A Comparison of Methodologies Incorporating Uncertainties into Power Plant Investment Evaluations
|
|
- Rudolf Casey
- 6 years ago
- Views:
Transcription
1 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 A Comparon of Mehodologe Incorporang Uncerane no Power Plan Invemen Evaluaon Nnghong SUN # Derk Jan SWIDER Alfred VOSS Inue of Energy Economc and he Raonal Ue of Energy Unvery of Sugar Hebruehlrae 49a Sugar Germany # Dpl.-W.-Ing. Nnghong Sun. Tel.: ; Fax: E-Mal: nnghong.un@er.un-ugar.de Abrac Th paper offer a comparon of echnque propoed o deal wh uncerane exng n power yem expanon plannng. Dvere approache developed or appled over he pa wo o hree decade are urveyed and clafed no he convenonal and new one accordng o her predomnan applcaon n he regulaed and lberalzed me. Baed on he curren leraure concluon on he poenal of developng new mehodologe able o mee he requremen of power plan nvemen evaluaon n he comng year are drawn. 1 Inroducon The Uned Kngdom and a a poneer n Europe for beng he fr counry o have underaken he rerucurng of elecrcy marke. Snce hen lberalzaon ha been gradually mplemened n he elecrcy ecor of oher counre. The man objecve purued by he lberalzaon of elecrcy marke o reduce co by ncreang compeon n he wholeale and real ecor where radonal monopole had alway prevaled. Under h new framework power plan nveor have o ake varou addonal concern no accoun n her decon-makng. The mo gnfcan of hee concern he expoure o dvere uncerane boh n relaon o he marke fundamenal and o he raegy of her compeor. Therefore he developmen of mehodologe capable of ncorporang and effecvely handlng relevan uncerane no nvemen evaluaon a new challenge one ha reearcher are akng up. In he nex econ we wll brefly nroduce he mo mporan change on he elecrcy marke brough along by lberalzaon and he major uncerane ha need o be aken no conderaon when plannng new power generaon projec. Change hrough marke lberalzaon We wll decrbe he mo gnfcan change n he elecrcy ndury nce he lberalzaon focung on hree apec: he ownerhp and hu nveor of power plan benchmark for evaluang power plan nvemen projec and regulaory polce degned o guaranee he adequae elecrcy upply. In he pre-lberalzaon me generang ule were moly ae owned and operaed. Wh lberalzaon he elecrcy ecor wa enrely or parly opened o prvae nveor. Pror o lberalzaon he goal n power plan nvemen and operaon wa co mnmzaon. Wh he peneraon of prvae nveor no he marke and ncreaed compeon ha goal wched o prof maxmzaon. In regulaed marke he man concern whle plannng for new capacy wa o offer a uffcen upply. Generaor were no under preure nce all 1
2 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 he co relang o he power upply even hoe co reulng from her adveraral decon could evenually be ranferred o he conumer. Bu wh he marke lberalzaon elecrcy prce are no longer fxed a a prevouly negoaed arff bu e by he marke equlbrum. In oher word generaor have o ake a lo for her own accoun. Elecrcy ha alway been a commody under much more uncerane han oher common one. The grea capal neny and long lead me of mo power plan make even more dffcul o enure an adequae delvery olely dependng on he marke mechanm. For he lberaled elecrcy marke dvere concep are developed o enure yem relably. The mo mporan one are energy only capacy paymen capacy marke and relably conrac [1]. In general no company ha an oblgaon o nve n new power plan. In he cae of horage of generang capacy hee mechanm hould creae ncenve for new nvemen. In he German marke for example he energy only prncple mplemened. Th leave he creaon of nvemen ncenve o he marke. In addon a marke for balancng energy erve o enure hor-erm ecury on an energy and capacy paymen cheme. 1.2 Man uncerane on he regulaed and deregulaed elecrcy marke Relevan uncerane for he power plan nvemen can be dfferenaed beween he one whch all along ex bu dd no really play an mporan role due o he cenraled marke regulaon and he one whch have emerged under he new framework of lberalzaon. Eher on a regulaed or lberalzed marke rucure demand noceably one of he mo unceran facor n he power plan plannng. The long-erm developmen rend of elecrcy demand rongly dependen on varou facor uch a he growh of populaon gro domec produc employmen and o on. The dffculy n properly forecang hee facor and he complexy of analyng her correlaon gnfcanly complcae he deermnaon of he developmen of he demand. Durng he power plan nvemen evaluaon no only he long-erm rend of he demand bu alo he load curve mu be condered. In he hor-erm he load profle preen an obvou perodcal cycle becaue of he rong dependency of he elecrcy demand on he meeorologcal condon. Neverhele n he horcal daa many excepon appeared whch could have hardly been foreeen n me. From boh pon of vew enurng a uffcen power upply or maxmzng prof demand forecang conue one of he key pon n power yem plannng. Uncerane aocaed wh fuel prce were earler no a ubanal concern for power plan nveor nce he ncreaed expene creaed by evenual hgh fuel prce could be reganed hrough rang he elecrcy prce. A menoned above he elecrcy prce on he lberaled marke are e by he upply-demand equlbrum. Therefore a a gnfcan par n he operang expene fuel co wll evenually nfluence he nvemen prof. In he pa few year fuel prce epecally of crude ol have experenced a very hgh degree of volaly (from he horcal low of barely10$/barrel n December 1998 o around 60$/barrel by he me of h wrng). The lack of ranparency on he upply de and dffcule o foreee he demand boh conrbue o he prce nably. Furhermore naural ga whch erve a an mporan alernave reource for ol produc ha for long been prced wh a gh lnk o ol. In h repec volale ol prce would drecly reul n volaly of ga prce. Alhough oher fuel prce how a relavely lower volaly modellng her long-erm developmen ll preen a complex ak. Elecrcy characered a a prce nelac produc nce he regulaed me. Sll now lle elacy of demand o prce can be denfed. Bu converely change n he genera- 2
3 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 ng rucure caued by addon of new capace wll lead o change n he prcng. Behavour of oher uppler make nowaday even more dffcul o foreca he elecrcy prce. The above mple ha n a lberaled envronmen no only he elecrcy prce are e by he marke bu alo he elecon of new generang echnologe ubjec o. Technologcal nnovaon however ha alway been an unpredcable and omeme even accdenal occurrence. Managng rk wh a dverfcaon of he energy mx ha already been aken no conderaon by power plan nveor. Ju lke n regulaed me energy polce relaed o elecrcy marke can mpac he nvemen decon o a grea exen. The nroducon of he greenhoue ga radng yem and he decon o phae ou nuclear power for example ha aroued nene dcuon regardng a neceary change of he energy mx. 1.3 Paper rucure The re of h paper rucured a follow: n econ 2 dvere mehod o evaluae nvemen under uncerany wll be nroduced. They are compared accordng o he dfferen echnque ued o ncorporae uncerane. Secon 3 con of a cae udy evaluang a e power plan nvemen projec hrough he applcaon of hree eleced mehod dcued. The fnal econ analyze he reul and draw concluon abou he rend n he developmen of fuure mehodologe. 