A Hybrid Evaluation model for Distribution Network Reliability Based on Matter-element Extension Method

Transcription

1 Advanced Scence and Technology Letters Vol.74 (ASEA 204), pp A Hybrd Evaluaton model for Dstrbuton Network Relablty Based on Matter-element Extenson Method Huru Zhao, Nana L School of Economcs and Management, North Chna Electrc Power Unversty, Bejng 02206, Chna Abstract. The relablty of power supply n the dstrbuton network, related to the use of energy normally and effectvely, plays a sgnfcant role n all walks of lfe, urban and rural lfe, publc facltes as well. Consderng about ths, t s necessary to evaluate the power supply relablty of the dstrbuton network. A comprehensve evaluaton ndex system of dstrbuton network relablty s set up n ths paper. Meanwhle, a relablty comprehensve evaluaton method s proposed based on matter-element extenson model, whch realzed the relablty evaluaton from the perspectve of the system operaton. The effectveness and practcalty of the model s verfed through the case study of a dstrbuton network. Keywords: Relablty; Element extenson model; Comprehensve Evaluaton Method. Introducton As we all know, power system should supply electrcty to customers unnterruptedly, wth a qualty standard whch can be accepted [] The power supply relablty s an ndcator measurng power supply capacty n the power system. The relablty level of power supply not only determnes whether all walks of lfe,urban and rural lfe and publc facltes can use electrcty normally and effectvely, but also s a crucal ndcator whch power regulars draw attenton to[2]. Takng all of the above nto consderaton, t s necessary to establsh a reasonable ndex system and an effectve method to evaluate the power supply relablty n the dstrbuton network. Currently, some comprehensve evaluaton methods have been used to evaluate the power supply relablty, such as the analytc herarchy process, Monte Carlo analyss method, artfcal ntellgence method, statstcal method and so on[3,4]. Consderng the nfluence of relay protecton devce and acton accuracy, Lterature [5] calculated the power supply relablty of a substaton based on the smplfed Markov model. Lterature [6] appled fault tree method to establsh the relablty model of mcro grd under off net mode and calculated the falure rate durng fxed tme based on the Monte Carlo smulaton method. In order to evaluate the power supply relablty of low-voltage users, Lterature [7] extracted some nterrupton nformaton and ISSN: ASTL Copyrght 204 SERSC

2 Advanced Scence and Technology Letters Vol.74 (ASEA 204) calculated the relablty of an area based on probablty and statstcs theory. Lterature [8] used the varable fuzzy evaluaton model to evaluate the relablty of dstrbuton network. However, although these tradtonal methods on the relablty evaluaton for power supply are matured and precse, the evaluaton object s only focusng on equpment n the system. Unfortunately, the researches on the comprehensve evaluatons of power supply relablty from the perspectve of the whole system are few. In an effort to fulfll ths research gap on power supply relablty, a comprehensve evaluaton model based on matter-element extenson model s proposed to realze the evaluaton of the relablty for power dstrbuton network, from the perspectve of the whole system. As an evaluaton method solvng the fuzzy, dversty and ncompatble of objects, matter-element extenson theory can establsh performance evaluaton model from multple ndcators and standards. The grade of a matter-element can be judged by calculatng the correlaton degree between evaluaton results and evaluaton rates. Addtonally, the proposed model not only can reflect the performance of an object, but also t has no requrements on the number of samples. In order to evaluate the power supply relablty of dstrbuton network, a comprehensve evaluaton ndex system s constructed n ths paper, and a formula method s used to determne the ndex weghts, so as to avod subjectve factors nfluencng the results. Meanwhle, an evaluaton model based on matter-element extenson s proposed to evaluate the power supply relablty from a perspectve of system. What s more, when some ndcators exceed ther controlled feld, the correlaton functon cannot be calculated. As a result, to overcome the lmtaton, the classcal doman and matter-element should be normalzed. Fnally, takng a dstrbuton network as an example, an emprcal analyss on the power supply relablty has been performed and verfed the effectveness and practcalty of the model. 2 The evaluaton ndex system of power supply relablty n dstrbuton network In order to realze the comprehensve evaluaton of the power supply relablty n dstrbuton network, t s essental to establsh a ratonal statstcal evaluaton ndex system. In addton, the quanttatve ndcators may lay the foundaton and bass for the comprehensve evaluaton. Accordng to the User Power Supply Relablty Evaluaton Code of Power Supply System, the evaluaton ndcators of power supply relablty should be related to power customers closely. Therefore, the frequency of power outage, tme and range of power outage are the basc elements to reflect relablty. The evaluaton ndex system of power supply relablty n ths paper s as follows: () Relablty on Servce n Total 88 Copyrght 204 SERSC

