CN103065271A - Power supply reliability and customer satisfaction quantitative relation model establishment method - Google Patents
Power supply reliability and customer satisfaction quantitative relation model establishment method Download PDFInfo
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Abstract
The invention discloses a power supply reliability and customer satisfaction quantitative relation model establishment method. The method includes the steps of firstly establishing four power supply reliability indexes and customer satisfaction quantitative relation models which respectively are a prearranged power failure time model, a prearranged power failure frequency model, a fault power failure time model and a fault power failure frequency model according to customer satisfaction research data, then calculating weight of the four power supply reliability indexes, and finally establishing a power supply reliability and customer overall satisfaction quantitative relation model. The method is simple and accurate, not only can be used for establishing the four power supply reliability indexes and customer satisfaction quantitative relation models which respectively are the prearranged power failure time model, the prearranged power failure frequency model, the fault power failure time model and the fault power failure frequency model, but also can be used for determining a weight coefficient of the importance of the four indexes according to customers. In addition, the method can reflect the quantitative relation between the four power supply reliability indexes and the customer satisfaction, and can reflect the conditions of customer satisfaction change when the power supply reliability indexes are changed.
Description
Technical field
The invention belongs to customer satisfaction and concern quantitative model method for building up technical field, be specifically related to a kind of power supply reliability and customer satisfaction and concern the quantitative model method for building up.
Background technology
The customer satisfaction of electric power, refer to power consumer by to the perceived effect of electricity consumption or electricity consumption service with after its expectation value is compared, formed joyful and disappointed state of feeling, it from user perspective comprehensive evaluation the service quality of electric company, power supply reliability, for aspect information such as electrical stabilities.Along with the propelling of China's electricity market reform, deep variation is occuring in the residing environment of power supply enterprise and status, faces by the environment transition of monopolization to competition.Power supply enterprise's operating environment is by distributing electric power and brownout to change the service type of guiding client electricity consumption into.This shows the quality that power supply quality and power supply are served, directly have influence on the existence of power supply enterprise.And carry out power supply Customer Satisfaction Measurement work, research affects the various factors of customer satisfaction, analyze various factors to the concrete influence degree of customer satisfaction, can help power supply enterprise to find the problem that exists in power supply quality and the power supply service and affect customer satisfaction and then affect the various factors of power supply quality, thereby in time formulate targetedly innovative approach, further improve power supply quality, thus, Customer Satisfaction Measurement all is of great significance power supply enterprise self, user and society.
Power customer satisfaction is subjected to a plurality of factor affecting, and the influence degree of different influence factors is also different.At present, the research of power customer satisfaction is mainly concentrated on the qualitative analysis of influence factor both at home and abroad, comprise customer satisfaction exponential model construction method, customer satisfaction analysis of Influential Factors.
The system architecture of a kind of uniqueness that the customer satisfaction exponential model is comprised of a plurality of satisfaction base values, model comprises the satisfaction base values to the relation of customer satisfaction.Test and assess the client out to the satisfaction of base values according to customer satisfaction exponential model design investigation questionnaire, its weighted mean is obtained client's total satisfaction.Such as " Customer Satisfaction Index of Chinese Electricity Industry makes up and the positive research " literary composition in the 3rd phase of the 28th volume March in 2006 " Wuhan University of Technology's journal (information and management engineering version) ", disclosed is the thought of using the multilevel hierarchy analytic approach, make up power consumer Satisfaction systems multi-level, many indexs, pay and 19 base values of 5 aspects propositions of Service Management from power supply quality, Standard Service, consulting service, the electricity charge, design accordingly questionnaire evaluation and test customer satisfaction.And for analyzing the satisfaction of client for power supply reliability, it is too coarse that above-mentioned model seems, the satisfaction factor that relates to is too extensive, and belong to qualitative analysis, only can provide the client to the satisfaction of current power supply reliability level, the client can't be characterized to the real needs of power supply reliability, the rule that customer satisfaction changes with the power supply reliability level can not be provided.
Summary of the invention
In calculating for existing satisfaction evaluation and test about the deficiency of power supply reliability, the purpose of this invention is to provide a kind of power supply reliability and customer satisfaction and concern the quantitative model method for building up, this method is more simple accurately, not only set up pre-arrangement power off time, arrange frequency of power cut, fault outage time and four power supply reliability indexs of fault outage number of times and customer satisfaction relation in advance, can also determine weight coefficient to the attention degree of above-mentioned four indexs from the client; The quantitative relationship that can reflect four power supply reliability indexs and customer satisfaction; The situation of change that can reflect customer satisfaction when the power supply reliability index changes.
The present invention realizes that the technical solution of above-mentioned purpose is as follows:
A kind of power supply reliability and customer satisfaction concern the quantitative model method for building up, according to customer satisfaction investigation data, set up respectively first and arrange power off time in advance, arrange frequency of power cut, fault outage time and four power supply reliability indexs of fault outage number of times and customer satisfaction quantitative relationship model in advance, then calculate the weight of four power supply reliability indexs, set up at last the quantitative relationship model of power supply reliability and client's total satisfaction.
