integrated reliability evaluation of gentrans and dist systems

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Integrated reliability evaluation of generation,transmission and distribution systemsA.M. Leite da Silva, A.M. Cassula, R. Billinton and L.A.F. Manso

Abstract: A new methodology evaluates the reliability of distribution systems considering theimpact of failures from the gen eration and tra nsmission (G& T) systems is presented. An integra tedadequacy evaluation. including generation, transmission and distribution. is performed to providedetailed infor mation on the interruption s experienced by consum ers. G& T systems are representedby a fictitious equivalent networ k whose parameters are obtained by Mo nte Carlo no nsequentialsimulation. The equivalent G&T network is then connected with the distribution network andanalysed using minimal cut-set theory. Traditio nal distribution indices (e.g. SAIF I, SAIDI, etc.) aswell as the loss-of-load cost indices are disaggregated to measure the contribution of G&T anddistribution systems on the overall system indices. Th e m ethod is applied to a hybrid system createdfrom two standard test systems. The results and their potential applications in the new powersystem com petitive environm ent are discussed.

1 IntroductionDistribution systems [Id]have always received lessattention than generation and transmission (G&T)systemswith regard to reliability modelling and evaluation [7-121.An analysis of custom er failure statistics of the mo st ut[ I ] . however, shows that the distribution system makes thegreatest individual contribution to the unavailability ofsupply to a customer. In the last few years, distributionsystems have begun to receive mo re attention mainly due tothe restructuring and privatisation process of the powersector many countries in the world are undergoing.Therefore reliability worth will have to be accuratelyevaluated and inserted in the electricity tariff for compen-sating customers in case an intemption occurs.

The reliability evaluation of a complete electric powerincluding generation. transmission and distributions (known as hierarchical level 3, or simply HL3) isan important objective in overall power system planningand operation [3]. The usual hierarchical levels are shown inFig. I . Due to the dimension of the H L 3 problem, however,reliability studies are no rmally perform ed assumin g that theG&T system supply points have unlimited capacity and100% reliability.In this work, a new methodology is proposed to evaluatethe impact of H L 2 ailures on the distribution systems. Thisis achieved using nonsequential Monte Carlo simulation.Based on the load curtailment strategy at the distributionlevel, a fictitious network is created whose componentssimulate the H L 2 nterruption s. This procedur e generalises< ' IEE. ZWZ

IE E Proccw1in;p online no. 2WZW81Dol. IO . IWYiip-gld:?W2W8Paper first received 6th Novemhr ?Ow an d in revired form 23id May ?WIA . M . Lriic ds Silva an d A . M . Couua arc with the lnrtiriite of E1emic;ilEnginefing. Federal Univenily - EFEI. A? . BPS 1303. Pinhcinnho. 1wj;llabi.MG, 37,500-903. r-lR. Billinion is uith the Electrical Enginenng Depiinmeni. T h e Univenity ofSaskatchewan.5.~rha1oon.CanadaL.A.F . Manso is with the Elclncal Enginrrfing Department. FedenilIJnivmily. SCo JoCoDel Rei ~ FUNREI. M C. BriiulIE E Proc-Ge,iei: Trumr. Dlirrih.. Cb L 14Y. No 1. Jmr u r ~v uO2

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Fig. 1the concepts proposed in [3] .Both fictitious and distributionnetworks are analysed using the minimal cut-set concepts[13]. In addition to the usual distribution indices for thesystem and load points, the loss-of/oud cost (LOLC) indexor equivalent [2. 4, 9-12] is evaluated and disaggregatedconsidering the hierarchical levels. The proposed methodo-logy can therefore provide economic insight in terms ofresponsibilities for the customer damage costs.2 Distribution system reliabilityA distribution system is frequen tly represented as a ne tworkin which the system components are connected togethereither in series, parallel, meshed or a combination of these.There are different analytical techniques available todetermin e the solution and the evaluation of these networks[13]. I f continuity of supply is the major concern, the

