Documentation for the TIMES Model PART II

Size: px
Start display at page:

Download "Documentation for the TIMES Model PART II"

Transcription

1 Eegy Techology Syem Aalyi Pogamme h:// Documeaio fo he TIMES Model PART II Ail 2005 Auho: Richad Loulou Ai Lehilä Ami Kaudia Uwe Reme Gay Goldei 1

2 Geeal Ioducio Thi documeaio i comoed of hee Pa. Pa I comie eigh chae coiuig a geeal deciio of he TIMES aadigm wih emhai o he model geeal ucue ad i ecoomic igificace. Pa I alo iclude a imlified mahemaical fomulaio of TIMES a chae comaig i o he MARKAL model oiig o imilaiie ad diffeece ad chae decibig ew model oio. Pa II comie 7 chae ad coiue a comeheive efeece maual ieded fo he echically mided modele o ogamme lookig fo a i-deh udeadig of he comlee model deail i aicula he elaiohi bewee he iu daa ad he model mahemaic o coemlaig makig chage o he model equaio. Pa II iclude a full deciio of he e aibue vaiable ad equaio of he TIMES model. Pa III decibe he GAMS cool aeme equied o u he TIMES model. GAMS i a modelig laguage ha alae a TIMES daabae io he Liea Pogammig maix ad he ubmi hi LP o a oimize ad geeae he eul file. I addiio o he GAMS ogam wo model ieface (VEDA-FE ad VEDA-BE) ae ued o ceae bowe ad modify he iu daa ad o exloe ad fuhe oce he model eul. The wo VEDA ieface ae decibed i deail i hei ow ue guide. 2

3 PART II: REFERENCE MANUAL 3

4 TABLE OF CONTENTS FOR PART II 1 INTRODUCTION Baic oaio ad coveio GAMS modellig laguage ad TIMES imlemeaio SETS Idexe (Oe-dimeioal e) Ue iu e Defiiio of he Refeece Eegy Syem (RES) Pocee Commodiie Defiiio of he ime ucue Time hoizo Timelice Muli-egioal model Oveview of all ue iu e Defiiio of ieal e PARAMETERS Ue iu aamee Ie- ad exaolaio of ue iu aamee Iheiace ad aggegaio of imeliced iu aamee Oveview of ue iu aamee Ieal aamee Reo aamee VARIABLES VARACT(v) VARBLND(bleo) VARCAP() VARCOMNET(c) VARCOMPRD(c) VARDNCAP(u) VARELAST(cjl) VARFLO(vc) VARIRE(vcie) VARNCAP(v) VAROBJ(y 0 ) ad elaed vaiable VAROBJR( y 0 ) INVCOST(y) INVTAXSUB(y) INVDECOM(y) FIXCOST(y) FIXTAXSUB(y) VARCOST(y)

5 ELASTCOST(y) LATEREVENUES(y) SALVAGE(y 0 ) VARSIN/SOUT(vc) Vaiable ued i Ue Coai VARUC(uc) VARUCR(uc) VARUCT(uc) VARUCRT(uc) VARUCTS(uc) VARUCRTS(uc) VARUCSU(uc) VARUCSUS(uc) VARUCRSUS(uc) VARUCRSU(uc) EQUATIONS Noaioal coveio Noaio fo ummaio Noaio fo logical codiio Uig Idicao fucio i aihmeic exeio Objecive fucio EQOBJ Ioducio ad oaio Noaio elaive o ime Ohe oaio Remide of ome echology aibue ame (each i idexed by ) Dicouig oio Comoe of he Objecive fucio Iveme co: INVCOST(y) Taxe ad ubidie o iveme Decommiioig (dimalig) caial co: COSTDECOM(y) Fixed aual co: FIXCOST(y) SURVCOST(y) Aual axe/ubidie o caaciy: FIXTAXSUB(Y) Vaiable aual co VARCOST(y) y EOH Co of demad educio ELASTCOST(y) Salvage value: SALVAGE (EOH1) Lae eveue fom edogeou commodiy ecyclig afe EOH LATEREVENUE(y) The wo dicouig mehod fo aual ayme Coai Equaio: EQACTFLO Equaio EQ(l)ACTBND Equaio: EQ(l)BLND Boud: BNDELAST Equaio: EQ(l)BNDNET/PRD Equaio: EQ(l)CAPACT Equaio: EQ(l)CPT Equaio: EQ(l)COMBAL Equaio: EQECOMPRD Equaio: EQ(l)CUMNET/PRD Equaio EQDSCNCAP Equaio: EQDSCONE Equaio: EQ(l)FLMRK Equaio: EQ(l)FLOBND Equaio: EQ(l)FLOFR Equaio elaed o exchage (EQIRE EQIREBND EQXBND) Equaio EQIRE Equaio: EQ(l)IREBND Equaio: EQ(l)XBND