1) user arranges average power off time and customer satisfaction quantitative relationship model to set up as follows in advance:
1.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 11The pre-power off time mean value that arranges of % and expectation
T 11, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 12The pre-power off time mean value that arranges of % and expectation
T 12, select client's number of " generally " to account for total number of users ratio of investigating
a 13The pre-power off time mean value that arranges of % and expectation
T 13, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 14The pre-power off time mean value that arranges of % and expectation
T 14And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 15The pre-power off time mean value that arranges of % and expectation
T 15
1.2) incoming feeder arrange in advance the annual power off time and the ordering
The 1.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average power off time, and arranges by ascending order;
1.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 1.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 1%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 1%=
?a 11%+
?a 12%+
?a 13%
1.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average power off time
The 1.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average power off time ascending sequence of feeder line
n*
b 1The user of % position is pre-to arrange average power off time as the average power off time of pre-arrangement user that reaches the satisfaction passing score
d
1.5) the average power off time of pre-arrangement user corresponding to setting full marks satisfaction mark
The 1.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average power off time of user is set as 0;
1.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 1.5th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement before the rank
n*
a 11The all values of % calculates its mean value
A 11, then be calculated as follows very satisfied corresponding satisfaction mark
S 11
1.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 1.6th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 11% arrives
n* (
a 11+
a 12) all values of %, calculate its mean value
A 12, then be calculated as follows very satisfied corresponding satisfaction mark
S 12
1.8) calculate general corresponding satisfaction mark in the satisfaction
The 1.7th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 12% arrives
n* (
a 12+
a 13) all values of %, calculate its mean value
A 13, then be calculated as follows very satisfied corresponding satisfaction mark
S 13
1.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 1.8th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 13% arrives
n* (
a 13+
a 14) all values of %, calculate its mean value
A 14, then be calculated as follows very satisfied corresponding satisfaction mark
S 14
1.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 1.9th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 14% arrives
n* (
a 14+
a 15) all values of %, calculate its mean value
A 15, then be calculated as follows very satisfied corresponding satisfaction mark
S 15
1.11) set up pre-average power off time and the customer satisfaction quantitative relationship model of arranging of user
The 1.10th) after the step finishes, according to the 1.6th) step, the 1.7th) step, the 1.8th) step, the 1.9th) step and the 1.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 1={
S 11,
S 12,
S 13,
S 14,
S 15And the pre-power off time sequence that arranges of expectation
T 1=
T 11,
T 12,
T 13,
T 14,
T 15, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 1,
S 1) the pre-average power off time of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
2) user arranges average frequency of power cut and customer satisfaction quantitative relationship model to set up as follows in advance:
2.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 21The pre-frequency of power cut mean value that arranges of % and expectation
T 21, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 22The pre-frequency of power cut mean value that arranges of % and expectation
T 22, select client's number of " generally " to account for total number of users ratio of investigating
a 23The pre-frequency of power cut mean value that arranges of % and expectation
T 23, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 24The pre-frequency of power cut mean value that arranges of % and expectation
T 24And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 25The pre-frequency of power cut mean value that arranges of % and expectation
T 25
2.2) incoming feeder arrange in advance the annual frequency of power cut and the ordering
The 2.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average frequency of power cut, and arranges by ascending order;
2.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 2.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 2%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 2%=
?a 21%+
?a 22%+
?a 23%
2.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average frequency of power cut
The 2.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average frequency of power cut ascending sequence of feeder line
n*
b 2The user of % position is pre-to arrange average frequency of power cut as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
2.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 2.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
2.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 2.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement before the rank
n*
a 21The all values of % calculates its mean value
A 21, then be calculated as follows very satisfied corresponding satisfaction mark
S 21
2.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 2.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 21% arrives
n* (
a 21+
a 22) all values of %, calculate its mean value
A 22, then be calculated as follows very satisfied corresponding satisfaction mark
S 22
2.8) calculate general corresponding satisfaction mark in the satisfaction
The 2.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 22% arrives
n* (
a 22+
a 23) all values of %, calculate its mean value
A 23, then be calculated as follows very satisfied corresponding satisfaction mark
S 23
2.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 2.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 23% arrives
n* (
a 23+
a 24) all values of %, calculate its mean value
A 24, then be calculated as follows very satisfied corresponding satisfaction mark
S 24
2.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 2.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 24% arrives
n* (
a 24+
a 25) all values of %, calculate its mean value
A 25, then be calculated as follows very satisfied corresponding satisfaction mark
S 25
2.11) set up pre-average frequency of power cut and the customer satisfaction quantitative relationship model of arranging of user
The 2.10th) after the step finishes, according to the 2.6th) step, the 2.7th) step, the 2.8th) step, the 2.9th) step and the 2.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 2={
S 21,
S 22,
S 23,
S 24,
S 25And the pre-frequency of power cut sequence that arranges of expectation
T 2=
T 21,
T 22,
T 23,
T 24,
T 25, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 2,
S 2) the pre-average frequency of power cut of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
3) the average power off time of user malfunction and customer satisfaction quantitative relationship model are set up as follows:
3.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 31% and expectation fault outage time average
T 31, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 32% and expectation fault outage time average
T 32, select client's number of " generally " to account for total number of users ratio of investigating
a 33% and expectation fault outage time average
T 33, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 34% and expectation fault outage time average
T 34And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 35% and expectation fault outage time average
T 35
3.2) incoming feeder fault annual power off time and ordering
The 3.1st) step finish after, the input power supply administration all
nThe average power off time of the user malfunction of bar feeder line, and arrange by ascending order;
3.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 3.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 3%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 3%=
?a 31%+
?a 32%+
?a 33%
3.4) the average power off time of user malfunction corresponding to calculating qualifying satisfaction mark
The 3.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average power off time ascending sequence of feeder fault
n*
b 3The average power off time of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
3.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 3.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
3.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 3.5th) after the step finishes, choose first in the average power off time ascending sequence of fault before the rank
n*
a 31The all values of % calculates its mean value
A 31, then be calculated as follows very satisfied corresponding satisfaction mark
S 31
3.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 3.6th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 31% arrives
n* (
a 31+
a 32) all values of %, calculate its mean value
A 32, then be calculated as follows very satisfied corresponding satisfaction mark
S 32
3.8) calculate general corresponding satisfaction mark in the satisfaction
The 3.7th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 32% arrives
n* (
a 32+
a 33) all values of %, calculate its mean value
A 33, then be calculated as follows very satisfied corresponding satisfaction mark
S 33
3.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 3.8th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 33% arrives
n* (
a 33+
a 34) all values of %, calculate its mean value
A 34, then be calculated as follows very satisfied corresponding satisfaction mark
S 34
3.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 3.9th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 34% arrives
n* (
a 34+
a 35) all values of %, calculate its mean value
A 35, then be calculated as follows very satisfied corresponding satisfaction mark
S 35
3.11) set up the average power off time of user malfunction and customer satisfaction quantitative relationship model
The 3.10th) after the step finishes, according to the 3.6th) step, the 3.7th) step, the 3.8th) step, the 3.9th) step and the 3.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 3={
S 31,
S 32,
S 33,
S 34,
S 35And expectation fault outage time series
T 3=
T 31,
T 32,
T 33,
T 34,
T 35, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 3,
S 3) the average power off time of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression;
4) the corresponding satisfaction mark of each satisfaction of the average frequency of power cut of fault calculates as follows:
4.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 41% and expectation fault outage number of times mean value
T 41, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 42% and expectation fault outage number of times mean value
T 42, select client's number of " generally " to account for total number of users ratio of investigating
a 43% and expectation fault outage number of times mean value
T 43, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 44% and expectation fault outage number of times mean value
T 44And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 45% and expectation fault outage number of times mean value
