electric energy, obtains by consulting account data.
S4. utilize the parameter that step S3 obtains, calculate the dependability parameter of regional block according to following formula:
In formula
be respectively backbone, branch line, the average time for repair of breakdowns of distribution transforming (containing fuse) and average year fault correction time;
Due in region unit without on-off element, fault pervasion scope and the scope that restores electricity are again border with switchgear, so region unit has following characteristic in reliability: Arbitrary Fault produces homogeneity impact to all nodes in region unit and element, in the same area block, node has identical reliability index arbitrarily, region unit is equal to element, has all character of element.Therefore, a region unit S
ijust be equal to an element, its dependability parameter is obtained by backbone parameter, branch line parameter, merger of distribution transforming (containing fuse) parameter estimated all in this region unit.
S5. according to the region unit that step S2 obtains, and the connection line between region unit, structure simplified network model:
Described connection line, for classifying according to overhead transmission line and cable line: the interconnected type of overhead transmission line comprises multi-joint network, simply connected network, radial fashion; The interconnected type of cable line comprises dicyclic, monocyclic, twinshot, injection formula form; Turn for the low circuit determination connection line type of ability for circuit that is built on stilts and cable mixed type with trunk wire diameter;
The parameter prediction schematic diagram of simplified network model as shown in Figure 2.
S6. according to the region unit that step S2 obtains, the Overload Class of each region unit is determined, and according to the following formula calculated load classification factor:
In formula
be the Overload Class factor of the i-th type load,
be the load of the i-th type load, P is the attaching capacity of region unit;
Overload Class comprises city load and rural area load:
Described city load comprises industrial class city, resident's class city and commercial city;
Described rural area load comprises market town, town government location, the combination area of city and country or the II class village group of relying on I class village group of economic and technological development zone, small processing industry or agricultural production comparatively flourishing, and based on the III class village group of rural area basic production with life;
The load that the Overload Class factor larger representation unit capacity is corresponding is larger.The Overload Class factor is not unalterable, and it becomes with the actual conditions of each bar circuit.
S7. the power load distributing coefficient of regional block is calculated:
In formula
for region unit S
iestimate capacity,
for the total volume of circuit, P is the burden with power of circuit,
for the normalized Overload Class factor, calculated by the Overload Class factor of region units all in circuit:
S8. power distribution network typical case day k-factor is collected, the polynary load model of structure first section of circuit and region unit:
The polynary load model of circuit head end is:
P
j＝K·E
P in formula
jfor the payload of any time point j of each region unit, K is typical case's day k-factor, and E is typical case day electricity E;
The polynary load model of region unit is:
In formula
for the payload of any time point j of each region unit,
for the power load distributing coefficient of this region unit, P
jfor the payload of any time point j of each region unit;
The schematic diagram of polynary load model as shown in Figure 3.
S9. the polynary load model that the dependability parameter of region unit, the simplified network model of step S5 acquisition and the step S8 that obtain according to S4 obtain, the Quantitative Reliability adopting Failure Mode Effective Analysis method to complete power distribution network calculates;
The Failure Mode Effective Analysis method adopted be a kind of principle simply, Reliability Evaluation Algorithm clearly.The concrete analysis step of the method is: list according to the dependability parameter of each element whole states that system may occur, then to the impact analysis that each element fault produces, list all possible fault effects event table, more comprehensively draw the reliability index of each load point and system accordingly.
S10. following three formulas are utilized to calculate power distribution network project yet to be built to the quantization influence of reliability:
Amount when Δ SAIDI is line outage in formula; Δ SAIFI is line outage number of users; Δ AENS is that line outage lacks delivery.
Below in conjunction with a specific embodiment, the technology of the present invention is further detailed:
Choose A respectively, B, C, D tetra-class carries out area reliability calculating for distinguishing district, what wherein category-A typical case power supply area was chosen is Changsha Dong Tang service area, sweet osmanthus garden, Changsha service area, what category-B typical case power supply area was chosen is trees ridge, Changsha service area, Changsha Yu Jiawan service area, what C quasi-representative power supply area was chosen is Changsha environmental protection service area, Changsha vast stretch of wooded country service area, Huo Changping town, Shaodong County, Shaoyang, Lian Qiao town, Hei Tianpu town, what D quasi-representative power supply area was chosen is She Tianqiao town, Shaodong County, Shaoyang, water Dong Jiang town, Changsha Yan Nong service area, selected representative region line construction type contains multi-joint network, simply connected network, radial overhead transmission line and dicyclic, monocyclic, twinshot, the various ways such as injection formula cable line." power supply network computational analysis and decision-assistant software " (being called for short CEES method) that comparing calculation analysis adopts CEES star electrically to develop.