3 Advanced Scence and Technology Letters Vol.74 (ASEA 204) Relablty on Servce n Total refers to the rato of total hours of effectve power supply and total hours of statstcal perod. It s an ndcator reflectng the relablty of a system provdng electrcty to users. The calculaton formula s as follows: Re lablty on Servce n Total = () - Average Interrupton Hours of Customer 00% Statstcal Perod (2) Average Interrupton Hours of Customer Average Interrupton Hours of Customer refers to the average nterrupton hours of power customers n a statstcal perod, whch s an ndcator reflectng the tme duraton of power outage. The calculaton formula s as follows: () Outage Tme Outage Number Average Interrupton Hours of Customer = Total Number (3) Average Falure Interrupton Tmes of Customer Average Falure Interrupton Tmes of Customer refers to the mean outage frequences of customers n the statstcal perod, whch s an ndcator reflectng the power-cut frequency of a power supply system. The calculaton formula s as follows: Outage Number Average Falure Interrupton Tmes of Customer = Total Number (3) (4) Mean Interrupton Customer Mean Interrupton Customer refers to the average number of customers who are affected by power-falure n the statstcal perod. It s an ndcator used to reflect the sphere of nfluence of power nterrupton of power supply system. The calculaton formula s as follows: () Outage Number Mean Interrupton Customer = Falure Interrupton Tmes (5) Average Repeat Falure Interrupton Tmes of Customer Average Repeat Falure Interrupton Tmes of Customer refers to the rato of repeated outages occur to the users. The calculaton formula s as follows: Repeat Outage Number Average Repeat Falure Interrupton Tmes of Customer = Total Number (5) (6) Energy not Suppled due to Interrupton Energy not Suppled due to Interrupton refers to the electrcty short for users durng a power outage. The calculaton formula s as follows: W = K S T Where W denotes Energy not Suppled due to Interrupton; K represents the rato of loadng capacty coeffcent, whch s updated at the begnnng of each year on the bass of the specfc crcumstances of last year; S refers to the outage () (2) (4) (6) Copyrght 204 SERSC 89

4 Advanced Scence and Technology Letters Vol.74 (ASEA 204) capacty, namely the total loadng capacty of the outage users; T represents nterrupton duraton. 3 Constructon of the model 3. Basc theory of matter-element model Matter-element extenson model s based on the theoretcal framework of matterelement theory and extenson set theory. Through establshng classcal feld, controlled feld, evaluaton level and correlaton functon, the level of an object can be determned by the assocaton degree between the matter-element to be evaluated and evaluaton grade [9,0]. The basc dea of matter-element evaluaton method s as follows: Frst of all, the object s dvded nto j levels whch are determned by database or experts; Secondly, determne the weght of each ndex; Fnally, calculate the correlaton degree between ndex value and each evaluaton grade. Moreover, the larger correlaton degree s, the better matter-element s complance wth ths level. 3.2 Proposed model Matter element s the logc unt of matter-element extenson model, whch descrbes objects through an ordered trple R=(P,C,V). Where, P, C, V represents the name, characters and value of thngs respectvely. The basc steps of the mproved matterelement extenson model are as follows: () Determne the classcal doman, controlled feld and matter-element of the object to be evaluated. Suppose Rj = ( P j,c,v j ) as the classcal doman matter-element: P j, j j c v j a b Pj c c v 2 2 j c2 a2j, b 2j Rj = ( Pj,c,v j ) = = (7) cn v c nj n anj, b nj Where P j represents the evaluaton grade of j th, c,c 2,,c n represent the characterstcs of P j, and v j,v j2,,v jn denote the value ranges of c,c 2,,c n for P j respectvely, whch are callde the classcal felds. Suppose the controlled feld matter-element as R = ( PC,, V ): p p P c v, p ap b P c p v c2 p2 c2 ap2, bp2 Rp = ( PC,, Vp ) = = c n v c pn n apn, b pn (8) 90 Copyrght 204 SERSC

5 Advanced Scence and Technology Letters Vol.74 (ASEA 204) where p denotes all grades of the object, the value ranges of p about c,c 2,,c n are represent by v p,v p2,,v pn, namely the controlled feld of p. Suppose the matter-element to be evaluated as R0 = ( P0, C, V ) : P0 c v c2 v 2 R = 0 ( P0, C, V) = (9) cn v n Where p 0 represents all grades of the object to be evaluated, and v p,v p2,,v pn are actual data of p 0 about c,c 2,,c n. (2) Normalzaton The classcal doman and matter-element evaluaton should be normalzed when an ndex value exceeds ts controlled feld. The correlaton functon cannot be calculated snce the denomnator s zero. Aganst the lmtaton, matter-element and extenson model should be mproved. Therefore, the classcal doman Rj and matter-element evaluaton R 0 should be normalzed [], whch are shown as follows: aj b j Pj c, bp bp a2 j b (0) 2 j c2, R j = ( Pj, C, Vj ) = bp2 b p2 anj bnj cn, bpn b pn P0 c v / bp v 2 2 / b c p2 R0 = c n vn / bpn () (3) Determned ndex weghts The ndex weghts are very mportant to the evaluaton result of power dstrbuton relablty, snce the ndex weghts drectly affect the qualty and feasblty of the comprehensve evaluaton. There are varous weghtng methods, such as Delph method, nterval estmaton method, Analytc Network Process and so on. However, all these methods are easly nfluenced by subjectve factors. Therefore, the ndex weghts of power dstrbuton relablty are determned by formula method, whch s shown as follows: 2( -) -2ln( ) n n + (2) + ( < ) W ' = 2( -) -2ln(2 - ) n - n + ( < n) Where, W ' and = 2,,, mm ( n) denotes the mportance of ndex and ndex orders respectvely. The ndex orders are determned accordng to the mportance of ndexes. The more mportant ndcator s, the smaller the value of s. Copyrght 204 SERSC 9