T 45
4.2) incoming feeder fault annual frequency of power cut and ordering
The 4.1st) step finish after, the input power supply administration all
nThe average frequency of power cut of the user malfunction of bar feeder line, and arrange by ascending order;
4.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 4.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 4%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 4%=
?a 41%+
?a 42%+
?a 43%
4.4) the average frequency of power cut of user malfunction corresponding to calculating qualifying satisfaction mark
The 4.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average frequency of power cut ascending sequence of feeder fault
n*
b 4The average frequency of power cut of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
4.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 4.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
4.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 4.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault before the rank
n*
a 41The all values of % calculates its mean value
A 41, then be calculated as follows very satisfied corresponding satisfaction mark
S 41
4.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 4.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 41% arrives
n* (
a 41+
a 42) all values of %, calculate its mean value
A 42, then be calculated as follows very satisfied corresponding satisfaction mark
S 42
4.8) calculate general corresponding satisfaction mark in the satisfaction
The 4.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 42% arrives
n* (
a 42+
a 43) all values of %, calculate its mean value
A 43, then be calculated as follows very satisfied corresponding satisfaction mark
S 43
4.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 4.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 43% arrives
n* (
a 43+
a 44) all values of %, calculate its mean value
A 44, then be calculated as follows very satisfied corresponding satisfaction mark
S 44
4.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 4.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 44% arrives
n* (
a 44+
a 45) all values of %, calculate its mean value
A 45, then be calculated as follows very satisfied corresponding satisfaction mark
S 45
4.11) set up the average frequency of power cut of user malfunction and customer satisfaction quantitative relationship model
The 4.10th) after the step finishes, according to the 4.6th) step, the 4.7th) step, the 4.8th) step, the 4.9th) step and the 4.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 4={
S 41,
S 42,
S 43,
S 44,
S 45And expectation fault outage time Number Sequence
T 3=
T 41,
T 42,
T 43,
T 44,
T 45, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 4,
S 4) the average frequency of power cut of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression;
5) weighing computation method of four power supply reliability indexs is:
5.1) input Satisfaction Research data
The client that input is added up in the Satisfaction Research is to pre-arrangement power off time, arrange the importance ranking data of frequency of power cut, fault outage time, four indexs of fault outage number of times in advance, comprises that each power supply reliability index is chosen as respectively the ratio that 1,2,3,4 number of times accounts for total investigation client number;
5.2) calculate the weights of importance of each rank
The 5.1st) after the step finishes, adopt analytical hierarchy process to calculate the weight of each ranking in the importance ranking, at first set the scale of each ordering ranking, obtain the importance degree judgment matrix, then obtain weights of importance through normalized;
5.3) calculate each power supply reliability index weights
The 5.2nd) after the step finishes, add up each power supply reliability index and be chosen as respectively 1,2,3,4 number of times and calculate the ratio account for total investigation client number, the weight of each power supply reliability index is calculated as follows
Wherein,
w i Expression the
iThe comprehensive weight of individual power supply reliability index,
r Ij When ordering expression is with the
iIndividual power supply reliability index elects as
jThe client of name accounts for total investigation client's ratio,
Rank the in the expression importance ranking
jCorresponding weight.
5.4) set up as follows power supply reliability and client comprehensive satisfaction quantitative relationship model:
According to the 1st), 2), 3), 4) every minute index of the power supply reliability set up of step and customer satisfaction quantitative relationship expression formula, in conjunction with the 5.3rd) go on foot the indices weight that calculates, set up power supply reliability index and client comprehensive satisfaction quantitative relationship model by following formula;
Wherein
SIBe client comprehensive satisfaction mark,
f i (
x) expression the
iIndividual power supply reliability index and customer satisfaction quantitative relationship expression formula.
After the present invention adopts technique scheme, mainly contain following effect:
1. overcome the deficiency of existing power customer satisfaction evaluation and test model, not only can user's computing client to the satisfaction mark of current reliability level, can also point out customer satisfaction with the Changing Pattern of power supply reliability, being convenient to electric company provides differentiated service to the client accordingly;
2. can consider in the reliability management of power supply to arrange power off time in advance, to arrange the impact of frequency of power cut, fault outage time and four indexs of fault outage number of times in advance, more near power supply administration's reliability management practical operation situation, model accuracy is high;
3. can consider that different clients are to pre-arrangement power off time, arrange frequency of power cut, fault outage time and fault outage number of times four different attention degrees of index in advance, according to the user importance ranking of four power supply reliability indexs is determined index weights, more meet client's actual conditions.
It is simple, easy to utilize that the present invention has an algorithm, sets up the model accuracy height, and the spies such as reflection client actual conditions order.The present invention is widely used in power supply reliability and customer satisfaction concerns quantitative model foundation, is specially adapted to power supply reliability and the customer satisfaction management of power supply administration.
Embodiment
Power supply reliability of the present invention and customer satisfaction concern the quantitative model method for building up, according to customer satisfaction investigation data, set up respectively first and arrange power off time in advance, arrange frequency of power cut, fault outage time and four power supply reliability indexs of fault outage number of times and customer satisfaction quantitative relationship model in advance, then calculate the weight of four power supply reliability indexs, set up at last the quantitative relationship model of power supply reliability and client's total satisfaction.
Wherein: 1) user arranges average power off time and customer satisfaction quantitative relationship model to set up as follows in advance:
1.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 11The pre-power off time mean value that arranges of % and expectation
T 11, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 12The pre-power off time mean value that arranges of % and expectation
T 12, select client's number of " generally " to account for total number of users ratio of investigating
a 13The pre-power off time mean value that arranges of % and expectation
T 13, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 14The pre-power off time mean value that arranges of % and expectation
T 14And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 15The pre-power off time mean value that arranges of % and expectation
T 15
1.2) incoming feeder arrange in advance the annual power off time and the ordering
The 1.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average power off time, and arranges by ascending order;
1.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 1.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 1%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 1%=
?a 11%+
?a 12%+
?a 13%
1.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average power off time
The 1.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average power off time ascending sequence of feeder line
n*
b 1The user of % position is pre-to arrange average power off time as the average power off time of pre-arrangement user that reaches the satisfaction passing score
d
1.5) the average power off time of pre-arrangement user corresponding to setting full marks satisfaction mark
The 1.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average power off time of user is set as 0;
1.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 1.5th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement before the rank
n*
a 11The all values of % calculates its mean value
A 11, then be calculated as follows very satisfied corresponding satisfaction mark
S 11
1.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 1.6th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 11% arrives
n* (
a 11+
a 12) all values of %, calculate its mean value
A 12, then be calculated as follows very satisfied corresponding satisfaction mark
S 12
1.8) calculate general corresponding satisfaction mark in the satisfaction
The 1.7th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 12% arrives
n* (
a 12+
a 13) all values of %, calculate its mean value
A 13, then be calculated as follows very satisfied corresponding satisfaction mark
S 13
1.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 1.8th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 13% arrives
n* (
a 13+
a 14) all values of %, calculate its mean value
A 14, then be calculated as follows very satisfied corresponding satisfaction mark
S 14
1.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 1.9th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 14% arrives
n* (
a 14+
a 15) all values of %, calculate its mean value
A 15, then be calculated as follows very satisfied corresponding satisfaction mark
S 15
1.11) set up pre-average power off time and the customer satisfaction quantitative relationship model of arranging of user
The 1.10th) after the step finishes, according to the 1.6th) step, the 1.7th) step, the 1.8th) step, the 1.9th) step and the 1.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 1={
S 11,
S 12,
S 13,
S 14,
S 15And the pre-power off time sequence that arranges of expectation
T 1=
T 11,
T 12,
T 13,
T 14,
T 15, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 1,
S 1) the pre-average power off time of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
2) user arranges average frequency of power cut and customer satisfaction quantitative relationship model to set up as follows in advance:
2.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 21The pre-frequency of power cut mean value that arranges of % and expectation
T 21, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 22The pre-frequency of power cut mean value that arranges of % and expectation
T 22, select client's number of " generally " to account for total number of users ratio of investigating
a 23The pre-frequency of power cut mean value that arranges of % and expectation