2 Comparon of convenonal and new mehod wh her applcaon o power plan nvemen 2.1 Convenonal mehod for he regulaed plannng The leraure urveyed n h paper race back o he md eghe. Snce hen ncorporang uncerane no power plan nvemen evaluaon or power yem expanon plannng ha been gradually aracng he aenon of he planer. Wh he aumpon of perfec foregh parameer uch a power demand fuel prce were formerly condered o feaure a deermnc developmen. In order o acheve a more realc plannng ophcaed mehodologe dealng wh uncerane were added o he exng model ll rerced o meeng he fuure power demand wh a gven relably a mnmum co. In oher word he movaon of ncorporang hee uncerane no he modellng o a grea exen o avod he co penaly from neffcen generang rucure. In he fr par of h econ an nroducon of radonal approache wll be gven. We focu on he one whch durng he regulaed me had been mo commonly dcued n he leraure dealng wh power expanon plannng under uncerane. A farly exenve workng paper of he World Bank [2] ugge clafyng hee approache n he followng hree caegore: () ochac opmzaon () robune analy or rade-off analy and () opon value mehod. In anoher arcle [3] comparng everal olvng mehodologe addree h ue wh a dfferen clafcaon. In he abence of opon value mehod nclude he approach of deermnc equvalen n he dcuon. Wh an n-deph gh n he mehodologcal developmen no dffcul o conclude ha he deermnc equvalen approach preen he fr ep oward ncorporaon of uncerane alhough he way on whch handle he uncerane appeared o be oo mple. The erm opon value derve orgnally from he fnance marke and more pecfc from he ock marke where ued o denoe opporune o ell or buy ock hare. I exenon for power economc 3
4 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 can ll be frequenly found n recen leraure. Hence opon value mehod alo and for a gnfcan ubjec n he reearch of new mehod n h paper. All of hee four caegore are o be decrbed nex. Deermnc Equvalen In he deermnc equvalen approach nvemen plannng formulaed a a radonal lnear opmzaon problem. To keep a clear overvew we mplfy he nvemen plannng problem wh he followng formulaon: Mn { Q } ( fc + oc Q ) () Subjec o l (1.2) Q D 0 Q ρ ( τ + ) τ = 1 (1.3) (1.4) Q 0 (1.5) Where: fc oc 0 l Q D Specfc nvemen co of echnology n me age Specfc operang co of echnology n me age Invemen varable for echnology n me age Exng capace of echnology pror o he plannng horzon Mnmum nvemen capacy of echnology n me age Producon varable for echnology n me age Demand n me age ρ Tme-dependen avalably of echnology n me age Th nend o fnd an opmal power plan nvemen plan n erm of decdng on echnologe nveng me nveng capace a well a operang power plan o a o mee he fuure demand akng no accoun he avalably of he nalled capacy. A he name deermnc equvalen mple acually deal wh deermnc conran. Unceran facor a demand and fuel prce are nally aumed o be conan for each me age. Ther value are o be emaed baed on he currenly be avalable nformaon. Thu he nvemen chedule deermned by he deermnc equvalen only opmal a vewed from he curren me age. In he ucceedng age new foreca are o be aumed. Afer updang he daa nvemen raege from h age wll be agan decded by recalculang he opmzaon problem. Th proce recur ll he end of he plannng horzon. A already poned ou n [3] he deermnc equvalen approach doe no necearly lead o he mo adequae nvemen plan becaue he opmzaon n each age obvouly ju 4
5 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 reaonable for a lmed perod of me. In h conex alhough he deermnc equvalen approach doe no mply a compuaonal complexy uually no able o provde a plauble advce for he long range. Ye mgh be more nereng for he projec whch poe he flexbly o be readjued durng he execuon proce whou reulng n ubanal loe. Robune Analy In general power yem plannng a complex ak whch uually face more han one objecve. In ome cae hee objecve even conflc wh each oher. For example whle amng a a pobly economcal generaon expanon he yem planner mu mulaneouly aure ceran yem relably wh exra capace ha are lef unued for mo of he me. The robune analy approach wa developed o olve uch problem wh mulple objecve. I prncple o fnd a o called robu decon wh a rade-off analy among he conflcng objecve. In [4] h mehodology wa furher exended for applcaon under uncerany. Durng he fr ep of eekng a robu plan all he poble cenaro are ummarzed. The amoun of cenaro depend no only on he nvemen alernave he planner mgh prefer bu alo on he poble fuure ae of unceran facor. Thee cenaro decrbe all he uaon he decon-maker would evenually confron afer he plan carred ou. Furhermore f he uncerane are modeled probablcally a correpondng probably can be calculaed for each cenaro. To avod geng no a caarophc exen rgh from he ar recommended o carefully defne he meanngful plan alernave and relevan nfluencng facor. In addon he objecve purued n he plannng hould be nerpreed wh quanfable funcon e.g. he mnmzaon of he oal co or he maxmzaon of an ndex for he envronmenal compably. Ther value are ubjec o he cenaro pecfc arbue: J ( r) f ( ) = a ( S (2) r j= 1 r j ) Here f r () and for he value of r -h objecve n he -h cenaro from he cenaro e S. Equaon conrbung o compue f r () are ( ) whoe defnon and number J (r are deermned by he objecve. a r j ) Afer he problem formulaon decrbed above he rade-off analy follow. The rade-off analy nend o denfy he be comprome n he e of objecve value. Whou conderng uncerane he mulaed cenaro are dencal o he nvemen alernave. Therefore objecve value of a cenaro can be een a he objecve value of he correpondng nvemen alernave. Accordng o [4] he domnance beween wo alernave can be dfferenaed beween he condonal rc domnance and he condonal gnfcan domnance. The former obaned f he eleced alernave alway ha a beer value han he oher one for each objecve. The laer mean ha he domnan alernave ha a lea one gnfcanly beer objecve value and no gnfcanly wore han he oher canddae. To generalze he obervaon o unceran cae where he occurrence probable are gven rk analy echnque lke Mone Carlo mulaon are appled o calculae he domnance probably of an alernave relave o anoher one. Domnance defnon are alo exended o he rc global domnance and he gnfcan global domnance repecvely wh a predefned probably ay p. 5
6 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 On he ba of he global domnance deermnaon of every wo alernave he decon e rade off curve e and knee e can be exraced. Trade off curve e con of all he alernave whch are no rcly globally domnaed by any oher. A knee e he collecon of all he alernave whch are no gnfcanly globally domnaed by any oher. In he proce of fndng he decon e he nferor alernave are elmnaed. In order o defne he fnal plan ubequenly mporan o analye he decon e by examnng oher addonal queon a robune of he alernave her performance regardng a parcular objecve and her flexbly. Sochac Opmzaon Adaped from he mahemacal programmng he ochac opmzaon approach ha been frequenly appled n mul-age nvemen plannng under uncerany hence alo n power yem expanon plannng. I applcaon uually bae on he cenaro analy whch denfe dfferen ae of he fuure dependng on he poble evoluon of uncerane. The objecve of ochac opmzaon however no o fnd he opmal oluon for each cenaro bu o deermne he decon ha be f all of hem. Therefore h global opmum may no be he deal oluon for ome of hee cenaro bu repreen he be one for he whole e. To llurae he applcaon of he procedure o a power plan nvemen problem we connue akng he mplfed formulaon () a example. Fr we reformulae by addng ochac characerc: Mn { Q } (3.1) Subjec o l p fc + oc Q ) ( (3.2) Q p Q. p D ρ 0 τ + τ = 1 (3.3) (3.4) Q 0 (3.5) In (3.1) he pecfc operang co exended o a cenaro-dependen erm and an occurrence probably p aocaed o he cenaro. In h conex he objecve funcon equal o he expecaon of he ngle cenaro. The formulaon of an nvemen problem n a ochac opmzaon model doe no eem o be very dffcul aumng ha poenal echnologe her echncal performance and evoluon of uncerane a demand and fuel co are gven. Wh he nvolvemen of addonal facor hence ncreang he number of cenaro he complexy of uch problem grow exponenally. Before he appearance of he ophcaed compung echnology avalable oday he greae challenge n applyng h mehodology wa olvng uch problem. Addonally equaon (3.4) complcae he cae by makng mul-age. 6