6 Equaio: EQ(l)INSHR EQ(l)OUTSHR Equaio: EQPEAK Equaio: EQPTRANS Equaio: EQSTGTSS/IPS EQSRGTSS: Soage bewee imelice (icludig igh-oage device): EQSTGIPS: Soage bewee eiod Equaio: EQ(l)STGIN / EQ(l)STGOUT Ue Coai Equaio: EQ(l)UC / EQEUC Equaio: EQ(l)UCR / EQEUCR Equaio: EQ(l)UCT / EQEUCT Equaio: EQ(l)UCRT / EQEUCRT Equaio: EQ(l)UCRTS / EQEUCRTS Equaio: EQ(l)UCTS / EQEUCTS Equaio: EQ(l)UCSU / EQEUCSU Equaio: EQ(l)UCRSU / EQEUCRSU Equaio: EQ(l)UCRSUS / EQEUCRSU Equaio: EQ(l)UCSUS / EQEUCSUS Equaio: EQ(l)UCSU / EQEUCSU Equaio: EQ(l)UCRSU / EQEUCRSU Equaio: EQ(l)UCRSUS / EQEUCRSU Equaio: EQ(l)UCSUS / EQEUCSUS THE ENDOGENOUS TECHNOLOGICAL LEARNING (ETL) OPTION Se Swiche ad Paamee Vaiable VARCCAP() VARCCOST() VARDELTA(k) VARIC() VARLAMBD(k) Equaio EQCC() EQCLU() EQCOS() EQCUINV() EQDEL() EQEXPE1(k) EQEXPE2(k) EQIC1() EQIC2() EQLA1(k) EQLA2(k) EQOBJSAL(cu) EQOBJINV(cu) THE TIMES CLIMATE MODULE Fomulaio of he TIMES Climae Module Aoach ake Coceaio (accumulaio of CO2) Radiaive focig Temeaue iceae Iu aamee of he Climae Module Climae elaed Vaiable VARCO2TOT() VARCO2ATM() VARCO2UP() VARCO2LOW()

7 7.4 Climae Equaio Equaio: EQCO2TOT Equaio: EQCO2ATM Equaio: EQCO2UP Equaio: EQCO2LOW Equaio: EQMXCONC Reoig Paamee DTFORC DTATM DTLOW Defaul value of he climae aamee GAMS imlemeaio Secificaio of aamee Climae elaed Vaiable Equaio Examle of ue Exoig eul o VEDA Refeece fo chae