T 23, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 24The pre-frequency of power cut mean value that arranges of % and expectation
T 24And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 25The pre-frequency of power cut mean value that arranges of % and expectation
T 25
2.2) incoming feeder arrange in advance the annual frequency of power cut and the ordering
The 2.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average frequency of power cut, and arranges by ascending order;
2.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 2.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 2%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 2%=
?a 21%+
?a 22%+
?a 23%
2.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average frequency of power cut
The 2.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average frequency of power cut ascending sequence of feeder line
n*
b 2The user of % position is pre-to arrange average frequency of power cut as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
2.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 2.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
2.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 2.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement before the rank
n*
a 21The all values of % calculates its mean value
A 21, then be calculated as follows very satisfied corresponding satisfaction mark
S 21
2.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 2.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 21% arrives
n* (
a 21+
a 22) all values of %, calculate its mean value
A 22, then be calculated as follows very satisfied corresponding satisfaction mark
S 22
2.8) calculate general corresponding satisfaction mark in the satisfaction
The 2.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 22% arrives
n* (
a 22+
a 23) all values of %, calculate its mean value
A 23, then be calculated as follows very satisfied corresponding satisfaction mark
S 23
2.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 2.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 23% arrives
n* (
a 23+
a 24) all values of %, calculate its mean value
A 24, then be calculated as follows very satisfied corresponding satisfaction mark
S 24
2.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 2.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 24% arrives
n* (
a 24+
a 25) all values of %, calculate its mean value
A 25, then be calculated as follows very satisfied corresponding satisfaction mark
S 25
2.11) set up pre-average frequency of power cut and the customer satisfaction quantitative relationship model of arranging of user
The 2.10th) after the step finishes, according to the 2.6th) step, the 2.7th) step, the 2.8th) step, the 2.9th) step and the 2.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 2={
S 21,
S 22,
S 23,
S 24,
S 25And the pre-frequency of power cut sequence that arranges of expectation
T 2=
T 21,
T 22,
T 23,
T 24,
T 25, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 2,
S 2) the pre-average frequency of power cut of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
3) the average power off time of user malfunction and customer satisfaction quantitative relationship model are set up as follows:
3.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 31% and expectation fault outage time average
T 31, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 32% and expectation fault outage time average
T 32, select client's number of " generally " to account for total number of users ratio of investigating
a 33% and expectation fault outage time average
T 33, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 34% and expectation fault outage time average
T 34And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 35% and expectation fault outage time average
T 35
3.2) incoming feeder fault annual power off time and ordering
The 3.1st) step finish after, the input power supply administration all
nThe average power off time of the user malfunction of bar feeder line, and arrange by ascending order;
3.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 3.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 3%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 3%=
?a 31%+
?a 32%+
?a 33%
3.4) the average power off time of user malfunction corresponding to calculating qualifying satisfaction mark
The 3.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average power off time ascending sequence of feeder fault
n*
b 3The average power off time of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
3.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 3.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
3.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 3.5th) after the step finishes, choose first in the average power off time ascending sequence of fault before the rank
n*
a 31The all values of % calculates its mean value
A 31, then be calculated as follows very satisfied corresponding satisfaction mark
S 31
3.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 3.6th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 31% arrives
n* (
a 31+
a 32) all values of %, calculate its mean value
A 32, then be calculated as follows very satisfied corresponding satisfaction mark
S 32
3.8) calculate general corresponding satisfaction mark in the satisfaction
The 3.7th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 32% arrives
n* (
a 32+
a 33) all values of %, calculate its mean value
A 33, then be calculated as follows very satisfied corresponding satisfaction mark
S 33
3.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 3.8th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 33% arrives
n* (
a 33+
a 34) all values of %, calculate its mean value
A 34, then be calculated as follows very satisfied corresponding satisfaction mark
S 34
3.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 3.9th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 34% arrives
n* (
a 34+
a 35) all values of %, calculate its mean value
A 35, then be calculated as follows very satisfied corresponding satisfaction mark
S 35
3.11) set up the average power off time of user malfunction and customer satisfaction quantitative relationship model
The 3.10th) after the step finishes, according to the 3.6th) step, the 3.7th) step, the 3.8th) step, the 3.9th) step and the 3.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 3={
S 31,
S 32,
S 33,
S 34,
S 35And expectation fault outage time series
T 3=
T 31,
T 32,
T 33,
T 34,
T 35, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 3,
S 3) the average power off time of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression;
4) the corresponding satisfaction mark of each satisfaction of the average frequency of power cut of fault calculates as follows:
4.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 41% and expectation fault outage number of times mean value
T 41, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 42% and expectation fault outage number of times mean value
T 42, select client's number of " generally " to account for total number of users ratio of investigating
a 43% and expectation fault outage number of times mean value
T 43, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 44% and expectation fault outage number of times mean value
T 44And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 45% and expectation fault outage number of times mean value
T 45
4.2) incoming feeder fault annual frequency of power cut and ordering
The 4.1st) step finish after, the input power supply administration all
nThe average frequency of power cut of the user malfunction of bar feeder line, and arrange by ascending order;
4.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 4.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 4%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 4%=
?a 41%+
?a 42%+
?a 43%
4.4) the average frequency of power cut of user malfunction corresponding to calculating qualifying satisfaction mark
The 4.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average frequency of power cut ascending sequence of feeder fault
n*
b 4The average frequency of power cut of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
4.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 4.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
4.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 4.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault before the rank
n*
a 41The all values of % calculates its mean value
A 41, then be calculated as follows very satisfied corresponding satisfaction mark
S 41
4.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 4.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 41% arrives
n* (
a 41+
a 42) all values of %, calculate its mean value
A 42, then be calculated as follows very satisfied corresponding satisfaction mark
S 42
4.8) calculate general corresponding satisfaction mark in the satisfaction
The 4.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 42% arrives
n* (
a 42+
a 43) all values of %, calculate its mean value
A 43, then be calculated as follows very satisfied corresponding satisfaction mark
S 43
4.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 4.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 43% arrives
n* (
a 43+
a 44) all values of %, calculate its mean value
A 44, then be calculated as follows very satisfied corresponding satisfaction mark
S 44
4.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 4.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 44% arrives
n* (
a 44+
a 45) all values of %, calculate its mean value
A 45, then be calculated as follows very satisfied corresponding satisfaction mark
S 45
4.11) set up the average frequency of power cut of user malfunction and customer satisfaction quantitative relationship model
The 4.10th) after the step finishes, according to the 4.6th) step, the 4.7th) step, the 4.8th) step, the 4.9th) step and the 4.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 4={
S 41,
S 42,
S 43,
S 44,
S 45And expectation fault outage time Number Sequence
T 3=
T 41,
T 42,
T 43,
T 44,
T 45, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 4,
S 4) the average frequency of power cut of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression;
5) weighing computation method of four power supply reliability indexs is:
5.1) input Satisfaction Research data
The client that input is added up in the Satisfaction Research is to pre-arrangement power off time, arrange the importance ranking data of frequency of power cut, fault outage time, four indexs of fault outage number of times in advance, comprises that each power supply reliability index is chosen as respectively the ratio that 1,2,3,4 number of times accounts for total investigation client number;
5.2) calculate the weights of importance of each rank
The 5.1st) after the step finishes, adopt analytical hierarchy process to calculate the weight of each ranking in the importance ranking, at first set the scale of each ordering ranking, obtain the importance degree judgment matrix, then obtain weights of importance through normalized;
5.3) calculate each power supply reliability index weights
The 5.2nd) after the step finishes, add up each power supply reliability index and be chosen as respectively 1,2,3,4 number of times and calculate the ratio account for total investigation client number, the weight of each power supply reliability index is calculated as follows
Wherein,
w i Expression the
iThe comprehensive weight of individual power supply reliability index,
r Ij When ordering expression is with the
iIndividual power supply reliability index elects as
jThe client of name accounts for total investigation client's ratio,
Rank the in the expression importance ranking
jCorresponding weight.
