A PRACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISPATCHING

Transcription

1 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) A RACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISATCHING C. Sharma & S. Bahadoorsgh revetve mateace schedulg ad ecoomc dspatch, have foud promet postos the operato of power systems. A ew heurstc algorthm based o the tabu search has bee proposed as a soluto method to the mateace problem. Ths algorthm seeks to satsfy a objectve fucto that ca ether maxmze or mmze spg reserve capacty of the power system over the etre plag horzo whle satsfyg costrats. Maxmzg the reserve capacty provdes a method of matag ad creasg overall system relablty. Ths paper presets a Cbased Wdows applcato software tool for producto of optmzed mateace schedules, performg ecoomc dspatch, predctg actual dates for log-term mateace schedulg ad queryg the curret status of a geeratg ut from data fles. The ower Geerato Compay of Trdad ad Tobago has a stalled capacty of 1159MW wth 21 geeratg uts. Usg ths compay as the testg groud the software tool was developed ad mplemeted MATLAB 6.5 provdg user-fredly Graphcal User Iterfaces (G.U.I.s). Numercal results have bee obtaed ad the effectveess of ths developed software has bee demostrated. Selected results of the software are preseted ths paper for llustrato purposes. Keywords: revetatve mateace schedulg, ecoomc dspatch, tabu search, heurstc algorthm, software tool 1. Itroducto 1.1 Geeral Backgroud ower geeratg compaes must geerate suffcet electrcal power to cater for the varyg demads of cosumers. Electrcty caot be easly ad cheaply stored, so t must be cotuously geerated based o the customers demad. The geeratg compay has a declared capacty at ay gve stat ad must supply ths cotracted demad from ts resources. These resources clude the geeratg uts, trasformers ad trasmsso les. There are may types of geeratg uts that collectvely costtute the power system. The geeratg ut s a electro-mechacal devce. A attrbute of such equpmet s perodc mateace due to deterorato as a result of prologed usage. Ths mateace s ecessary order to exted the lfe ad mprove the overall avalablty of the equpmet. Hece the maer of schedulg ths mateace s of utmost mportace from ecoomc ad egeerg perspectves. Therefore, the optmum schedule s oe, whch satsfes the may costrats yet maxmzes servce relablty ad mmzes producto cost. The producto of ths optmal schedule has bee a topc of study for power egeers over the last three decades. [1] These egeers are also faced wth the challege of ecoomc dspatch, that s, operatg the power system to supply all demads at mmum producto costs, whlst satsfyg several costrats. 1 Departmet of Electrcal & Computer Egeerg, Faculty of Egeerg, The Uversty of the West Ides, St Auguste, Trdad. Emal: chadrabha.sharma@sta.uw.edu 2 hd Studet, Uversty of Machester, UK, sajay.bahadoorsgh@postgrad.machester.ac.uk 57

2 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) Salet Features of Software Tool Ths paper descrbes the developmet ad fuctoalty of a user-fredly software tool developed for power geeratg compaes. The specfcatos of ths tool are that t must clude a teractve Graphcal User Iterface (GUI) that outputs a optmzed mateace outage schedule, power outputs of ole geeratg uts from ecoomc dspatch ad a searchg method for queryg the curret status of a partcular geeratg ut wth a data fle. The developed system has bee appled to The ower Geerato Compay of Trdad ad Tobago (owerge). Aalyss of the curret method used by the above metoed geeratg compay for schedulg mateace ad ecoomc dspatch wll be compared to the outputs of the developed software. The ultmate goal s to mprove the relablty ad lower the operatg costs. The problem ca be dvded to four subproblems: a) Optmzg of mateace outage schedule over oe (1) year horzo; b) Ecoomc dspatch; c) Fve (5) year schedulg of a sgle geeratg ut; ad d) Excel lk Optmzg of Mateace Outage Over Oe (1) Year Horzo I ths software, there are two major costrats that must be satsfed for outage schedulg. These clude tme costrat ad load lmt requremet. Frstly, the tme costrat smply troduces the requremet that a gve geeratg ut must udergo mateace for a predetermed legth of tme, durg a specfed terval of the tme horzo where ether the start tme or ed tme of the mateace govers whe the mateace must be started. Secodly, the load lmt requremet represets the system load or cotracted fgure for whch the geeratg compay must be able to geerate power to meet at every terval of the horzo, regardless of mateace o geeratg uts. Ths requremet fgure cludes spg reserve capacty. Mateace o geeratg uts meas that these uts wll be able to partally or ot at all cotrbute to meet ths lmt. Hece, the resultat schedule must optmally satsfy both costrats f possble Ecoomc Dspatch I ths software, there are two major costrats that must be satsfed for the ecoomc dspatchg of geeratg uts. The frst costrat s load lmt requremet as explaed the prevous sub-secto. The secod s the heat rate lmt requremet that s a measure of effcecy of the power system ad s the cotracted fgure for whch the geeratg compay must strve ot to exceed or a pealty s curred. Hece, the result must be the effectve order of loadg the geeratg uts at specfc outputs. Ths leads ot to exceed the heat rate lmt requremet yet meet the load lmt requremet Fve (5) Year Schedulg of a Sgle Geeratg Ut All geeratg uts of a power system requre mateace o a perodc bass. Ths software tool must provde a forecast of the mateace schedule over a fve (5) year horzo for a sgle geeratg ut, predctg actual dates for the mateace actvtes for the geeratg ut questo Excel Lk I power systems, there are records of the curret status of each geeratg ut. These records are ecessary to keep track of the durato over whch the ut questo was avalable or uavalable. These records are usually stored a predefed spreadsheet format. Ths software must be able to query these records ad produce sutable search results. owerge s records are stored Excel Spreadsheet fles. Ths sub-problem has bee termed, Excel Lk. 2. Outage Schedulg 2.1 Model Formulato Varables Here are the varables used the model formulato: I = Number of geeratg uts J = Number of plag horzo 58