8 1 Ioducio The uoe of he Refeece Maual i o lay ou he full deail of he TIMES model icludig daa ecificaio ieal daa ucue ad mahemaical fomulaio of he model Liea Pogam (LP) fomulaio a well a he Mixed Iege Pogammig (MIP) fomulaio equied by ome of i oio. A uch i ovide he TIMES modelle/ogamme wih ufficiely deailed ifomaio o fully udead he aue ad uoe of he daa comoe model equaio ad vaiable. A olid udeadig of he maeial i hi Maual i a eceay eequiie fo ayoe coideig makig ogammig chage i he TIMES ouce code. The Refeece Maual i ogaized a follow: Chae 1 Baic oaio ad coveio: lay he goudwok fo udeadig he e of he maeial i he Refeece Maual; Chae 2 Se: exlai he meaig ad ole of vaiou e ha ideify how he model comoe ae goued accodig o hei aue (e.g. demad device owe la eegy caie ec.) i a TIMES model; Chae 3 Paamee: elaboae he deail elaed o he ue-ovided umeical daa a well a he ieally couced daa ucue ued by he model geeao (ad eo wie) o deive he coefficie of he LP maix (ad eae he eul fo aalyi); Chae 4 Vaiable: defie each vaiable ha may aea i he maix boh exlaiig i aue ad idicaig how if fi io he maix ucue; Chae 5 Equaio: ae each equaio i he model boh exlaiig i ole ad ovidig i exlici mahemaical fomulaio; Chae 6 The Ue Coai: exlai he famewok ha may be emloyed by modelle o fomulae addiioal liea coai which ae o a of he geeic coai e of TIMES wihou havig o bohe wih ay GAMS ogammig; Chae 7 The Lumy Iveme faciliy ad Chae 8 The Edogeou Techological Leaig caabiliy. 1.1 Baic oaio ad coveio To ai he eade he followig coveio ae emloyed coiely houghou hi chae: Se ad hei aociaed idex ame ae i lowe ad bold cae e.g. com i he e of all commodiie; Lieal exlicily defied i he code ae i ue cae wihi igle quoe e.g. UP fo ue boud; Paamee ad cala (coa i.e. u-idexed aamee) ae i ue cae e.g. NCAPAF fo he availabiliy faco of a echology; Vaiable ae i ue cae wih a efix of VAR e.g. VARACT coeod o he aciviy level of a echology. Equaio ae i ue cae wih a efix of EQ o EQ(l) wih he laceholde (l) deoig he equaio ye (l=e fo a ic equaliy l=l fo a iequaliy wih he lef 8

9 had ide em beig malle o equal he igh had ide em ad l=g fo a iequaliy wih he lef had ide em beig geae o equal he igh had ide em)e.g. EQCOMBAL i he commodiy balace coai ad 1.2 GAMS modellig laguage ad TIMES imlemeaio TIMES coi of geeic vaiable ad equaio couced fom he ecificaio of e ad aamee value deicig a eegy yem fo each diic egio i a model. To couc a TIMES model a eoceo fi alae all daa defied by he modelle io ecial ieal daa ucue eeeig he coefficie of he TIMES maix alied o each vaiable of Chae 4 fo each equaio of Chae 5 i which he vaiable may aea. Thi e i called Maix Geeaio. Oce he model i olved (oimied) a Reo Wie aemble he eul of he u fo aalyi by he modelle. The maix geeaio eo wie ad cool file ae wie i GAMS 1 (he Geeal Algebaic Modellig Syem) a oweful high-level laguage ecifically deiged o faciliae he oce of buildig lagecale oimiaio model. GAMS accomlihe hi by elyig heavily o he coce of e comoud idexed aamee dyamic looig ad codiioal cool vaiable ad equaio. Thu hee i vey a og yegy bewee he hiloohy of GAMS ad he oveall coce of he RES ecificaio embodied i TIMES makig GAMS vey well uied o he TIMES aadigm. Fuhemoe by aue of i udelyig deig hiloohy he GAMS code i vey imila o he mahemaical deciio of he equaio ovided i Chae 5. Thu he aoach ake o imleme a TIMES model i o maage he iu daa by mea of a (ahe comlex) eoceo ha hadle he eceay exceio ha eed o be ake io coideaio o oely couc he maix coefficie i a fom eady o be alied o he aoiae vaiable i he eecive equaio. GAMS alo iegae eamlely wih a wide age of commecially available oimie ha ae chaged wih he ak of olvig he acual TIMES liea (LP) o mixed iege (MIP) oblem ha eee he deied model. Thi e i called he Solve o Oimiaio e. CPLEX o XPRESS ae he oimie mo ofe emloyed o olve he TIMES LP ad MIP fomulaio. The adad TIMES fomulaio ha oioal feaue uch a lumy iveme ad edogeou echology leaig. I addiio a modelle exeieced i GAMS ogammig ad he deail of he TIMES imlemeaio ca defie addiioal equaio module o eo ouie module baed o a exeio mechaim which allow he likage of hee module o he adad TIMES code i a flexible way (ee PART III chae 3) To build u ad aalye a TIMES model eveal ofwae ool have bee develoed i he a o ae cuely ude develome o ha he modelle doe o eed o ovide he iu ifomaio eeded o build a TIMES model diecly i GAMS. Thee ool ae he model ieface VEDA-FE ANSWER-TIMES a well a he eoig ad aalyig ool VEDA-BE. 1 GAMS A Ue Guide A. Booke D. Kedick A. Meeau R. Rama GAMS Develome Cooaio Decembe