5.4) set up as follows power supply reliability and client comprehensive satisfaction quantitative relationship model:
According to the 1st), 2), 3), 4) every minute index of the power supply reliability set up of step and customer satisfaction quantitative relationship expression formula, in conjunction with the 5.3rd) go on foot the indices weight that calculates, set up power supply reliability index and client comprehensive satisfaction quantitative relationship model by following formula;
Wherein
SIBe client comprehensive satisfaction mark,
f i (
x) expression the
iIndividual power supply reliability index and customer satisfaction quantitative relationship expression formula.
Embodiment
Somewhere power supply reliability and customer satisfaction concern that the concrete steps of quantitative model method for building up are as follows:
1), the user arranges average power off time and customer satisfaction quantitative relationship model to set up in advance
1.1) the customer satisfaction investigation data of input take power supply reliability as object, the client's number that comprises selection " very satisfied " accounts for the total number of users ratio 23% of investigation, selects client's number of " satisfied " to account for the total number of users ratio 49% of investigation, selects client's number of " generally " to account for the total number of users ratio 26% of investigation, selects client's number of " more dissatisfied " to account for the total number of users ratio 1% of investigation and select client's number of " very dissatisfied " to account for the total number of users ratio 1% of investigation, and the user of the paired correspondence of each satisfaction expects to arrange average power off time mean value as follows in advance:
| Satisfaction | Very satisfied | Satisfied | Generally | More dissatisfied | Very dissatisfied |
| The pre-power off time that arranges is expected | 2.2 | 3.4 | 4.6 | 6.3 | 7.8 |
1.2) incoming feeder annual power off time and ordering
The 1.1st) after the step finished, the user of input power supply administration all 3532 feeder lines is pre-to arrange average power off time, and arranges by ascending order;
1.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 1.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 1%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 1%=23%+49%+26%=?98%
1.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average power off time
The 1.3rd) after the step finishes, set the satisfaction passing score
cBe 50 minutes, get that the pre-user who arranges the 3461st of rank in the average power off time ascending sequence of feeder line is pre-to arrange average power off time as the average power off time of pre-arrangement user that reaches the satisfaction passing score
d, be 21.4 hours;
1.5) the average power off time of pre-arrangement user corresponding to setting full marks satisfaction mark
The 1.4th) after the step finishes, set satisfaction full marks mark
eBe 100 minutes, the corresponding average power off time of user is set as 0;
1.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 1.5th) after the step finishes, choose first all values of rank front 812 in the average power off time ascending sequence of pre-arrangement, calculate its mean value
T 11=3.0 hours, then be calculated as follows very satisfied corresponding satisfaction mark
S 11
1.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 1.6th) after the step finishes, choose first all values of rank the 812nd to 2543 in the average power off time ascending sequence of pre-arrangement, calculate its mean value
T 12=7.0 hours, then be calculated as follows very satisfied corresponding satisfaction mark
S 12
1.8) calculate general corresponding satisfaction mark in the satisfaction
The 1.7th) after the step finishes, choose first all values of rank the 2543rd to 3461 in the average power off time ascending sequence of pre-arrangement, calculate its mean value
T 13=14.1 hours, then be calculated as follows very satisfied corresponding satisfaction mark
S 13
1.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 1.8th) after the step finishes, choose first all values of rank the 3461st to 3497 in the average power off time ascending sequence of pre-arrangement, calculate its mean value
T 14=26.4 hours, then be calculated as follows very satisfied corresponding satisfaction mark
S 14
1.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 1.9th) after the step finishes, choose first all values of rank the 3497th to 3532 in the average power off time ascending sequence of pre-arrangement, calculate its mean value
T 15=30.4 hours, then be calculated as follows very satisfied corresponding satisfaction mark
S 15
1.11) set up pre-average power off time and the customer satisfaction quantitative relationship model of arranging of user
The 1.10th) after the step finishes, according to the 1.6th) step, the 1.7th) step, the 1.8th) step, the 1.9th) step and the 1.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 1={ the pre-power off time sequence that arranges of 93.3,84.3,68.3,40.8,31.9} and expectation
T 1=2.2,3.4,4.6,6.3,7.8}, and call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 1,
S 1) the pre-average power off time of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression.
2), the user arranges average frequency of power cut and customer satisfaction quantitative relationship model to set up in advance
According to the 1st) step in computing method, input five users corresponding to satisfaction degree and expect to arrange in advance the frequency of power cut sequence of average
T 2={ 1.2,2.3,3.4,4.8,6.2} arrange in advance average frequency of power cut with all feeder line users, calculate for the pre-arrangement of user average frequency of power cut index " very satisfied ", " satisfied ", " generally ", " more dissatisfied " and " very dissatisfied " five Satisfaction index Number Sequences corresponding to satisfaction degree difference
S 2={
S 21,
S 22,
S 23,
S 24,
S 25, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 2,
S 2) the pre-average frequency of power cut of arrangement of match user and customer satisfaction quantitative relationship curve, and the calculated curve analytical expression.