Table 1 typical service area summary table
(1) error analysis
1) single line reliability error analysis
Table 2 is for calculating the Comparative result of the average power off time of single time point pole line single line user with CEES software and context of methods.Calculated by result of calculation, the arithmetic mean of CEES method is 38.5 minutes, and context of methods is 38.6 minutes, and the difference of two kinds of methods is 0.1 minute.The root mean square average of CEES method is 53.0, and context of methods is the difference of 53.7, two kinds of methods is 0.7.The mean absolute error of two kinds of methods is 1.1 minutes, and average relative error is only 2.84%.Present similar distribution character on average the have a power failure comparative analysis of scarce delivery of user's annual frequency of power cut, user, average relative error is within 3%.
Average power off time contrast (minute) of table 2 single time point pole line single line user
Table 3 is for calculating the Comparative result of the average power off time of single time point cable single line user with CEES software and context of methods.Calculated by result of calculation, the arithmetic mean of CEES method is 30.4 minutes, and context of methods is 30.0 minutes, and the difference of two kinds of methods is 0.4 minute.The root mean square average of CEES method is 43.4, and context of methods is the difference of 42.7, two kinds of methods is 0.7.The mean absolute error of two kinds of methods is 1.0 minutes, and average relative error is 3.21%.Present similar distribution character on average the have a power failure comparative analysis of scarce delivery of user's annual frequency of power cut, user, average relative error is within 4%.
The average power off time Comparative result (minute) of table 3 single time point cable single line user
Consider the result of calculation of pole line and cable, the arithmetic mean of CEES method is 33.9 clocks, and context of methods is 33.6 minutes, and the difference of two kinds of methods is 0.3 minute.The root mean square average of CEES method is 44.7, and context of methods is 47.7 minutes, and the difference of two kinds of methods is 0.The mean absolute error of two kinds of methods is 1.0 minutes, and average relative error is 3.03%.
2) area reliability error analysis
Table 4 is for calculating the Comparative result of the average power off time of all kinds of representative region users with CEES software and context of methods.Calculated by result of calculation, the arithmetic mean of CEES method is 48.5 minutes, and context of methods is 48.3 minutes, and the difference of two kinds of methods is 0.2 minute.The root mean square average of CEES method is 55.5, and context of methods is the difference of 53.4, two kinds of methods is 0.1.Meanwhile, each region calculates relative error maximal value and is also only 8.9%, and most of error range is all below 4%.Present similar distribution character on average the have a power failure comparative analysis of scarce delivery of user's annual frequency of power cut, user, average relative error is about 4%.
The average power off time Comparative result (minute) of all kinds of representative region of table 4 user
| Power supply zone | CEES | Context of methods | Absolute error | Relative error |
| Dong Tang | 67.3 | 65.1 | 2.2 | 3.3％ |
| Sweet osmanthus garden | 56.8 | 60.5 | 3.7 | 6.5％ |
| Trees ridge | 5.8 | 6.1 | 0.3 | 5.2％ |
| Yu Jia gulf | 7.9 | 7.2 | 0.7 | 8.9％ |
| Environmental protection | 19.4 | 18.8 | 0.6 | 3.1％ |
| Huo Chang level ground | 69.9 | 67.3 | 2.6 | 3.7％ |
| Vast stretch of wooded country | 69.9 | 67.8 | 2.1 | 3.0％ |
| She Tianqiao | 69.9 | 70.9 | 1.0 | 1.4％ |
| Prolong agriculture | 69.9 | 71.3 | 1.4 | 2.0％ |
| Arithmetic mean | 48.5 | 48.3 | 1.6 | 4.1％ |
| Root mean square average | 55.5 | 55.4 | - | - |
(2) technical indicator contrast
Table 5 is for contrasting the computing time calculating all kinds of representative region with CEES software and context of methods.Calculated by result of calculation, arithmetic mean computing time of CEES method is 40.1 seconds, and context of methods is 20.0 seconds, and the difference of two kinds of methods is 20.1 seconds.Context of methods average calculation times comparatively CEES method declines 49.6%.