10 2 Se Se ae ued i TIMES o gou eleme o combiaio of eleme wih he uoe of ecifyig qualiaive chaaceiic of he eegy yem. Oe ca diiguih bewee oedimeioal ad muli-dimeioal e. The fome e coai igle eleme e.g. he e c coai all ocee of he model while he eleme of muli-dimeioal e ae a combiaio of oe-dimeioal e. A examle fo a muli-dimeioal e i he e o which ecifie fo a oce he commodiie eeig ad leavig ha oce. Two ye of e ae emloyed i he TIMES famewok: ue iu e ad ieal e. Ue iu e ae ceaed by he ue ad ued o decibe qualiaive ifomaio ad chaaceiic of he deiced eegy yem. Oe ca diiguih he followig fucio aociaed wih ue iu e: defiiio of he eleme o buildig block of he eegy yem model (i.e. egio ocee commodiie) defiiio of he ime hoizo ad he ub-aual ime eoluio defiiio of ecial chaaceiic of he eleme of he eegy yem. I addiio o hee ue e TIMES alo geeae i ow ieal e. Ieal e eve o boh eue oe exceio hadlig (e.g. fom wha dae i a echology available o i which ime-lice i a echology emied o oeae) a well a omeime ju o imove he efomace o mooh he comlexiy of he acual model code. I he followig ecio he ue iu e ad he ieal e will be eeed. A ecial ye of e i a oe-dimeioal e alo called idex which i eeded o build mulidimeioal e o aamee. A he highe level of he oe-dimeioal e ae he mae o domai e ha defie he comeheive li of eleme (e.g. he mai buildig block of he efeece eegy yem uch a he ocee ad commodiie i all egio) emied a all ohe level wih which GAMS efom comlee domai checkig helig o auomaically eue he coece of e defiiio (fo iace if he oce ame ued i a aamee i o elled coecly GAMS will iue a waig). Theefoe befoe elaboaig o he vaiou e he idexe ued i TIMES ae dicued. 2.1 Idexe (Oe-dimeioal e) Idexe (alo called oe-dimeioal e) coai i mo cae he diffee eleme of he eegy model. A li of all idexe ued i TIMES i give i Table 2. Examle of idexe ae he e c coaiig all ocee he e c coaiig all commodiie o he e alleg coaiig all egio of he model. Some of he oe-dimeioal e ae ube of aohe oe-dimeioal e e.g. he e comiig he o-called ieal model egio i a ube of he e alleg which i addiio alo coai he o-called exeal model egio 2. To exe ha he e deed o he e alleg he mae e alleg i u i backe afe he e ame : (all). The e cg comie all commodiy gou 3. Each commodiy c i coideed a a commodiy gou wih oly oe eleme he commodiy ielf. Thu he commodiy e c i a ube of he commodiy gou e cg. Aa fom idexe ha ae ude ue cool ome idexe have fixed eleme o eve a idicao wihi e ad aamee ad hould o be modified by he ue (Table 1). The oly exceio o hi ule i he e cg: while he oce gou IRE NST PRV 2 The meaig ad he ole of ieal ad exeal egio i dicued i Secio See Secio fo a moe i-deh eame of commodiy gou. 10