3), the average power off time of user malfunction and customer satisfaction quantitative relationship model are set up
According to the 1st) step in computing method, input five users corresponding to satisfaction degree and expect fault outage time average value sequence
T 3={ 0.6,2.4,4.5,6.6,8.7} with the average power off time of all feeder line user malfunctions, calculate for the average power off time index of user malfunction " very satisfied ", " satisfied ", " generally ", " more dissatisfied " and " very dissatisfied " five Satisfaction index Number Sequences corresponding to satisfaction degree difference
S 3={
S 31,
S 32,
S 33,
S 34,
S 35, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 3,
S 3) the average power off time of match user malfunction and customer satisfaction quantitative relationship curve, and the calculated curve analytical expression.
4), the corresponding satisfaction mark of each satisfaction of the average frequency of power cut of fault calculates
According to the 1st) step in computing method, input five user malfunction frequency of power cut sequence of average that the satisfaction degree is corresponding
T 4={ 0.4,1.6,2.6,4,5.2} and the average frequency of power cut of all feeder line user malfunctions, calculate on average have a power failure index " very satisfied ", " satisfied ", " generally ", " more dissatisfied " and " very dissatisfied " five satisfaction degree of user malfunction and distinguish Satisfaction index Number Sequences of correspondence
S 4={
S 41,
S 42,
S 43,
S 44,
S 45, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 4,
S 4) the average power off time of match user malfunction and customer satisfaction quantitative relationship curve, and the calculated curve analytical expression.
5), the power supply reliability index weights calculates
5.1) input Satisfaction Research data
The client that input is added up in the Satisfaction Research is to pre-arrangement power off time, arrange the importance ranking data of frequency of power cut, fault outage time, four indexs of fault outage number of times in advance, comprise that each power supply reliability index is chosen as respectively the ratio that 1,2,3,4 number of times accounts for total investigation client number, as shown in the table.
| Ranking | The pre-power off time that arranges | The pre-frequency of power cut that arranges | The fault outage time | The fault outage number of times |
| 1 | 0.073 | 0.161 | 0.210 | 0.589 |
| 2 | 0.097 | 0.169 | 0.452 | 0.282 |
| 3 | 0.726 | 0.073 | 0.129 | 0.056 |
| 4 | 0.105 | 0.597 | 0.210 | 0.073 |
5.2) calculate the weights of importance of each rank
The 5.1st) after the step finishes, adopt analytical hierarchy process to calculate the weight of each ranking in the importance ranking.
At first set the scale of each ordering ranking
| Ranking | 1 | 2 | 3 | 4 |
| Scale | 8 | 6 | 4 | 2 |
Obtain the importance degree judgment matrix
| Ranking | 1 | 2 | 3 | 4 |
| 1 | 1 | 2 | 4 | 6 |
| 2 | 0.5 | 1 | 2 | 4 |
| 3 | 0.25 | 0.5 | 1 | 2 |
| 5 | 0.166667 | 0.25 | 0.5 | 1 |
Then obtain weights of importance through normalized
| The product of every row | 5 th Roots | Summation | Normalized (weight) |
| 48 | 2.63 | 5.133 | 0.513 |
| 4 | 1.41 | ? | 0.275 |
| 0.25 | 0.71 | ? | 0.138 |
| 0.020833 | 0.38 | ? | 0.074 |
Then the index weights of 1 to 4 of rank is respectively 0.513,0.275,0.138 and 0.074.
5.3) calculate each power supply reliability index weights
The 5.2nd) step finish after, the weight of reliability index is calculated as follows
Wherein,
w i Expression the
iThe comprehensive weight of individual power supply reliability index,
r Ij When ordering expression is with the
iIndividual power supply reliability index elects as
jThe client of name accounts for total investigation client's ratio,
Rank the in the expression importance ranking
jCorresponding weight;
Obtain each index weights such as following table
| ? | The pre-power off time that arranges | The pre-frequency of power cut that arranges | The fault outage time | The fault outage number of times |
| Weight | 0.169 | 0.179 | 0.262 | 0.390 |
5.4) set up power supply reliability and client comprehensive satisfaction quantitative relationship model
According to the 1st), 2), 3), 4) every minute index of the power supply reliability set up of step and customer satisfaction quantitative relationship expression formula, in conjunction with the 5.3rd) go on foot the indices weight that calculates, set up power supply reliability index and client comprehensive satisfaction quantitative relationship model by following formula.
Wherein
SIBe client comprehensive satisfaction mark,
y i (
t) expression the
iIndividual power supply reliability index and customer satisfaction quantitative relationship expression formula.
Experimental result
The present invention is applied to during Dongguan Power Supply Bureau, Guangdong Power Grid Corporation's power supply reliability and customer satisfaction concern that the quantitative relationship model is set up.Extensively carried out power supply reliability and customer satisfaction questionnaire investigation and added up the customer satisfaction related data that investigation obtains before setting up model.
Calculate satisfaction mark corresponding to five satisfactions and arrange power off time in advance, arrange frequency of power cut, fault outage time and four power supply reliability index values of fault outage number of times such as following table in advance
Pre-power off time and the customer satisfaction of arranging concerns that the quantitative model expression formula is as follows:
Pre-frequency of power cut and the customer satisfaction of arranging concerns that the quantitative model expression formula is as follows:
Fault outage time and customer satisfaction concern that the quantitative model expression formula is as follows:
Fault outage number of times and customer satisfaction concern that the quantitative model expression formula is as follows:
Power supply reliability index and client comprehensive satisfaction relational model are:
From the above results as can be known, utilization this method sets up power supply reliability and customer satisfaction concerns that quantitative model is, can in setting up process, be arranged in advance power off time, be arranged frequency of power cut, fault outage time and four reliability management of power supply indexs of fault outage number of times and customer satisfaction quantitative relationship in advance, more be pressed close to engineering reality; Index weights calculates based on client's actual conditions, has more cogency; The method interface is simple, be convenient to the engineering staff and learn practicality, and versatility is better, can effectively understand the customer satisfaction situation of change.
Explanation is at last, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although with reference to preferred embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement technical scheme of the present invention, and not breaking away from aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of the claim scope of the present invention.
Claims (4)
1. a power supply reliability and customer satisfaction concern the quantitative model method for building up, it is characterized in that: according to customer satisfaction investigation data, set up respectively first and arrange power off time in advance, arrange frequency of power cut, fault outage time and four power supply reliability indexs of fault outage number of times and customer satisfaction quantitative relationship model in advance, then calculate the weight of four power supply reliability indexs, set up at last the quantitative relationship model of power supply reliability and client's total satisfaction.