6 Advanced Scence and Technology Letters Vol.74 (ASEA 204) And then, the ndex weght ' W. (4) Calculate the correlaton degree The correlaton degree functon s shown as follows: W can be obtaned through the normalzaton of N ( p ) = D ( v ) w( X) (3) j 0 j = Where N represents the value of correlaton degree; a j + b j Dj ( v ) = v ( b j a j ) denotes the dstance of matter-element to be 2 2 evaluated related to ts correspondng normalzed classcal feld; weght. (5) Ratng Suppose Nj ( p0) max { Nj( p0) } n w ( X) s the ndex =, the matter-element to be evaluated p0 belongs to the j th level. 4 Case study In ths secton, a power dstrbuton network s used to exemplfy the applcablty of the proposed model. The specfc analyss processes of the evaluaton of power dstrbuton relablty are shown as below: () Determne the classcal doman, controlled feld and matter-element of the power dstrbuton relablty. The classcal doman R j of each ndcator s determned accordng to relatve standards and requrements. The classcal domans of all grades P P 2 P 3 represent hgh relablty, medum relablty, and low relablty respectvely. Pj P P2 P3 C 99.9% 00% 99.85% 99.9% 99.8% 99.5% C (4) Rj = C C C C The controlled feld of each ndex whch s equal to the sum of all classcal feld values s R. p 92 Copyrght 204 SERSC

7 Advanced Scence and Technology Letters Vol.74 (ASEA 204) P c(,) 99.5% 00% c2 (,) c3 04 (5) (,) Rp = c4 (,) 0 23 c5 (,) c6 0 0 (,) The matter-element to be evaluated s R 0, whch s shown as follows: P0 c 99.92% c2 4.3 c3 4.2 (6) R 0 = c4 3 c5 65 c6 3 (2) Normalzaton Snce some ndex values exceed the controlled felds, the classcal doman R j and matter-element evaluaton R p should be normalzed, whch are shown as follows: Pj P' P' 2 P' 3 C 99.9% 00% 99.85% 99.9% 99.85% 99.5% P0 c 99.92% c C (7) c3.05 R j = C , R 0 ' = c C c C c6 0.3 C6 (,)(, )(,) (3) Determned ndex weghts The ndex weghts are calculated by formula method accordng to the equaton (2), and the results are shown n table. Indcator Hgh D ( ) v Table. Index weghts and the value of D j ( v ) Medum D ( ) 2 v Low D ( ) 3 v Index weght c c c c c c (4) Calculate the correlaton degree Frstly, calculate the dstance D ( v ) of the evaluated matter-element related to j new classcal doman, whch s shown n the table. And then, calculate the correlaton degree between R 0 and all grades, just as shown n bellow: Copyrght 204 SERSC 93

8 Advanced Scence and Technology Letters Vol.74 (ASEA 204) 6 N ( p ) = D ( v ') w( X) = = = = 6 N ( p ) = D ( v ') w( X) = N ( p ) = D ( v ') w( X) = (4) The grade of power dstrbuton relablty Accordng the correlaton degree of R 0 related to each grade, the grade of power dstrbuton relablty can be judged. Ownng to N ( p ) = max{ N ( p )} = ,j=,2,3, the relablty n ths power dstrbuton 3 0 j 0 network belongs to low. (8) 5 Concluson () A comprehensve evaluaton model based on matter-element extenson s proposed to evaluate the power supply relablty n power dstrbuton network. In addton, compared wth the evaluaton method amng at equpment, ths paper evaluates the relablty of power supply from the perspectve of power dstrbuton network system. (2) In the process of the relablty evaluaton, some ndex values exceed the controlled felds. To overcome ths lmtaton, the classcal doman and matterelement evaluaton are normalzed n ths paper. Meanwhle, the effectveness and practcalty of the model s verfed through the case study of a dstrbuton network. (3) An emprcal analyss of a dstrbuton network s performed n ths paper, and the evaluaton result shows that the power supply relablty s low. Thereafter, the equpment n ths network should be frequently overhauled and replaced, so as to reduce the probablty of falure. Acknowledgements. Ths study s supported by the Humanty and Socal Scence project of the Mnstry of Educaton of Chna (Project number: YJA79027) and the Natonal Natural Scence Foundaton of Chna (Project number: ). Reference. Popovć D H, Greatbanks J A, Begovć M, et al. Placement of dstrbuted generators and reclosers for dstrbuton network securty and relablty [J]. Internatonal Journal of Electrcal Power & Energy Systems,( 2005), 27(5): QIAN K, Yuan Y, ZHOU C. Study on Impact of Dstrbuted Generaton on Dstrbuton System Relablty [J]. Power System Technology, (2008), : Dng M, Zhang J, LI S. A sequental Monte-Carlo smulaton based relablty evaluaton 94 Copyrght 204 SERSC

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