7 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 In he leraure on he ochac opmzaon approach urveyed he Bender decompoon algorhm [5] appear o be he mo popular nrumen o olve he mul-age ochac problem. The crucal pon of applyng h echnque o ranfer he ngle complex problem no a maer problem and a e of ub problem. [6] ugge dvdng he power plan nvemen problem no an nvemen problem and an operaon problem each repreenng he maer problem and he ub problem repecvely. Soluon va h dvon can be acheved by erave opmzaon. To llurae h concep we replace he formulaon (3) wh (3 ) and (3 ) a followng: Maer problem: Mn Subjec o Sub problem: For each S : l fc (3'.1) (3'.2) 0 (3'.3) Mn Q Subjec o oc Q (3''.1) Q Q Q. D 0 ρ τ + τ = 1 0 (3' '.2) (3' '.3) (3' '.4) Where: Opmal oluon of he maer problem (3') Durng he opmzaon he maer problem (3') o be updaed durng each new eraon. Th done by changng he o called Bender cu θ and he addonal lnear conran aocaed whθ (ee Fgure 1). A convergence e nroduced o conrol he ermnaon of he erave opmzaon proce by examnng he upper bound UB and he lower bound B whch are nally e o he pove and negave nfny. The eraon procedure connue unl he convergence conran fulflled. The cheme of opmzng problem (3) ung he Bender decompoon echnque hown n Fgure 1. 7
8 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 Inalzaon: := 1 (Ieraon number) UB := B := Solve he nal maer problem: Mn fc Subjec o l Inalze he opmal value of he nvemen varable : * : = (Opmal value) Solve he ub problem for each S : Mn Q Subjec o Q : oc Q Q. D ρ τ τ = 0 Q 0 Q v = Q * : q q = Updae he upper bound: 0 + Updae he opmal value of he operaon varable : (Opmal value) (Opmal dual value) UB : = mn{ UB p ( fc + oc Q )} Updae he lower bound: B : = Solve he updaed maer problem: Mn { θ } fc +θ Subjec o l h 0 h θ p ( q ( ρ τ + Q )) τ = 1 h = Updae he opmal value of he nvemen varable : * : = * θ : = θ fc + θ (Opmal value) (Opmal value) Convergence e: ( UB B ) /(1 + B ) TO? no Nex eraon: : = +1 ye Opmal oluon found Fgure 1: Illuraon of opmzng power plan nvemen wh Bender decompoon echnque Thank o he noable progre n compung echnque made n he la decade many ofware capable of olvng large mahemacal programmng problem are now avalable. The dffcul proce of Bender decompoon already embedded n he olver of hee ofware whch can be appled o a properly formulaed problem whou he uer havng o poe dealed knowledge abou he echnque. Such a olver (CPEX) for example provded by he mahemacal programmng ofware GAMS and wa ued o olve he E2M2 model developed n [7] on whch an exemplary calculaon of he cae udy n h paper baed. The Opon Approach Conrary o he mehodology decrbed before he opon approach examne he profably of an nvemen projec and no only co. The erm opon here dffer omehow from orgn on he fnancal marke where an opon an nrumen o proec agan rk. An unexerced nvemen can be een a an opon becaue he opporune for delayng can- 8
9 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 celng and evenually wchng o oher projec are kep alve. However he nvemen hould feaure he rreverbly and he flexbly.e. he ably o wa a defned n [9]. The rreverbly denoe ha he nvemen become valuele f denfed o be unprofable. I expendure whch repreen unk co can no be reganed hrough ellng he equpmen or ung for oher purpoe. In fac h propery ex o a ceran degree n mo cae. The dnc prncple ha dfferenae he opon approach from he radonal ne preen value rule he prcng of he flexbly wh an opon value. Ung h approach nveor expec a reurn whch no only cover he co bu alo he opon value. The ably o wa valuable and omeme can brng grea benef becaue allow obanng more explc nformaon abou he evoluon of unceran facor. Pror o he marke lberalzaon he opon approach wa no commonly appled o he power plan nvemen problem a he oher one. Some reaon are conderable. Frly he way he opon approach evaluae an nvemen.e. accordng o profably no convenonal. Some auhor (e.g. [2]) argue ha he maxmzaon of prof for he prelberalzed power marke hould lead o he ame reul a he mnmzaon of co nce he demand unchanged. Th hypohe however doe no hold for an mperfec marke where he prce are no e by he compeon equlbrum. Anoher reaon could con n he lack of flexbly o delay an nvemen on he regulaed marke. Depe hee unfavorable concern ome bac dea o adap he opon approach n power plan nvemen can ll be denfed. In [9] for example h mehod wa appled o a wo-age nvemen projec whch hould decde wheher o nall one 200-MW coal-fred plan or wo 100-MW ol-fred plan o mee a yearly demand ncreae of 100 MW. Whle aumng he demand ncreae o be known unceran fuel prce are aken no accoun. In h cae he cale compared o he flexbly. Alhough he lager coal plan comple wh he economy of cale nveng n an ol plan n he fr year provde he pobly o wch n oher echnology f he ol prce urn o be dadvanageou. In recen year he opon approach ha araced much more aenon no only n he evaluaon of nvemen problem bu alo n he operaon of power yem. In he nex par of h econ we are gong o dcu h approach once agan h me n he framework of a lberalzed marke. 2.2 New mehod for he lberalzed marke I no very exac o defne he mehod a new one nce hey already exed and were appled n he me before marke lberalzaon. They are een a new n he lgh of he modfcaon and exenon requred o make hem f for he new envronmen. In conra o he power generaon plannng of he regulaed era decon on power nvemen on he lberalzed marke are done baed on he profably raher han on yem adequacy. A ndcaed by he macroeconomc heory he maxmum of ocal welfare could be reached by he prof maxmzaon of each ndvdual marke parcpan. However h docrne only enable under he aumpon of a perfec marke. Some elecrcy marke do no fulfll h prereque depe beng lberalzed. A an example alhough he German marke 100% lberalzed can be beer decrbed a an olgopoly where he four large ule ll poe he domnan poon. On he oher hand elecrcy conumer do no repond o he prce change a much a before. Therefore clacal economc rule may no be uable 9