2. power supply reliability according to claim 1 and customer satisfaction concern the quantitative model method for building up, it is characterized in that:
1) user arranges average power off time and customer satisfaction quantitative relationship model to set up as follows in advance:
1.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 11The pre-power off time mean value that arranges of % and expectation
T 11, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 12The pre-power off time mean value that arranges of % and expectation
T 12, select client's number of " generally " to account for total number of users ratio of investigating
a 13The pre-power off time mean value that arranges of % and expectation
T 13, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 14The pre-power off time mean value that arranges of % and expectation
T 14And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 15The pre-power off time mean value that arranges of % and expectation
T 15
1.2) incoming feeder arrange in advance the annual power off time and the ordering
The 1.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average power off time, and arranges by ascending order;
1.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 1.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 1%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 1%=
?a 11%+
?a 12%+
?a 13%
1.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average power off time
The 1.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average power off time ascending sequence of feeder line
n*
b 1The user of % position is pre-to arrange average power off time as the average power off time of pre-arrangement user that reaches the satisfaction passing score
d
1.5) the average power off time of pre-arrangement user corresponding to setting full marks satisfaction mark
The 1.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average power off time of user is set as 0;
1.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 1.5th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement before the rank
n*
a 11The all values of % calculates its mean value
A 11, then be calculated as follows very satisfied corresponding satisfaction mark
S 11
1.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 1.6th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 11% arrives
n* (
a 11+
a 12) all values of %, calculate its mean value
A 12, then be calculated as follows very satisfied corresponding satisfaction mark
S 12
1.8) calculate general corresponding satisfaction mark in the satisfaction
The 1.7th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 12% arrives
n* (
a 12+
a 13) all values of %, calculate its mean value
A 13, then be calculated as follows very satisfied corresponding satisfaction mark
S 13
1.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 1.8th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 13% arrives
n* (
a 13+
a 14) all values of %, calculate its mean value
A 14, then be calculated as follows very satisfied corresponding satisfaction mark
S 14
1.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 1.9th) after the step finishes, choose first in the average power off time ascending sequence of pre-arrangement rank the
n*
a 14% arrives
n* (
a 14+
a 15) all values of %, calculate its mean value
A 15, then be calculated as follows very satisfied corresponding satisfaction mark
S 15
1.11) set up pre-average power off time and the customer satisfaction quantitative relationship model of arranging of user
The 1.10th) after the step finishes, according to the 1.6th) step, the 1.7th) step, the 1.8th) step, the 1.9th) step and the 1.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 1={
S 11,
S 12,
S 13,
S 14,
S 15And the pre-power off time sequence that arranges of expectation
T 1=
T 11,
T 12,
T 13,
T 14,
T 15, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 1,
S 1) the pre-average power off time of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
2) user arranges average frequency of power cut and customer satisfaction quantitative relationship model to set up as follows in advance:
2.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 21The pre-frequency of power cut mean value that arranges of % and expectation
T 21, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 22The pre-frequency of power cut mean value that arranges of % and expectation
T 22, select client's number of " generally " to account for total number of users ratio of investigating
a 23The pre-frequency of power cut mean value that arranges of % and expectation
T 23, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 24The pre-frequency of power cut mean value that arranges of % and expectation
T 24And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 25The pre-frequency of power cut mean value that arranges of % and expectation
T 25
2.2) incoming feeder arrange in advance the annual frequency of power cut and the ordering
The 2.1st) step finish after, the input power supply administration all
nThe user of bar feeder line is pre-to arrange average frequency of power cut, and arranges by ascending order;
2.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 2.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 2%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 2%=
?a 21%+
?a 22%+
?a 23%
2.4) calculate that user corresponding to qualifying satisfaction mark is pre-to arrange average frequency of power cut
The 2.3rd) after the step finishes, set the satisfaction passing score
c, get the pre-rank that arranges in the average frequency of power cut ascending sequence of feeder line
n*
b 2The user of % position is pre-to arrange average frequency of power cut as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
2.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 2.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
2.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 2.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement before the rank
n*
a 21The all values of % calculates its mean value
A 21, then be calculated as follows very satisfied corresponding satisfaction mark
S 21
2.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 2.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 21% arrives
n* (
a 21+
a 22) all values of %, calculate its mean value
A 22, then be calculated as follows very satisfied corresponding satisfaction mark
S 22
2.8) calculate general corresponding satisfaction mark in the satisfaction
The 2.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 22% arrives
n* (
a 22+
a 23) all values of %, calculate its mean value
A 23, then be calculated as follows very satisfied corresponding satisfaction mark
S 23
2.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 2.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 23% arrives
n* (
a 23+
a 24) all values of %, calculate its mean value
A 24, then be calculated as follows very satisfied corresponding satisfaction mark
S 24
2.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 2.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of pre-arrangement rank the
n*
a 24% arrives
n* (
a 24+
a 25) all values of %, calculate its mean value
A 25, then be calculated as follows very satisfied corresponding satisfaction mark
S 25
2.11) set up pre-average frequency of power cut and the customer satisfaction quantitative relationship model of arranging of user
The 2.10th) after the step finishes, according to the 2.6th) step, the 2.7th) step, the 2.8th) step, the 2.9th) step and the 2.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 2={
S 21,
S 22,
S 23,
S 24,
S 25And the pre-frequency of power cut sequence that arranges of expectation
T 2=
T 21,
T 22,
T 23,
T 24,
T 25, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 2,
S 2) the pre-average frequency of power cut of arrangement of match user and satisfaction mark relation curve, and the calculated curve analytical expression;
3) the average power off time of user malfunction and customer satisfaction quantitative relationship model are set up as follows:
3.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 31% and expectation fault outage time average
T 31, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 32% and expectation fault outage time average
T 32, select client's number of " generally " to account for total number of users ratio of investigating
a 33% and expectation fault outage time average
T 33, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 34% and expectation fault outage time average
T 34And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 35% and expectation fault outage time average
T 35
3.2) incoming feeder fault annual power off time and ordering
The 3.1st) step finish after, the input power supply administration all
nThe average power off time of the user malfunction of bar feeder line, and arrange by ascending order;
3.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 3.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 3%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 3%=
?a 31%+
?a 32%+
?a 33%
3.4) the average power off time of user malfunction corresponding to calculating qualifying satisfaction mark
The 3.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average power off time ascending sequence of feeder fault
n*
b 3The average power off time of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
3.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 3.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