3 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) (weeks [Max = 52]). Lmt = Demad/Load at perod j. j (Assume Lmt j costat for all j) = Rated output of geeratg ut. R = Reserve capacty of I geeratg uts at j perod j. M = Mateace durato of geeratg ut. X = State Varable f geeratg ut I s j mateace at perod j the X = 1; otherwse X = 0. j j DS = Derated state of geeratg ut durg M. 0 < DS 1 = Output of geeratg ut at perod j. Ths j output s a fucto of the state varable ad the derated state of the geeratg ut over the plag horzo. ST = Earlest absolute start tme for mateace durato M o ut. ET = Absolute ed tme at whch mateace durato M o ut must coclude. S = ossble umber of schedules for geeratg ut durg M. S s determed by the umber of tmes M ca uquely ft durg the mateace wdow ET. ST j A geeratg ut ca udergo mateace such that t s totally (100%) uavalable ad therefore the DS = 1. A geeratg ut caot have DS = 0, ths meas that t s totally avalable ad ths does ot represet behavour uder prevetve mateace. Hece 0 < DS 1 represets ether o output or partal output for geeratg ut durg M. Each ut 1 I, must be mataed for M Costrats Several costrats are detfed as follows: Oce mateace of ut has begu the mateace must cotue for M wthout terrupto. The absolute ed tme for a scheduled mateace must ot be earler tha ts absolute start tme. Mateace durato M o ut I must ft wth the mateace wdow whch s the tme betwee the ST ad ET clusve. The sum of the outputs of the I geeratg uts over the horzo must meet the load demad for the geerated schedule to be vald Objectve Fuctos The objectve fucto ca be ether oe (1) of the followg: [2] 1. Mmze the reserve capacty R j over the plag horzo OR 2. Maxmze the reserve capacty R j over the plag horzo Ftess Fucto The schedule that satsfes the approprate objectve fucto ad the costrats must the be evaluated wth the ftess fucto. Ths ftess fucto determes a dex for each schedule geerated. The magtude of ths dex provdes a smple relatoshp wth the optmal soluto foud. A dex wth the largest magtude correlates to the schedule for maxmzg the reserve capacty. Smlarly, a dex of the smallest magtude correlates to the schedule for mmzg the reserve capacty. 2.2 Schedulg Methodology Employed The method employed was a Redefed Tabu Search because of the smplcty uderstadg ad mplemetg the Tabu Search. The followg are the geeral steps used for ths method: [3] 1. For the I geeratg uts calculate, S ad store tabu lst. 59