10 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 for elecrcy marke and upplemenary nrumen hould be developed o provde a ecure power upply. Dcouned Cah Flow Approach The dcouned cah flow (DCF) approach wa nroduced n an OECD repor [15]. I ake uncerane no accoun n a general way n whch a dcoun rae aumed for he emaon of all major co componen. The deermnaon of h dcoun rae bae on an aemen of varou uncerane wh dfferen cenaro. The OECD udy ae ha compane can apply he DCF approach a comparng dfferen echnologe wh predefned nernal arge for reurn on equy. To addonally handle uncerane n revenue he auhor adve o emae anoher dcoun rae for revenue dfferen han he one for co. Baed on he recen updae of an OECD udy [16] a mehodology o calculae he o called Average feme eveled Elecrcy Generaon Co nroduced. The prncple o fnd a reference co of a projec by makng he preen value of oal co equal o he preen value of revenue over he lfeme. Equaon (4) explan h mehodology n he mahemacal conex. T = 0 * T p E I ( 1+ r) = 0 Where: + M + F (1 + r) = 0 (4) * p r E I M F Reference co o be defned Rk-adjued dcoun rae Elecrcy generaon n he year Invemen expendure n he year Manenance expendure n he year Fuel expendure n he year By olvng (4) * p can be calculaed by applyng he followng formula: p T ( I + M * = 0 = T = 0 + F ) (1 + r) E (1 + r) (5) Ung he reference co o emae dfferen nvemen opon offer he calculaon mplcy and he comparon convenence. However he eleced dcoun rae no elf explanaory nce he way how he dcoun rae deermned by ncludng all uncerane no h facor obcure. Furhermore wheher approprae o rea uncerane n each year baed on he ame dcoun rae alo queonable. 10
11 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 Real Opon Approach In econ 2.1 an nroducon for he bac prncple of he opon approach and a prelmnary example of applcaon o he power plan nvemen problem were provded. The adapaon of he fnancal opon for real ae nvemen whch herefore named real opon had been dcued over he la wo decade. I wa however no wdely acceped on he regulaed power marke. Due o he enormou change of marke fundamenal nce he lberalzaon many reearcher have nvolved he real opon approach n her analy of ome apec of he power yem e.g. uly nvemen and un commmen. Boerud e al. [10] deve a model o calculae he opmal power generaon nvemen raegy under boh cenralzed ocal welfare and decenralzed prof objecve. In [11] h model even exended o analyze he effec of nvemen ncenve on he yem adequacy of an elecrcy marke wh he capacy paymen mechanm. Roque e al. [12] deal wh an nereng obervaon on he lberalzed power marke ha ndvdual nveor end o prefer fol fuel echnologe (carbon naure ga) agan nuclear power. They explan h ue by howng he decreae of he opon value of he nuclear echnology wh a rng correlaon beween elecrcy ga and carbon prce. In order o conder he behavor of oher marke parcpan n nvemen decon Muro [13] develop a mehod combnng he real opon approach wh game heory o ncorporae he compeve neracon no nvemen evaluaon. Snce h paper concenrae on he evaluaon of power generaon projec he mehodology developed by Boerud farly repreenave for an applcaon of he real opon approach. He llurae he dfferenaon of he real opon heory from he clacal ne preen value (NPV) mehod wh he dagram of Fgure 2. Ne Preen Value (NPV) I: Invemen co V*: opmal hrehold for nvemen F(V) = N(V) + A(V) F(V) A(V) N(V) I V* Ne Cah flow from Projec V Fgure 2: Illuraon of he dfference beween he real opon approach and he NPV mehod The curve N(V) how he NPV over he range of poenal ne cah flow of he projec. The clacal NPV mehod would ugge nveng a oon a he ne cah flow exceed he nvemen co I. Accordng o he real opon heory hould however no ye be nveed 11
12 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 unl he NPV of he projec exceed he value of he nvemen opon. The opon value F(V) reul from he NPV of he projec plu an addonal value A(V) of poponng he nvemen decon o wa for more nformaon abou fuure rend of uncerane. In h conex decon-makng ung he ac NPV mehod rea he nvemen raher a a now or never ak. In he mul-age model developed n [10] demand he only facor condered a unceran. A long-erm and a hor-erm uncerany are aken no accoun. Furhermore o quanfy he rk averon of he nveor a rk-adjued dcoun rae ued. The model underle he objecve of maxmzng he ocal welfare or he nvemen prof by deermnng he opmal echnology and nvemen mng. To olve h model he ochac dynamc programmng ued for a backward opmzaon. Becaue he dynamc programmng mple a grea mahemacal complexy and doe no belong o he cope of h paper wll no be dcued n deal. The model n [10] unforunaely ha ome lmaon nce he elecrcy marke condered a a ngle-agen yem. Thu he neracon beween dfferen marke parcpan dregarded. I alo aumed ha nveor are purely prce aker. Bu on he compeve power marke elecrcy prce could be nfluenced o a grea exen e.g. when a new large cale power plan become avalable. To ake he mpac of new capace on he elecrcy prce no he model Keppo and u [14] nclude he prce effec n he calculaon of he opon value conderng ha no only he value of he new plan bu alo he value of oher exng plan of he nveor ubjec o marke prce. The value of a real opon can hen be exended o he followng expreon: F(V) = N(V) + A(V) (V) (5) The erm (V) demonrae he lo value due o lowered marke prce beng caued by he nvemen. A mlar concepon can be found n [17] where he auhor defne he value of a company a he compoon of operave raegc real opon and he value of real ae calculaed on he ba of he adoped raegy. A gnfcan advanage poned ou n [9] a well a n [17] ha applyng he real opon approach avod he elecon of a rk-adjued rae. The nvemen evaluaon calculae drecly wh he rk-free rae whle ncludng uncerane wh her ochac profle n he evaluaon proce. Alhough he applcaon of he real opon heory n he power yem preen a ubanal progre n he mehodology developmen bu he ranfer of h concep from he fnance marke frequenly crczed due o he mperfecon of he elecrcy marke and lower lqudy on radng poble. Therefore prcng of a real opon baed on he marke dffcul [18]. Anoher dffculy ndcaed n he acquon of opon-pecfc npu daa a ochac coeffcen decrbng he volaly of he fuel prce developmen. 2.3 Mehod comparon In h par we preen a bref revew of he urveyed mehod by comparng hem accordng o four characerc a lluraed n Table 1. 12
13 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 Sochac Dynamc Analycal Compuaonal complexy Pre-lberalzaon Snce lberalzaon Deermnc Equvalen Robune Analy Sochac Opmzaon Opon Approach Dcouned Cah Flow Approach Real Opon Approach low - - low - hgh very hgh low very hgh Table 1: Comparon of dcued mehod 3 Cae udy for a e projec In h econ he reul of he applcaon of hree eleced approache nroduced n econ 2 o a cae udy are preened. I mporan o noe ha daa ued for h cae udy bacally aumed for an exemplary calculaon and doe no reflec he realy. In h example a company plan o nve n new capace o mee he ncreae n demand n 2 conecuve year wh an expeced conan growh rae of 100 MW n each perod. The wo echnologe avalable for h company o nve n are coal fred or ga fred plan. Due o echncal conran each coal and ga plan can only be bul wh a ne nalled capacy of 200 MW and 100 MW repecvely. Demand and operang co of he coal plan are aumed a ceran. The evoluon of he operang co of ga plan on he oher hand aumed o preen a gven ochac profle durng he plannng perod and a conan growh rae aferward. I alo agreed ha he eleced power plan could be ready for operaon a he begnnng of each year. In order o provde a comparable bae he lfeme and full load hour of boh plan are equally e o 40 year and 5000 hour. A dcoun rae of 10% choen for he followng calculaon. In Table 2 he parameer of he wo plan ype and he developmen of her operang co are preened. The ga prce n hee wo year aumed o be parcularly volale. Capacy Cap [MW] Invemen co fc [Mo. ] Operaon co n bae year [ / MWh] Operaon co growh rae =1 =2 =3 40 Coal fred plan % 5% 5% Ga fred plan Pr 50% : 50% Pr 50% : 50% Pr 50% : -50% Pr 50% : -50% 5% Table 2: Daa of wo canddae echnologe 13