3.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 3.5th) after the step finishes, choose first in the average power off time ascending sequence of fault before the rank
n*
a 31The all values of % calculates its mean value
A 31, then be calculated as follows very satisfied corresponding satisfaction mark
S 31
3.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 3.6th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 31% arrives
n* (
a 31+
a 32) all values of %, calculate its mean value
A 32, then be calculated as follows very satisfied corresponding satisfaction mark
S 32
3.8) calculate general corresponding satisfaction mark in the satisfaction
The 3.7th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 32% arrives
n* (
a 32+
a 33) all values of %, calculate its mean value
A 33, then be calculated as follows very satisfied corresponding satisfaction mark
S 33
3.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 3.8th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 33% arrives
n* (
a 33+
a 34) all values of %, calculate its mean value
A 34, then be calculated as follows very satisfied corresponding satisfaction mark
S 34
3.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 3.9th) after the step finishes, choose first in the average power off time ascending sequence of fault rank the
n*
a 34% arrives
n* (
a 34+
a 35) all values of %, calculate its mean value
A 35, then be calculated as follows very satisfied corresponding satisfaction mark
S 35
3.11) set up the average power off time of user malfunction and customer satisfaction quantitative relationship model
The 3.10th) after the step finishes, according to the 3.6th) step, the 3.7th) step, the 3.8th) step, the 3.9th) step and the 3.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 3={
S 31,
S 32,
S 33,
S 34,
S 35And expectation fault outage time series
T 3=
T 31,
T 32,
T 33,
T 34,
T 35, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 3,
S 3) the average power off time of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression;
4) the corresponding satisfaction mark of each satisfaction of the average frequency of power cut of fault calculates as follows:
4.1) the customer satisfaction surveyed and statistic data of input take power supply reliability as object, comprising: select client's number of " very satisfied " to account for the total number of users ratio of investigation
a 41% and expectation fault outage number of times mean value
T 41, select client's number of " satisfied " to account for the total number of users ratio of investigation
a 42% and expectation fault outage number of times mean value
T 42, select client's number of " generally " to account for total number of users ratio of investigating
a 43% and expectation fault outage number of times mean value
T 43, select client's number of " more dissatisfied " to account for the total number of users ratio of investigation
a 44% and expectation fault outage number of times mean value
T 44And client's number of selecting " very dissatisfied " accounts for the total number of users ratio of investigation
a 45% and expectation fault outage number of times mean value
T 45
4.2) incoming feeder fault annual frequency of power cut and ordering
The 4.1st) step finish after, the input power supply administration all
nThe average frequency of power cut of the user malfunction of bar feeder line, and arrange by ascending order;
4.3) calculate and think that satisfaction reaches client's ratio of qualifying level
The 4.2nd) after the step finishes, calculate client that investigation selects " very satisfied ", " satisfied " and " generally " and account for total investigation client and count ratio
b 4%, satisfaction reaches client's ratio of qualifying level when namely thinking, is calculated as follows:
b 4%=
?a 41%+
?a 42%+
?a 43%
4.4) the average frequency of power cut of user malfunction corresponding to calculating qualifying satisfaction mark
The 4.3rd) after the step finishes, set the satisfaction passing score
c, get rank in the average frequency of power cut ascending sequence of feeder fault
n*
b 4The average frequency of power cut of the user malfunction of % position is as the average frequency of power cut of pre-arrangement user that reaches the satisfaction passing score
d
4.5) the average frequency of power cut of pre-arrangement user corresponding to setting full marks satisfaction mark
The 4.4th) after the step finishes, set satisfaction full marks mark
e, the corresponding average frequency of power cut of user is set as 0;
4.6) calculate very satisfied corresponding satisfaction mark in the satisfaction
The 4.5th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault before the rank
n*
a 41The all values of % calculates its mean value
A 41, then be calculated as follows very satisfied corresponding satisfaction mark
S 41
4.7) calculate the satisfaction mark of satisfied correspondence in the satisfaction
The 4.6th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 41% arrives
n* (
a 41+
a 42) all values of %, calculate its mean value
A 42, then be calculated as follows very satisfied corresponding satisfaction mark
S 42
4.8) calculate general corresponding satisfaction mark in the satisfaction
The 4.7th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 42% arrives
n* (
a 42+
a 43) all values of %, calculate its mean value
A 43, then be calculated as follows very satisfied corresponding satisfaction mark
S 43
4.9) calculate relatively more dissatisfied corresponding satisfaction mark in the satisfaction
The 4.8th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 43% arrives
n* (
a 43+
a 44) all values of %, calculate its mean value
A 44, then be calculated as follows very satisfied corresponding satisfaction mark
S 44
4.10) calculate very dissatisfied corresponding satisfaction mark in the satisfaction
The 4.9th) after the step finishes, choose first in the average frequency of power cut ascending sequence of fault rank the
n*
a 44% arrives
n* (
a 44+
a 45) all values of %, calculate its mean value
A 45, then be calculated as follows very satisfied corresponding satisfaction mark
S 45
4.11) set up the average frequency of power cut of user malfunction and customer satisfaction quantitative relationship model
The 4.10th) after the step finishes, according to the 4.6th) step, the 4.7th) step, the 4.8th) step, the 4.9th) step and the 4.10th) go on foot Satisfaction index Number Sequence corresponding to five satisfactions calculate
S 4={
S 41,
S 42,
S 43,
S 44,
S 45And expectation fault outage time Number Sequence
T 3=
T 41,
T 42,
T 43,
T 44,
T 45, call three Hermite interpolation fittings of segmentation function PCHIP in the Matlab program (
T 4,
S 4) the average frequency of power cut of match user malfunction and satisfaction mark relation curve, and the calculated curve analytical expression.
3. power supply reliability according to claim 1 and 2 and customer satisfaction concern the quantitative model method for building up, it is characterized in that: 5) weighing computation method of four power supply reliability indexs is:
5.1) input Satisfaction Research data
The client that input is added up in the Satisfaction Research is to pre-arrangement power off time, arrange the importance ranking data of frequency of power cut, fault outage time, four indexs of fault outage number of times in advance, comprises that each power supply reliability index is chosen as respectively the ratio that 1,2,3,4 number of times accounts for total investigation client number;
5.2) calculate the weights of importance of each rank
The 5.1st) after the step finishes, adopt analytical hierarchy process to calculate the weight of each ranking in the importance ranking, at first set the scale of each ordering ranking, obtain the importance degree judgment matrix, then obtain weights of importance through normalized;
5.3) calculate each power supply reliability index weights
The 5.2nd) after the step finishes, add up each power supply reliability index and be chosen as respectively 1,2,3,4 number of times and calculate the ratio account for total investigation client number, the weight of each power supply reliability index is calculated as follows
Wherein,
w i Expression the
iThe comprehensive weight of individual power supply reliability index,
r Ij When ordering expression is with the
iIndividual power supply reliability index elects as
jThe client of name accounts for total investigation client's ratio,
Rank the in the expression importance ranking
jCorresponding weight.
4. power supply reliability according to claim 3 and customer satisfaction concern the quantitative model method for building up, it is characterized in that: 5.4) set up as follows power supply reliability and client comprehensive satisfaction quantitative relationship model:
According to the 1st), 2), 3), 4) every minute index of the power supply reliability set up of step and customer satisfaction quantitative relationship expression formula, in conjunction with the 5.3rd) go on foot the indices weight that calculates, set up power supply reliability index and client comprehensive satisfaction quantitative relationship model by following formula;
Wherein
SIBe client comprehensive satisfaction mark,
f i (
x) expression the
iIndividual power supply reliability index and customer satisfaction quantitative relationship expression formula.
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