4 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) I S = max teratos. 2. Determe stoppg crtera, umber of teratos to perform, where, 1 umber of teratos max teratos. 3. Geerate a radom tral schedule: usg the tabu lst radom tegers geerated to chage the ST for the I geeratg uts 4. Valdate tral schedule agast costrats, f schedule vald, evaluate objectve fucto ad approprate ftess fucto. 5. Store as optmal soluto f ftess fucto regards the tral schedule as optmal. 6. Istead of chagg the ST for oe geeratg ut as a ormal tabu search go to step 3 ad repeat for the umber of teratos. Optmal soluto(s) from the umber of teratos defed are avalable. However actual mplemetato of the Redefed Tabu Search, the optmzato of the code volved some prcples of the Iteger rogrammg Method. Hece, the Redefed Tabu Search has udergoe geetc mutato. For large systems, the radom techque employed ( Redefed Tabu Search) to move wth areas of the etre search space ca result the optmal soluto(s) beg foud, f t exsts a smaller computatoal ru tme. The egatve aspect of ths method s; the same optmal soluto, for a gve problem, ca be ecoutered more tha oce. Ths s due to the radom geerato of schedules. However the probablty of ths occurrece has a verse relatoshp wth the umber of teratos set by the user ad the umber geeratg uts uder aalyss. The maxmum umber of teratos the user ca set s determed by I S. Ths s drectly related to the mateace wdows of these geeratg uts uder aalyss. The greater the umber of teratos the method s allowed to perform the hgher the probablty of fdg better qualty solutos. [4] 3. Ecoomc Dspatch 3.1 Costrats Affectg Ecoomc Dspatch There are may costrats wth the ecoomc dspatch problem. [5] These clude: Mmum ad maxmum power output of each geeratg ut; Heat rate lmt (see subsecto 1.2.2); Load lmt requremet (see subsecto 1.2.1); ad Avalablty of geeratg uts. 3.2 Factors Affectg Cost There are may factors, whch affect the fal cost of geeratg power from a geeratg ut, they clude: Fuel Costs Icremetal Operatoal ad Mateace Costs Fxed Costs of Operato Effcecy of Geeratg Ut I order to take to cosderato losses trasmsso les betwee geeratg uts belogg to dfferet power plats, the system cost fucto becomes a augmeted cost fucto Eq(1) called the lagraga. Cost ($) F COSINC O & M LOAD Eq (1) Where: F = Fuel Iput COSINC = Icremetal fuel cost of the th ut O&M = Icremetal O&M cost of th ut = ower output from th ut LOAD = Total power receved by the loads = Trasmsso losses loss = Lagrage multpler loss 60

5 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) The lagraga equato Eq(1) represets a ucostraed problem whch t s requred to mmse the Cost fucto wth respect to λ ad the geerator outputs. Therefore for mmum cost we requre the dervatve of Eq(1) wth respect to each to be equal to zero, gvg the dspatch codto Eq(2). 0 df dloss. Eq (2) COSINC O & M 1 d d I power systems, a approxmato s usually made to reduce computer smulato costs, power geerato plag. Ths approxmato cossts of represetg the cremetal trasmsso loss term 1 as a costat dloss 1 d pealty factor, L, where L may be the rage of 1.0 L Further approxmato for smulato exercses, results Eq(3) beg approxmated where L =1 ad. O & s eglected to produce. M df COSINC M Cost($) Eq (3) d 4. Software Desg ad Implemetato The software model, whch has bee appled to the creato of ths software tool, was the Waterfall Model wth rototypg. The optos provded to the user (see secto 1.2) were mplemeted as modules. Detaled help screes were desged for all put ad output screes. 5. Software Testg I order to verfy the accuracy of ths software, results were subjected to aalyss wth the Isttute of Electroc ad Electrcal Relablty Test System (IEEE RTS). Ths test system comprses thrty-two (32) geerators. The IEEE RTS has bechmarked system relablty dces, beg the Loss Of Load Expectato (LOLE) ad Loss Of Eergy Expectato (LOEE) dces for the above specfed test system. The L.O.L.E. dex represets the umber of hours per year that the system load shall exceed the avalable geeratg capacty whle the LOEE dex represets the severty of ths defcecy power (usually MW) per year. Ths test system performs aalyss for mateace schedulg of the 32 geeratg uts. Hece ths software ca be appled to ths test system va a geerated schedule. Ths result (schedule) must the be used to compute the relevat relablty dces. Ths computato ca be doe maually or by usg relablty software tools whch have bee prevously calbrated accordg to the IEEE RTS or equvalet. The latter method was selected, usg Mote Carlo Smulato. 5.1 IEEE RTS Test Case Ths test volved geeratg a schedule for the IEEE RTS system where the weekly load demad values were used to heurstcally formulate the mateace wdows for the 32 geeratg uts. The schedule produced was used to compute the respectve LOLE ad LOEE dces usg the Mote Carlo Smulato method. The results are llustrated Table 1. TABLE 1: Comparso of IEEE Results IEEE RTS Developed LOLE Hr/Yr LOEE MWHr/Yr Case Study of owerge Mateace Schedulg owerge has a cotracted oblgato to the Trdad ad Tobago Electrcty Commsso (T&TEC) to supply 719MW capacty ad 100MW spg reserve. Ths study cludes aalyss of the curret methods of schedulg [6] ad ecoomc dspatch performed by owerge ad comparso of the results produced usg THE DEVELOED SOFTWARE. The Excel Lk was successfully appled to owerge sce the format of the Spreadsheet for proper fuctog of that module was adhered to owerge s 2000 Mateace was 61