14 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 The ochac profle gven n Table 2 reul n four cenaro for he developmen of fuure operaon co of he ga fred plan: Scenaro Probably p Operaon co of he ga fred plan oc =1 =2 2 [ /MWh] 1 25% % % % Table 3: Scenaro of fuure operaon co of he ga fred plan We fr formulae h nvemen projec n a ochac opmzaon problem amng a he mnmzaon of oal co durng he plannng perod. Mn = 1 = 1 = 1 fc ( Cap 1 u + p oc Q ) (6) Subjec o 2 Q. D = 1 Q Q τ = 1 u τ Cap 0 u {01} Where: u : Bnary decon varable 1 and for he nvemen n he echnology The opmal oluon of h projec baed on he ochac opmzaon ugge an nvemen of a ga fred plan wh 100 MW capacy for each perod wh a oal expene of Mo. durng he plannng perod. Furher we apply he wo approache dcued a he new mehod n he evaluaon of he cae udy projec. Three alernave nvemen plan are predefned and led n Table 4. Alernave 1 ugge an nvemen n 200 MW of capacy wh one coal fred power. Th repec he economy of cale rule. In conra Alernave 2 buld ju he capacy whch requred n each year and chooe a ga fred plan for each perod. Alernave 3 combne boh opon by addng he exac capacy needed for he fr year and a larger cale coal plan for he remanng me. 14
15 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 =1 =2 Coal [MW] Ga [MW] Coal [MW] Ga [MW] Alernave Alernave Alernave Table 4: Conderable nvemen alernave In he fr ep he leveled co mehod appled o evaluae hee hree alernave. The preen value of oal co and he average lfeme leveled generaon co are calculaed: * p [ /MWh] pv oal [Mo. ] Alernave Alernave Alernave Table 5: Calculaon reul wh leveled co mehod Accordng o he comparon n Table 5 Alernave 1 obvouly he mo economcal varan no only regardng average leveled co bu alo he preen value of oal co. For he nex evaluaon we ue he real opon heory o examne agan he hree nvemen alernave. Alernave 1 doe no need o be modfed and he preen value of oal co over he lfeme correpond o he calculaon reul above. Alernave 2 and Alernave 3 wll furher be een a an nvemen opon whch gve he pobly o wa for more nformaon abou he ga prce developmen rend n he econd year. If he ga prce end o be hgher whch would rae he operaon co n he fr year he nveor could wch he decon o a coal fre plan wh lower fuel co or ck o he nal plan of buldng anoher ga plan. Baed on h we can calculae he preen value of h opon wh he followng formulaon: OV = 50 Mo. (7) 40 /MWh MW 5000h 180 Mo ( + 40 = 2 20 /MWh MW 5000 h ) 90 Mo /MWh MW 5000 h 50 Mo ( + 15
16 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 = 455 Mo. 20 /MWh 200 MW 5000 h = 3 20 /MWh MW 5000 h ) -2 The preen value of h opon gnfcanly lower han ha of Alernave 1. Therefore buldng a ga fred plan n he fr year and keepng he opon for he followng year hould be he preferred decon. A he evaluaon reul how he real opon approach aache addonal value o he nvemen flexbly. The coherence beween uncerane and nvemen decon can be quanavely preened by real opon model wh he mplcaon ha he more unceran he fuure he more valuable he opon and he longer he nvemen me wll be delayed [18]. 4 Concluon The mehod dcued n h paper cover he man caegore commonly ued durng he regulaed me and hoe mehod ha are beng exended for her applcaon n he lberalzed marke. The way each mehod ncorporae uncerane no power plan nvemen evaluaon wa decrbed and compared. Through a cae udy he meanng of dealng wh uncerane n he decon makng wa demonraed and wa hown ha could lead o a oally dfferen reul han baed on purely deermnc aumpon. Of all he mehod decrbed n h paper he real opon approach repreen a novel approach wh he ably o quanavely emae he flexbly of choong beween avalable echnologe deermnng nvemen mng and defnng nvemen cale. A hown n h paper mo mehod dealng wh uncerane demand her quanave decrpon. Therefore mehodologe able o precely model he uncerane wll be requred o furher mprove hee mehod and her applcably. On he oher hand hgher accuracy on he decrpon of uncerane may dramacally ncreae he complexy of he decon problem due o he ochac and dynamc propere. Therefore he developmen of mehodologe o denfy he gnfcan nfluencng facor anoher neceary and challengng ak. 16
17 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 Acknowledgemen Th paper preen a reearch whn he ongong projec Energewrchaflche Anforderungen und Inveonenchedungen für neue Krafwerke m lberaleren Mark fnancally uppored by he Sfung Energeforchung Baden-Würemberg Semen AG E. ON Energe AG and MTU Aero Engne GmbH aocaed wh projec KW21: Reearch Nework Power Plan for he 21 Cenury (hp:// Reference [1] Krchen D. and Srbac G. (2004) Fundamenal of Power Syem Economc: [2] Croulla E. O. (1989) Incorporang Rk and Uncerany n Power Syem Plannng Workng Paper of The World Bank [3] Gorenn B. G. Campodonco N. M. Coa J. P. and Perera M. V. F. (1993) Power Syem Expanon Plannng Under Uncerany IEEE Tranacon On Power Syem 8(1): [4] Burke W. J. Merrll H. M. Schweppe F. C. ovell B. E. McCoy and M. F. Monohon S. A. (1988) Trade Off Mehod n Syem Plannng IEEE Tranacon On Power Syem 3(3): [5] Bender J. F. (1962) Paronng procedure for olvng mxed varable programmng problem Numer. Mah. vol. 4: [6] Granvlle S. (1988) Mahemacal Decompoon Technque for Power Syem Expanon Plannng EPRI E-5299 [7] Swder D. J. and Weber C. (2005) The Effec of Sochac Elecrcy Marke Modellng on Emang Addonal Co of Inermen RES-E Inegraon 7h IAEE European Conference Bergen Norway [8] Kalvelagen E. (2003) Bender Decompoon for Sochac Programmng wh GAMS hp:// [9] Dx A.K. and Pndyck R.S. (1994) Invemen under Uncerany Prnceon Unvery Pre: 3-54 [10] Boerud A. Ilc M. D. and Wangeneen I. (2004) Opmal Invemen n Power Generaon Under Cenralzed and Decenralzed Decon Makng IEEE Tranacon On Power Syem 20(1): [11] Boerud A. and Korpå M. (2004) Modellng of Power Generaon Invemen Incenve under Uncerany n beralzed Elecrcy Marke 6h IAEE European Conference Zurch Swzerland [12] Roque F. A. Nuall W.J. Newbery D. M. and de Neufvlle R. (2005) Nuclear Power: a Hedge agan Unceran Ga and Carbon Prce? hp:// 17
18 Preened a he 29h IAEE Inernaonal Conference. Podam Germany June 2006 [13] Muro P.(2003) On Invemen Uncerany and Sraegc Ineracon wh Applcaon n Energy Marke Syem Analy aboraory Reearch Repor A84 Helnk Unvery of Technology Fnland [14] Keppo J. and u H. (2003) Real Opon and A arge Producer: The Cae o Elecrcy Marke Energy Economc 25(2003): [15] OECD/IEA (2003) Power Generaon Invemen n Elecrcy Marke: [16] OECD/IEA (2005) Projeced co of Generang Elecrcy 2005 Updae: [17] Ram A. (2001) De Bewerung von Krafwerknveonen al Realoponen. Hommel U. Scholch M. and Vollrah R. Reale Oponen n der Unernehmenprax. Sprnger Verlag: [18] Müller D. (2005) Inveonenchedung n der Elekrzäwrchaf ene berebwrchaflche Analye. Zechrf für Energewrchaf 29(2005) 1:
(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function
MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,
More informationA Demand System for Input Factors when there are Technological Changes in Production
A Demand Syem for Inpu Facor when here are Technologcal Change n Producon Movaon Due o (e.g.) echnologcal change here mgh no be a aonary relaonhp for he co hare of each npu facor. When emang demand yem
More informationA. Inventory model. Why are we interested in it? What do we really study in such cases.