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method bascd on minimal cut-set theory is the most useful,since the cut-sets are directly related to the system failuremodes.2.1 Evaluation techniquesThe Markov technique and the frequency aiid durationapproach form sound and precise modelling and evaluationmethods for ii range of reliability application s [13]. For hrgeand complex systems, such as distribution networks,approxim ate equations hav e been developed based on thFsemethods. These approximate equations can be used' inconjunction with minimal cut-sct techniques to give- rapi dand sufficiently accurate results for a wide range of practicaldistributions systems.2.2 Performance indicesI t is essential for electric utilities to track distribution systemreliability levels and define performance indices Ib assesstheir basic function of pro viding a cost-effective and reliablepower supply to all sectors of society. This procedure isknown by past performance or historical reliability assess-ment, a nd it is widely used by utilities. Futu re perlblm auccor predictive reliability assessment is another valuableprocedure which can be used to determine systemreinforcements and to compare expansion alternatives. Tomeasure the past or future performance of the supplyadequacy at the customer load points, indices used are:failure rate i , ailure duration r, unavailability U,energyriolsupplied ENS; and for the system indices SAIFI. SAID1and CAlDI [ I ] .At hierarchical level 2, predictive assessment is the mostcom mon procedu re uscd for system reliability planning . Onthe contrary, at HL3, predictive assessment is not aspopular as historical assessment. Bearing in mind the newcompetitive environment, there is, however, a growinginterest in economic optimisation approaches to distributionplanning and expansion. In the new environment, alldistribution companies will be looking to identify the bestpoints in the network to receive the appropriate invest-ments. Therefore predictive assessment will become animportant tool in the distribution system decision makingprocess.Reliability of any electric service, including distributionactivities, should be bascd o n balancing the costs to a utilityand the value of the benefits received by its customers. Avalue-based reliability planning approach [4]must attemptto locate the minimum-cost solution, where the total costincludes the utility investment cost plus the operating costplus customer interruption costs. Thereforc the LOLC, atboth load point and system levels, will become the primaryindex for value-based reliability planning. Tlus indexdepends basically on the unit interruption cost (UC) o feach consu ming class, usually given in US$ per kWh. TheUC s are obtained through specific economic studies

(consum er surveys). These studies describc different factorswhich may have some impact on the UC , and the durationof. the interruption is considered the most impo rtant one.The accuracy level established to evaluate this duration is animportant element in the quality of the estimates of L OL Cindices.3There are many benefits associated with the ability toperform overall reliability ev aluation_ i.e. H L 3 reliabilityassessmen t. Th e overall indices provid e reliability measur esfrom a customer point of view, and can be used to rankfunctional zone contributions and therefore to optiiniseinvestmeiits [6].The assessment of overall indices is carried out in threemajor steps. First, an algorithm for evaluating the G&Tsystem is used to generate a significant number of samp lesof power interruptions, at the high-voltage bus or buses, towhich the dislrihution system is connected. In this work theH L 2 assessmelit is done by a nonsequential Monte Carlosimulation. In the second step, parameters are extractedfrom the sim ulation process to assist in the def inition of anequivalent network. which depends on the load curtailmentstrategy at the bus or buses involved. Once the fictitiousG& T equivalent network is defined, it is then connected tothe distribution network for the third and final step of theH L 3 analysis.

Impact of G&T failures on distribution system

3.7 Parameters to characterise G&T failuresTo define, from the reliability point of view, the fictitiouscompon ents which belong to the equivalent G& T network.it is necessary to know, their corresponding Failure rates iand their undvailabilitiesU. The methodology to determinesuch components is described as follows, considering adistribution network with N feeden.During the convergence of the H L 2 M onte Carlosimulation, the sequence of events which represent thefailure states associated with the bus connected with thedistribution network are stored. Each failure state ischaracterised by the following parame ters [8,9]: incrementalfrequency,f;,,,,,nd the am oun t of load curtailed due to G & TLCGT.The load curtailments are clustered within powerintervals which correspond to the total amount of oadconnected to each feeder of the distribution netw ork. This isillustrated in Table 1.Where NI is the num ber of the interva l and PI,P 2 .P3 .. .4 ... P,,, re the amounts of power associated with thefeeders R I , R2, R3 ... Rk .. RN. The number of intervalsis also the number of feeders connected to the high-voltagebus. This procedure can be easily extended to c onsider morethan one bus connected to the same distribution network.The probability or unavailability U and the frequencyassociated with each pow er interval (wluch corresponds to

Table 1: Power intetval for fictitious components G&TFeeder NI Power intewa1R1 p, 1 0 < LCGT 5 ,R2 P2 2 P,


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load curtailment or failure events) can be obtained usingeqns. I . Observe that the Failure frequency is approximatelythe pseudofiiilure rate associated with the fictitious com po-ncnt. Therefore the G&T fictitious compo nent s are entirelycharacterized by j. and U

where PA represents probability associated with the powerinterval k. U, s the unavailability of the power interval k ,N , is the total number of failure states belonging to thepower interval k. NT is the total number of simulations. j.,is the failure rate associated with the power interval k.h.sthe frequency of occurrence of the power interval k . rA is theaverage failure duration associated with the power intervalk, an d x;i, /&cl is the summation of the incrementalfrequency of states j belonging to the power interval k . Thepirameter U is usually given in hours per year. i.e.3.2 Representation of load curtailment policiesEach distribution company adopts its own load curtailmentpolicy or strategy. The adopted policy follows a set ofcriteria to reduce the effects caused by interruptions andalso to mininiise the corresponding costs. The loadcurtailment policies can be represented or modelled by theway that the fictitious G&T components are arrangedwithin the distribution system. To illustrate this point,consider a distribution system with four feeders: R I. R2. R3and R4. The power capacity of each feeder and thedisconnection policy are shown in Table 2.Table 2 Load curtailment policyFeeder capacity Power intewa l FeederIMWI disconnectedR 1 20 O