6 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) used as a test case, where the horzo uder aalyss was the etre year 2000 (.e. 52 weeks). TABLE 2: Comparso of case study results for mateace schedulg 2000 #1 #2 owerge M Cap 948 MW 948 MW MW Max Cap 1118 MW 1118 MW 1098 MW Ecoomc Dspatch A 24-hour hourly aalyss was performed usg owerge s geeratg data (dated 2003/01/31). The results obtaed provded a hourly aalyss of how owerge s geeratg uts should be loaded, gve ther respectve avalabltes ad declared capactes for successful ecoomc dspatch. Table 3 llustrates cumulatvely the hourly results. 6. Further Study ad Upgrades to the Developed Software The followg are proposals to crease the fuctoalty of ths developed software tool: a) Schedulg ca tegrate the use of weekly load values to produce a more flexble mateace schedule. Ths schedule ca the be evaluated by a ftess fucto whch produces LOLE ad LOEE dces. b) The Redefed Tabu Search Algorthm ca be modfed so that vsted areas of the search space are ot revsted, thus creasg the probablty of fdg uque solutos faster. c) The ecoomc dspatch ca be made to accommodate the costrats of rampg the geeratg uts durg startup, shutdow ad termedate stages. d) Addtoal costrats for ecoomc dspatch clude usg te le costrats for mult-area ad tercoected systems ad revsg the objectve fucto to clude evrometal cosderato. The latter ca cotrol ad reduce the emsso of troge ad sulphur oxdes by fosslfuel geeratg uts. e) The ecoomc dspatch ca make practcal recommedatos for the modelg of combed cycle geerato plats. 7. Cocluso Ths paper provded a revew of outage schedulg, examed the ecoomc dspatch prcple based o cremetal cost curves ad descrbed the developmet of a practcal MATLAB software tool. Ths developed software successfully performed mateace schedulg, for a maxmum of thrty-two geeratg uts, seekg to ether maxmze or mmze the spg reserve capacty whst satsfyg the load demad as well as the mateace wdow costrats for each geeratg ut. A very smple, user fredly GUI was developed. It hghlghted the perods durg the specfed horzo whe every geeratg ut uder aalyss was ole ad offle. Accompayg each produced schedule was a aalyss of the total power avalable ad the correspodg spg reserve for every week. Aother fucto successfully mplemeted was the ecoomc dspatch (aga for a maxmum of 32 geeratg uts) over a hourly perod ad a 12-hour perod. The latter perod provded the opto for every geeratg ut avalable to be shutdow ad or started up oce durg ths perod. Here, a hourly report s geerated whch suggests how the avalable geeratg uts should be loaded to acheve mmal cost ad maxmum effcecy (mmum heat rate). The report also hghlghts these mmal cost ad heat rate fgures. The 5- year mateace forecast for each geeratg ut ad the process of queryg the outage records (excel spreadsheets) to determe a geeratg ut s status, were both successfully mplemeted. The developed software was appled to a practcal power system, the ower Geerato Compay of Trdad ad Tobago. All the fuctoaltes of the developed software were 62

7 West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) successfully appled. Curretly at ths compay, o software tool s avalable to assst the mateace schedulg ad ecoomc dspatch operatos. A aalyss usg the developed software of owerge s mateace schedule for the year 2000 llustrated that, ts schedule could have bee optmzed to produce creased mmum ad maxmum total power ole. The aalyss also revealed that a ole capacty greater tha the desred 920 MW could have bee acheved. The results of the ecoomc dspatch for a gve 24-hour perod, revealed that the et heat rate ad producto cost fgures acheved by owerge ca be reduced by 8.32 % ad % respectvely. Hece, order to acheve ths reducto producto cost ad heat rate, the curret strategy used at owerge to load the geeratg uts must be revsted. I cocluso, sce mateace schedulg determes the avalablty of geeratg uts for ecoomc dspatch, a software tool such as ths, whe appled to practcal power systems ca result a mprovemet system relablty ad ecoomc operato. Refereces [1] Bllto, R. ad Alla, Roald N. (1984), Relablty Evaluato of ower Systems, tma Advaced ublshg rogram, Great Brta, p.398. [2] Kght, U.G., (1972), ower Systems Egeerg ad Mathematcs, ergeamo ress, p [3] Marwal, M. ad Shahdehpour, M. (2000), Mateace Schedulg I Restructured ower Systems, Kluwer Academc ublshers, p.14 [4] fleeger, S. (1998), Software Egeerg, retce Hall, p. 35 [5] Stoll G. Harry, (1989), Least-Cost Electrc Utlty lag, Wley Iterscece, p [6] Yamayee, Z. A. (1982), Mateace schedulg: descrpto, lterature survey ad terface wth overall operatos schedulg, IEEE Trasactos o ower Apparatus ad Systems, AS- 101, No.8, pp