Some general yem model.. Inenory model. Why are we nereed n? Wha do we really udy n uch cae. General raegy of machng wo dmlar procee, ay, machng a fa proce wh a low one. We need an nenory or a buffer or
More informationUNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION
INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he
More informationVariants of Pegasos. December 11, 2009
Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on
More informationLecture 11: Stereo and Surface Estimation
Lecure : Sereo and Surface Emaon When camera poon have been deermned, ung rucure from moon, we would lke o compue a dene urface model of he cene. In h lecure we wll udy he o called Sereo Problem, where
More informationCooling of a hot metal forging. , dt dt
Tranen Conducon Uneady Analy - Lumped Thermal Capacy Model Performed when; Hea ranfer whn a yem produced a unform emperaure drbuon n he yem (mall emperaure graden). The emperaure change whn he yem condered
More informationGraduate Macroeconomics 2 Problem set 5. - Solutions
Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K
More informationANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES. Wasserhaushalt Time Series Analysis and Stochastic Modelling Spring Semester
ANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES Waerhauhal Tme Sere Analy and Sochac Modellng Sprng Semeer 8 ANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES Defnon Wha a me ere? Leraure: Sala, J.D. 99,
More informationReactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times
Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November
More informationH = d d q 1 d d q N d d p 1 d d p N exp
8333: Sacal Mechanc I roblem Se # 7 Soluon Fall 3 Canoncal Enemble Non-harmonc Ga: The Hamlonan for a ga of N non neracng parcle n a d dmenonal box ha he form H A p a The paron funcon gven by ZN T d d
More informationTHE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS
THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he
More informationL N O Q. l q l q. I. A General Case. l q RANDOM LAGRANGE MULTIPLIERS AND TRANSVERSALITY. Econ. 511b Spring 1998 C. Sims
Econ. 511b Sprng 1998 C. Sm RAD AGRAGE UPERS AD RASVERSAY agrange mulpler mehod are andard fare n elemenary calculu coure, and hey play a cenral role n economc applcaon of calculu becaue hey ofen urn ou
More informationSolution in semi infinite diffusion couples (error function analysis)
Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of
More informationELIMINATION OF DOMINATED STRATEGIES AND INESSENTIAL PLAYERS
OPERATIONS RESEARCH AND DECISIONS No. 1 215 DOI: 1.5277/ord1513 Mamoru KANEKO 1 Shuge LIU 1 ELIMINATION OF DOMINATED STRATEGIES AND INESSENTIAL PLAYERS We udy he proce, called he IEDI proce, of eraed elmnaon
More information( ) () we define the interaction representation by the unitary transformation () = ()
Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger
More informationControl Systems. Mathematical Modeling of Control Systems.
Conrol Syem Mahemacal Modelng of Conrol Syem chbum@eoulech.ac.kr Oulne Mahemacal model and model ype. Tranfer funcon model Syem pole and zero Chbum Lee -Seoulech Conrol Syem Mahemacal Model Model are key
More informationThe Dynamic Programming Models for Inventory Control System with Time-varying Demand
The Dynamc Programmng Models for Invenory Conrol Sysem wh Tme-varyng Demand Truong Hong Trnh (Correspondng auhor) The Unversy of Danang, Unversy of Economcs, Venam Tel: 84-236-352-5459 E-mal: rnh.h@due.edu.vn
More informationV.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS
R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon
More informationChapter 6: AC Circuits
Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.
More informationLIABILITY VALUATION FOR LIFE INSURANCE CONTRACTS:THE CASE OF A NON HOMOGENEOUS PORTFOLIO
LIABILITY VALUATION FOR LIFE INSURANCE CONTRACTS:THE CASE OF A NON HOMOGENEOUS PORTFOLIO Albna Orlando and Aleandro Trudda 2 C.n.r. Iuoper le Applcazon del Calcolo. Napol (e-al: a.orlando@na.ac.cnr.) 2
More information1) According to the article, what is the main reason investors in US government bonds grow less optimistic?
4.02 Quz 3 Soluon Fall 2004 Mulple-Choce Queon Accordng o he arcle, wha he man reaon nveor n US governmen bond grow le opmc? A They are concerned abou he declne (deprecaon of he dollar, whch, n he long
More informationLinear Response Theory: The connection between QFT and experiments
Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure
More informationLecture 11 SVM cont
Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc
More informationMultiple Regressions and Correlation Analysis
Mulple Regreon and Correlaon Analy Chaper 4 McGraw-Hll/Irwn Copyrgh 2 y The McGraw-Hll Compane, Inc. All rgh reerved. GOALS. Decre he relaonhp eween everal ndependen varale and a dependen varale ung mulple
More informationA Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed
IJCSI Inernaonal Journal of Compuer Scence Iue, Vol. 9, Iue 3, No, ay ISSN (Onlne): 694-84 www.ijcsi.org 8 A Nonlnear ILC Scheme for Nonlnear Dynamc Syem o Improve Convergence Speed Hoen Babaee, Alreza
More informationRisky Swaps. Munich Personal RePEc Archive. Gikhman, Ilya Independent Research. 08. February 2008
MPR Munch Peronal RePEc rchve Ry Swap Ghman Ilya Independen Reearch 8. February 28 Onlne a hp://mpra.ub.un-muenchen.de/779/ MPR Paper o. 779 poed 9. February 28 / 4:45 Ry Swap. Ilya Ghman 677 Ivy Wood
More informationSolution Strategies for Multistage Stochastic Programming with Endogenous Uncertainties
oluon raege for Mulage ochac Programmng wh Endogenou Uncerane Vja Gupa* Ignaco E. Gromann Deparmen of Chemcal Engneerng Carnege Mellon Unver Purgh PA 523 Arac In h paper we preen a generc Mulage ochac
More informationFX-IR Hybrids Modeling
FX-IR Hybr Moeln Yauum Oajma Mubh UFJ Secure Dervave Reearch Dep. Reearch & Developmen Dvon Senor Manaer oajma-yauum@c.mu.jp Oaka Unvery Workhop December 5 h preenaon repreen he vew o he auhor an oe no
More informationSSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018
SSRG Inernaonal Journal of Thermal Engneerng (SSRG-IJTE) Volume 4 Iue 1 January o Aprl 18 Opmal Conrol for a Drbued Parameer Syem wh Tme-Delay, Non-Lnear Ung he Numercal Mehod. Applcaon o One- Sded Hea
More informationDiscounting, Risk and Inequality: A General Approach
Dcounng, Rk and Inequaly: A General Approach Marc Fleurbaey a Séphane Zuber b Ocober 2013 Abrac The common pracce con n ung a unque value of he dcoun rae for all publc nvemen. Endorng a ocal welfare approach
More informationEcon107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6)
Econ7 Appled Economercs Topc 5: Specfcaon: Choosng Independen Varables (Sudenmund, Chaper 6 Specfcaon errors ha we wll deal wh: wrong ndependen varable; wrong funconal form. Ths lecure deals wh wrong ndependen
More informationDynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005
Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc
More informationMultiple Failures. Diverse Routing for Maximizing Survivability. Maximum Survivability Models. Minimum-Color (SRLG) Diverse Routing
Mulple Falure Dvere Roung for Maxmzng Survvably One-falure aumpon n prevou work Mulple falure Hard o provde 100% proecon Maxmum urvvably Maxmum Survvably Model Mnmum-Color (SRLG) Dvere Roung Each lnk ha
More informationOMXS30 Balance 20% Index Rules
OMX30 Balance 0% ndex Rules Verson as of 30 March 009 Copyrgh 008, The NADAQ OMX Group, nc. All rghs reserved. NADAQ OMX, The NADAQ ock Marke and NADAQ are regsered servce/rademarks of The NADAQ OMX Group,
More informationNON-HOMOGENEOUS SEMI-MARKOV REWARD PROCESS FOR THE MANAGEMENT OF HEALTH INSURANCE MODELS.