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condition and are disaggregated into G& T and distributioncontributions.From the results in Table 5 one can clearly identify theG&T curtailment policy. Note that the failure rate forfeeder RI (from where LP I is supplied) has a higher value(Le. 20.473 failures per year) than feeder R2 (Le. 10.863failures per year), which, in turn. has a higher value thanfeeder R3 and so on , according to the adopted loadcurtailment strategy. The contribution of the failuresoriginating from the G&T system is much larger thanthose originating from the distribution system itself. Notethat the IEE E-R TS is not very reliable at the peak loadcondition mainly due to generation.Table 6 presents the results obtained for the systemindices SAIFI (interruption per customer year), SAID1(hours per customer year), CA IDl (hours per customer perinterruption), ENS (MWh per year) and LOLC (US$ peryear). All the H L 3 indices are disaggregated into G&T anddistribution contributions. For instance, the SAIFI for theoverall system (i.e. HL3) is equal to 11.4377 interruptionsper customer, where 11.1845 interruptions come from theG& T system a nd only 0.2532 interruptions come from thedistribution system.4

I equivalentI G &Ts ys t emI(24) (34)

Another conclusion from the results shown in Tables 5and 6 is that both systems, G& T and distribution, behave astwo independent components connected in series. Thereason is due to the assumption that all equipment in thedistribution system (Le. lines, transformers, etc.) are able tosupport any loading situation. Due to this restriction it isnot possible to measure the simultaneous effect ofgeneration, transmission and distribution. This restriction,however, is due to the continuity criterion which is used inmost distribution reliability assessment metho dologies.4.3 Effects of LC distribution policyTo measure the effects of the load curtailment policy at th edistribution level, Table 7 provides a new strategy in wh ichfeeder R3 is the first one to be disconnected, followed byR4, RI and finally R2. The load curtailment policy at t heG&T was kept the same, and therefore there was no needfor a new H L 2 simulation. The only change is the way thepower intervals are handled to define the new param eters o fthe fictitious G&T components. The structure of theequivalent G& T system is the same as shown in Fig. 4.Table 8 presents the system indices obtained with the newload curtailment policy. Comparing the results fromTables 6 and 8 it can be seen that the indices related withthe distribution system have not changed. This could beexpected because the inherent reliability of the d istributionnetwork depends only on the failure characteristics of itsown components. On the other hand, the contribution ofthe G&T system indices changes, and so do the overallH L 3 indices. In fact, the system with this new policybecomes more costly from the interruption point of view.In the case where the LC distribution policy is such that itremoves one feeder at a time as presented in Tables 4an d 7(Le. RI + R 1 + R2-.RI + R2+ R3-RI + R 2 + R 3 + R 4,o r R3+ R3 + R 4 + R 3 + R 4 + R1 + R 3 + R4+ R 1+ R2etc.), the equivalent network is simply characterised by thefailure of the fictitious compo nents, as show n in Figs. 2 an d4. It is possible. however, that the LC policy involves thecombination of feeders (e.g . R l+ R 2 - .R l+ W + R 3 -+

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Table 3 Parame ters for G&T c omponents, peak load Table 7: Feeder peak loa d capacity, new LC policyParameters Power interval

1 2 3 4i. (per year) 9.609967 2.939667 3.159663 4.763195r lh) 35.646540 39.366430 46.256100 28.360880U lh Der vr ) 342.562100 115.724200 146.153700 135.08840

Table 4 Feeder peak load capacity, LC policyFeeder IMWI LC due to G& T DisconnectedfeederR1 5.934 o < LCG


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the new competitive scenario as it can provide an overall distibution system data an d mul t s ' , IEEE Trum Power Sysr.,1991. 6. (Z), pp . 813-8?0BILLINTON. R.. and J O N N A V I T H U L A , S. : 'A test system forteaching overall power system reliability assessment', IEEE Trirn~Powr Sy.rr. 1996, I I . (4). pp. 1670-1676LElTE DA SILVA. A.M.. MELO, A.C.G., an d C U N H A . S .H .F . :'Frequency and duration method fo r rcliability e v ~ l ~ a t i o nf large-sca le h yd ro the mi genera ting s ~ s t c m i ' . E E Pruc. C,Gener. Trun.

view Of the system in terms Of both past and futureperformance. The present work makes a contribution tothis H L 3 reliability area by providing indices, includingmethodology is based on a combination of nonsequential

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to overall system perfomance, T he 7

hierarchica l levels. The pro posed me tho do lo^ can providetechnical and economic bases for discussing the standardsand rcsponsibilities associated with customer damage.fl"'" ' ( i r '. '6 References JP

Power Syrt., 1993, R . (3).'pp. lllE-Il2

integrated reliability evaluation of gentrans and dist systems

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