All kinds of representative region of table 5 contrast computing time (second)
| Power supply zone | CEES | Context of methods | Difference | Time reduction ratio |
| Dong Tang | 51 | 23 | 28.0 | 54.9％ |
| Sweet osmanthus garden | 49 | 22 | 27.0 | 55.1％ |
| Trees ridge | 43 | 23 | 20.0 | 46.5％ |
| Yu Jia gulf | 40 | 20 | 20.0 | 50.0％ |
| Environmental protection | 39 | 19 | 20.0 | 51.3％ |
| Huo Chang level ground | 33 | 17 | 16.0 | 48.5％ |
| Vast stretch of wooded country | 29 | 17 | 12.0 | 41.4％ |
| She Tianqiao | 32 | 16 | 16.0 | 50.0％ |
| Prolong agriculture | 45 | 23 | 22.0 | 48.9％ |
| Arithmetic mean | 40.1 | 20.0 | 20.1 | 49.6％ |
Claims (8)
1. the computing method that affect electric network reliability of power distribution network project yet to be built, comprise the steps:
S1. the basic run book of power distribution network before and after power distribution network project construction yet to be built is collected;
S2. according to the data that step S1 collects, by arbitrary without switch isolation and the element set be interconnected is defined as region unit in all for power distribution network circuits;
S3. all region units are obtained to step S2, according to circuit backbone length, backbone wire diameter, branch's number, branch line length, branch line wire diameter, distribution transforming number of units and attaching capacity parameter in operation of power networks data and operation of power networks personnel experience discreet area block; ,
S4. utilize the parameter that step S3 obtains, calculate the dependability parameter of regional block according to following formula:
In formula
for the average time for repair of breakdowns of backbone,
for backbone average year fault correction time,
for the average time for repair of breakdowns of branch line,
for branch line average year fault correction time,
be the average time for repair of breakdowns of the distribution transforming comprising fuse,
it is the distribution transforming average year fault correction time comprising fuse;
S5. the region unit obtained by step S2 carries out the connection between each region unit, to form simplified network model by connection line;
S6. according to the region unit that step S2 obtains, the Overload Class of each region unit is determined, and according to the following formula calculated load classification factor:
In formula
be the Overload Class factor of the i-th type load,
be the load of the i-th type load, P is the attaching capacity of region unit;
S7. the power load distributing coefficient of regional block is calculated:
In formula
for region unit S
ithe attaching capacity estimated,
for the total volume of circuit, P is the burden with power of circuit,
for the normalized Overload Class factor, calculated by the Overload Class factor of region units all in circuit:
S8. power distribution network typical case day k-factor and typical case's day electricity is collected, the structure polynary load model of circuit head end and the polynary load model of region unit:
The polynary load model of circuit head end is:
P
j＝K·E
P in formula
jfor the payload of any time point j of each region unit, K is typical case's day k-factor, and E is typical case day electricity E;
The polynary load model of region unit is:
In formula
for the payload of any time point j of each region unit,
for the power load distributing coefficient of this region unit, P
jfor the payload of any time point j of each region unit;
S9. the polynary load model that the dependability parameter of region unit, the simplified network model of step S5 acquisition and the step S8 that obtain according to S4 obtain, the Quantitative Reliability completing power distribution network calculates.
2. the computing method that affect electric network reliability of power distribution network according to claim 1 project yet to be built, characterized by further comprising following steps:
S10. following three formulas are utilized to calculate power distribution network project yet to be built to the quantization influence of reliability:
Amount when Δ SAIDI is line outage in formula; Δ SAIFI is line outage number of users; Δ AENS is that line outage lacks delivery.
3. power distribution network according to claim 1 and 2 project yet to be built computing method that electric network reliability is affected, it is characterized in that the basic run book of the power distribution network described in step S1, comprise the network structure of power distribution network, the distribution line length of power distribution network and load current, the average time for repair of breakdowns of distribution line and average year fault correction time, distribution line load type, total attaching capacity of power distribution network, power distribution network typical case day k-factor and typical case's day electricity.
4. power distribution network according to claim 1 and 2 project yet to be built computing method that electric network reliability is affected, it is characterized in that the connection line described in step S5, for classifying according to overhead transmission line and cable line: the interconnected type of overhead transmission line comprises multi-joint network, simply connected network, radial fashion; The interconnected type of cable line comprises dicyclic, monocyclic, twinshot, injection formula form; Circuit that is built on stilts and cable mixed type is turned for the low circuit determination connection line type of ability with trunk wire diameter.
5. the computing method that affect electric network reliability of power distribution network according to claim 1 and 2 project yet to be built, is characterized in that the Overload Class described in step S6 comprises city load and rural area load.
6. the computing method that affect electric network reliability of power distribution network according to claim 5 project yet to be built, is characterized in that described city load comprises industrial class city, resident's class city and commercial city.
7. power distribution network according to claim 5 project yet to be built computing method that electric network reliability is affected, it is characterized in that described rural area load comprises market town, town government location, the combination area of city and country or the II class village group of relying on I class village group of economic and technological development zone, small processing industry or agricultural production comparatively flourishing, and based on the III class village group of rural area basic production with life.
8. the computing method that affect electric network reliability of power distribution network according to claim 1 and 2 project yet to be built, is characterized in that the Quantitative Reliability of the power distribution network described in step S9 calculates, calculating for adopting Failure Mode Effective Analysis method.
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| CN107546737B (en) * | 2016-06-28 | 2022-06-21 | 中国电力科学研究院 | Method for analyzing power distribution network reliability influence factors based on cluster analysis |
| CN106952027A (en) * | 2017-03-11 | 2017-07-14 | 国网浙江省电力公司台州供电公司 | A kind of 10kV distribution network lines plan access capacity computational methods |
| CN108647415A (en) * | 2018-04-28 | 2018-10-12 | 国网湖南省电力有限公司 | The reliability estimation method of electric system for high proportion wind-electricity integration |
| CN109449930A (en) * | 2018-11-22 | 2019-03-08 | 南方电网科学研究院有限责任公司 | Power distribution network reliability assessment and repair time parameter modeling method, equipment and medium |
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