NON-HOOGENEOU EI-AKO EWA POCE FO THE ANAGEENT OF HEATH INUANCE OE. Jacque Janen CEIAF ld Paul Janon 84 e 9 6 Charlero EGIU Fax: 32735877 E-mal: ceaf@elgacom.ne and amondo anca Unverà a apenza parmeno d
More informationOutline. Probabilistic Model Learning. Probabilistic Model Learning. Probabilistic Model for Time-series Data: Hidden Markov Model
Probablsc Model for Tme-seres Daa: Hdden Markov Model Hrosh Mamsuka Bonformacs Cener Kyoo Unversy Oulne Three Problems for probablsc models n machne learnng. Compung lkelhood 2. Learnng 3. Parsng (predcon
More informationApplication of the PageRank algorithm for ranking locations of a production network
Applcaon of he PageRank algorh for rankng locaon of a producon nework Bernd Scholz-Reer (2), Faban Wrh 2, Sergey Dahkovky 3, hoa Makuchewz, Mchael Koykov 3, Mchael Schönlen 2 Plannng and Conrol of Producon
More informationLecture 6: Learning for Control (Generalised Linear Regression)
Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson
More informationModeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts
nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong
More informationOn One Analytic Method of. Constructing Program Controls
Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna
More informationMatrix reconstruction with the local max norm
Marx reconrucon wh he local max norm Rna oygel Deparmen of Sac Sanford Unvery rnafb@anfordedu Nahan Srebro Toyoa Technologcal Inue a Chcago na@cedu Rulan Salakhudnov Dep of Sac and Dep of Compuer Scence
More informationLecture VI Regression
Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M
More informationPolitical Economy of Institutions and Development: Problem Set 2 Due Date: Thursday, March 15, 2019.
Polcal Economy of Insuons and Developmen: 14.773 Problem Se 2 Due Dae: Thursday, March 15, 2019. Please answer Quesons 1, 2 and 3. Queson 1 Consder an nfne-horzon dynamc game beween wo groups, an ele and
More informationAn introduction to Support Vector Machine
An nroducon o Suppor Vecor Machne 報告者 : 黃立德 References: Smon Haykn, "Neural Neworks: a comprehensve foundaon, second edon, 999, Chaper 2,6 Nello Chrsann, John Shawe-Tayer, An Inroducon o Suppor Vecor Machnes,
More informationAn Effective League Championship Algorithm for the Stochastic Multi- Period Portfolio Optimization Problem
An Effecve League Champonhp Algorhm for he Sochac Mul- Perod Porfolo Opmzaon Problem Al Huenzadeh Kahan *1, Mohammad Eyvaz 2, Amn Abba-Pooya 3 Faculy of Indural and Syem Engneerng, Tarba Modare Unvery,
More informationEEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment
EEL 6266 Power Sysem Operaon and Conrol Chaper 5 Un Commmen Dynamc programmng chef advanage over enumeraon schemes s he reducon n he dmensonaly of he problem n a src prory order scheme, here are only N
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu
More informationTSS = SST + SSE An orthogonal partition of the total SS
ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally
More informationDepartment of Economics University of Toronto
Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of
More informationRobustness Experiments with Two Variance Components
Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference
More informationLecture 18: The Laplace Transform (See Sections and 14.7 in Boas)
Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as
More informationDelay-Limited Cooperative Communication with Reliability Constraints in Wireless Networks
ource relay 1 relay 2 relay m PROC. IEEE INFOCOM, RIO DE JANEIRO, BRAZIL, APRIL 2009 1 Delay-Lmed Cooperave Communcaon wh Relably Conran n rele Nework Rahul Urgaonkar, Mchael J. Neely Unvery of Souhern
More informationAppendix H: Rarefaction and extrapolation of Hill numbers for incidence data
Anne Chao Ncholas J Goell C seh lzabeh L ander K Ma Rober K Colwell and Aaron M llson 03 Rarefacon and erapolaon wh ll numbers: a framewor for samplng and esmaon n speces dversy sudes cology Monographs
More informationRELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA
RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA Mchaela Chocholaá Unversy of Economcs Braslava, Slovaka Inroducon (1) one of he characersc feaures of sock reurns
More informationJohn Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany
Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy
More informationLet s treat the problem of the response of a system to an applied external force. Again,
Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem
More informationLi An-Ping. Beijing , P.R.China
A New Type of Cpher: DICING_csb L An-Png Bejng 100085, P.R.Chna apl0001@sna.com Absrac: In hs paper, we wll propose a new ype of cpher named DICING_csb, whch s derved from our prevous sream cpher DICING.
More informationCS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4
CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped
More informationVolatility Interpolation
Volaly Inerpolaon Prelmnary Verson March 00 Jesper Andreasen and Bran Huge Danse Mares, Copenhagen wan.daddy@danseban.com brno@danseban.com Elecronc copy avalable a: hp://ssrn.com/absrac=69497 Inro Local
More informationOnline Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading
Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng
More informationProblem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.
CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex
More information7.6 Disjoint Paths. 7. Network Flow Applications. Edge Disjoint Paths. Edge Disjoint Paths
. Nework Flow Applcaon. Djon Pah Algorhm Degn by Éva Tardo and Jon Klenberg Copyrgh Addon Weley Slde by Kevn Wayne Algorhm Degn by Éva Tardo and Jon Klenberg Copyrgh Addon Weley Slde by Kevn Wayne Edge
More informationOrdinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s
Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class
More informationGENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim
Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran
More informationEstimation of Cost and. Albert Banal-Estanol
Esmaon of Cos and Producon Funcons ns Movaon: Producon and Cos Funcons Objecve: Fnd shape of producon/cos funcons Evaluae effcency: Increasng reurns, economes of scale Complemenary/subsuably beween npus
More informationOligopoly with exhaustible resource input
Olgopoly wh exhausble resource npu e, P-Y. 78 Olgopoly wh exhausble resource npu Recebmeno dos orgnas: 25/03/202 Aceação para publcação: 3/0/203 Pu-yan e PhD em Scences pela Chnese Academy of Scence Insução:
More informationFundamentals of PLLs (I)
Phae-Locked Loop Fundamenal of PLL (I) Chng-Yuan Yang Naonal Chung-Hng Unvery Deparmen of Elecrcal Engneerng Why phae-lock? - Jer Supreon - Frequency Synhe T T + 1 - Skew Reducon T + 2 T + 3 PLL fou =
More informationOn computing differential transform of nonlinear non-autonomous functions and its applications
On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,
More informationCan we use seasonally adjusted variables in dynamic factor models? *
Can we ue eaonally adjued varable n dynamc facor model? Maxmo Camacho + Unverdad de Murca mcamacho@um.e Yulya ovcha Unverdad Rovra--Vrgl yulya.lovcha@gmal.com Gabrel Perez Quro Banco de Epaña and CEPR
More informationSecurity Constrained Economic Dispatch: A Markov Decision Process Approach with Embedded Stochastic Programming
Secury Conraned Economc Dpach: A Markov Decon Proce Approach wh Embedded Sochac Programmng Lzh Wang an aan profeor n Indural and Manufacurng Syem Engneerng a Iowa Sae Unvery, and he alo hold a courey jon
More informationRobust and Accurate Cancer Classification with Gene Expression Profiling
Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem
More informationIn the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!
ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal
More informationFTCS Solution to the Heat Equation
FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence
More informationResearch Article A Two-Mode Mean-Field Optimal Switching Problem for the Full Balance Sheet
Hndaw Publhng Corporaon Inernaonal Journal of Sochac Analy Volume 14 Arcle ID 159519 16 page hp://dx.do.org/1.1155/14/159519 Reearch Arcle A wo-mode Mean-Feld Opmal Swchng Problem for he Full Balance Shee
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ
More informationTime-interval analysis of β decay. V. Horvat and J. C. Hardy
Tme-nerval analyss of β decay V. Horva and J. C. Hardy Work on he even analyss of β decay [1] connued and resuled n he developmen of a novel mehod of bea-decay me-nerval analyss ha produces hghly accurae
More informationJanuary Examinations 2012
Page of 5 EC79 January Examnaons No. of Pages: 5 No. of Quesons: 8 Subjec ECONOMICS (POSTGRADUATE) Tle of Paper EC79 QUANTITATIVE METHODS FOR BUSINESS AND FINANCE Tme Allowed Two Hours ( hours) Insrucons
More informationFinancial Market Integration and Business Cycle Volatility in a Monetary Union
Kel Inue of World Economc Dueernbrooker Weg 20 2405 Kel (Germany) Kel Workng Paper No. 5 Fnancal Marke Inegraon and Bune Cycle Volaly n a Moneary Unon by Chran Perdzoch July 2002 The reponbly for he conen
More informationCubic Bezier Homotopy Function for Solving Exponential Equations
Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.
More informationRobust planning model for logistics relief warehouses locating based on Monte Carlo simulation model
2015, TexRoad Publcaon ISSN: 2090-4274 Journal of Appled Envronmenal and Bologcal Scence www.exroad.com Robu plannng model for logc relef warehoue locang baed on Mone Carlo mulaon model Farzaneh Mahdan
More informationRandomized Perfect Bipartite Matching
Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for
More informationStandard Error of Technical Cost Incorporating Parameter Uncertainty
Sandard rror of echncal Cos Incorporang Parameer Uncerany Chrsopher Moron Insurance Ausrala Group Presened o he Acuares Insue General Insurance Semnar 3 ovember 0 Sydney hs paper has been prepared for
More informationDual Approximate Dynamic Programming for Large Scale Hydro Valleys
Dual Approxmae Dynamc Programmng for Large Scale Hydro Valleys Perre Carpener and Jean-Phlppe Chanceler 1 ENSTA ParsTech and ENPC ParsTech CMM Workshop, January 2016 1 Jon work wh J.-C. Alas, suppored
More informationAdvanced time-series analysis (University of Lund, Economic History Department)
Advanced me-seres analss (Unvers of Lund, Economc Hsor Dearmen) 3 Jan-3 Februar and 6-3 March Lecure 4 Economerc echnues for saonar seres : Unvarae sochasc models wh Box- Jenns mehodolog, smle forecasng
More informationAdvanced Macroeconomics II: Exchange economy
Advanced Macroeconomcs II: Exchange economy Krzyszof Makarsk 1 Smple deermnsc dynamc model. 1.1 Inroducon Inroducon Smple deermnsc dynamc model. Defnons of equlbrum: Arrow-Debreu Sequenal Recursve Equvalence
More informationXMAP: Track-to-Track Association with Metric, Feature, and Target-type Data
XMAP: Track-o-Track Aocaon wh Merc, Feaure, Targe-ype Daa J. Ferry Meron, Inc. Reon, VA, U.S.A. ferry@mec.com Abrac - The Exended Maxmum A Poeror Probably XMAP mehod for rack-o-rack aocaon baed on a formal,
More informationCS626 Speech, Web and natural Language Processing End Sem
CS626 Speech, Web and naural Language Proceng End Sem Dae: 14/11/14 Tme: 9.30AM-12.30PM (no book, lecure noe allowed, bu ONLY wo page of any nformaon you deem f; clary and precon are very mporan; read
More informationPASSIVE USE OF SOLAR ENERGY IN DOUBLE SKIN FACADES FOR REDUCTION OF COOLING LOADS
PSSIVE USE OF SOLR ENERGY IN DOUBLE SKIN FCDES FOR REDUCTION OF COOLING LODS naolj Borodnec Jurg Zem lekej Prozumen Rga Techncal Unvery P. o.box 526, LV-00, Rga, Lava anaolj.borodnec@ru.lv alekej.prozumen@ru.lv
More informationInventories and Mixed Duopoly with State-Owned and Labor-Managed Firms
Bune,,, 6- do:436/b4 Publhed Onlne June (hp://wwwscrporg/journal/b) nvenore and Mxed Duopoly wh Sae-Owned and Labor-Managed Frm Kazuhro Ohnh nue for Bac Economc Scence, Oaka, Japan Emal: ohnh@epeopleorjp
More informationGravity Segmentation of Human Lungs from X-ray Images for Sickness Classification
Gravy Segmenaon of Human Lung from X-ray Image for Sckne Clafcaon Crag Waman and Km Le School of Informaon Scence and Engneerng Unvery of Canberra Unvery Drve, Bruce, ACT-60, Aurala Emal: crag_waman@ece.com,
More informationA Simulation Based Optimal Control System For Water Resources
Cy Unversy of New York (CUNY) CUNY Academc Works Inernaonal Conference on Hydronformacs 8--4 A Smulaon Based Opmal Conrol Sysem For Waer Resources Aser acasa Maro Morales-Hernández Plar Brufau Plar García-Navarro
More informationTowards New Open Economy Macroeconometrics *
Toward New Open Economy Macroeconomerc * Fabo Ghron Inernaonal Reearch Funcon Federal Reerve Bank of New York Fr draf: Augu 9, 999 Th draf: February, 2 Abrac Commen welcome I develop a model ha mprove
More informationAnalysis And Evaluation of Econometric Time Series Models: Dynamic Transfer Function Approach
1 Appeared n Proceedng of he 62 h Annual Sesson of he SLAAS (2006) pp 96. Analyss And Evaluaon of Economerc Tme Seres Models: Dynamc Transfer Funcon Approach T.M.J.A.COORAY Deparmen of Mahemacs Unversy
More informationDeveloping A Model-Based Software To Optimize Wheat Storage and Transportation System: A Real-World Application
Developng A odel-baed Sofware To Opmze Whea Sorage and Tranporaon Sem: A Real-World Applcaon Reza Zanran Farahan a,b,c*, Narn Agar c, Hoen Hoabr a and Amr Ardean Jaafar a a Logc & Suppl Chan Reearche &
More information2 Aggregate demand in partial equilibrium static framework
Unversy of Mnnesoa 8107 Macroeconomc Theory, Sprng 2009, Mn 1 Fabrzo Perr Lecure 1. Aggregaon 1 Inroducon Probably so far n he macro sequence you have deal drecly wh represenave consumers and represenave
More informationISSN MIT Publications
MIT Inernaonal Journal of Elecrcal and Insrumenaon Engneerng Vol. 1, No. 2, Aug 2011, pp 93-98 93 ISSN 2230-7656 MIT Publcaons A New Approach for Solvng Economc Load Dspach Problem Ansh Ahmad Dep. of Elecrcal
More informationUsing a Prediction Error Criterion for Model Selection in Forecasting Option Prices
Ung a Predcon Error Creron for Model Selecon n Forecang Opon Prce Savro Degannak and Evdoka Xekalak Deparmen of Sac, Ahen Unvery of Economc and Bune, 76, Paon Sree, 0434 Ahen, Greece echncal Repor no 3,
More informationComb Filters. Comb Filters
The smple flers dscussed so far are characered eher by a sngle passband and/or a sngle sopband There are applcaons where flers wh mulple passbands and sopbands are requred Thecomb fler s an example of
More information