11 PRW STG ad STK ae ued wihi he code ad mu o be deleed he ohe oce gou may be modified by he ue. Table 1: Se wih fixed eleme Se/Idex ame Deciio bd(lim) Idex of boud ye; ube of he e lim havig he ieally fixed eleme LO UP FX. comye Idicao of commodiy ye; iiialized o he eleme DEM (demad) NRG (eegy) MAT (maeial) ENV (eviome) FIN (fiacial) bu he ue ca defie ay li fo comye i MAPLIST.DEF wih he exceio of he edefied eleme DEM ENV FIN MAT NRG. lim Idex of limi ye; ieally fixed o he eleme LO UP FX N. ie Exo/imo exchage idex; ieally fixed o he wo eleme: IMP adig fo imo ad EXP adig fo exo. io Iu/Ouu idex; ieally fixed eleme: IN OUT ; ued i combiaio wih ocee ad commodiie a idicao whehe a commodiy ee o leave a oce. cg Li of oce gou; ieally eablihed i MAPLIST:DEF a: CHP: combied hea ad owe la DISTR: diibuio oce DMD: demad device ELE: eleciciy oducig echology excludig CHP HPL: hea la MISC: micellaeou PRE: echology wih eegy ouu o fallig i he gou of he ohe eegy echologie REF: efiey oce RENEW: eewable eegy echology XTRACT: exacio oce. The ue may adju hi li o ay dijoi gou deied. The followig gou ae equied by he model heefoe mu o be deleed by he ue: IRE: ie-egioal exchage oce PRV: echology wih maeial ouu meaued i volume ui PRW: echology wih maeial ouu meaued i weigh ui NST: igh (off-eak) oage oce STG: oage oce STK: ockilig oce. lvl Idex of imelice level; ieally fixed o he eleme ANNUAL SEASON WEEKLY DAYNITE. ucgye Idex of ieally fixed key ye of vaiable: = ACT CAP COMPRD COMCON FLO IRE NCAP ued i aociaio wih he ue coai. ucame Li of ieally fixed idicao fo aibue able o be efeeced a coefficie i ue coai (e.g. he flow vaiable may be mulilied by he aibue FLOCOST i a ue coai if deied): = ACTCOST ACTBNDUP ACTBNDLO ACTBNDFX CAPBNDUP CAPBNDLO CAPBNDFX GROWTH FLOCOST FLODELIV FLOSUB FLOTAX NCAPCOST NCAPITAX NCAPISUB. 11

12 Table 2: Idexe i TIMES Idex 4 Aliae 5 Relaed Idexe 6 age Deciio Idex fo age (umbe of yea ice iallaio) io a aamee haig cuve; defaul eleme all alleg All ieal ad exeal egio. bd bdye lim Idex of boud ye; ube of lim havig he ieally fixed eleme LO UP FX. c cg comy e com com1 com2 com3 comg cg1 cg2 cg3 cg4 cg c Ue defied 7 li of all commodiie i all egio; ube of cg. Ue defied li of all commodiie ad commodiy gou i all egio 8 ; each commodiy ielf i coideed a commodiy gou; iiial eleme ae he membe of comye. Idicao of commodiy ye; iiialized o he eleme DEM (demad) NRG (eegy) MAT (maeial) ENV (eviome) FIN (fiacial) bu he ue ca defie ay li fo comye i MAPLIST.DEF wih he exceio of he edefied eleme DEM ENV FIN MAT NRG. cu cu Ue defied li of cuecy ui. daayea y Yea fo which model iu daa ae ecified. ie imex Exo/imo exchage idicao; ieally fixed = EXP fo exo ad IMP fo imo. io iou Iu/Ouu idicao fo defiig whehe a commodiy flow ee o leave a oce; ieally fixed = IN fo ee ad OUT fo leave. j k Idicao fo elaic demad e ad equece umbe of he hae/muli cuve; defaul eleme Idex fo kik oi i ETL fomulaio; cuely limied o 1-6 {ca be exeded i <cae>.u file by icludig SET KP / 1* /; fo -kik oi. lim limye l bd Idex of limi ye; ieally fixed = LO UP ll FX ad N. c Ue defied li of all ocee i all egio 9. 4 Thi colum coai he ame of he idexe a ued i hi docume. 5 Fo ogammig eao aleaive ame (aliae) may exi fo ome idexe. Thi ifomaio i oly eleva fo hoe ue who ae ieeed i gaiig a udeadig of he udelyig GAMS code. 6 Thi colum efe o oible elaed idexe e.g. he idex c i a ube of he idex cg. 7 VEDA comile he comlee li fom he uio of he commodiie defied i each egio. 8 VEDA comlie he comlee li fom he uio of he commodiy gou defied i each egio. 9 VEDA comlie he comlee li fom he uio of he ocee defied i each egio. 12

13 Idex 4 Aliae 5 Relaed Idexe 6 Deciio ayea y modlyeay Yea fo which a iveme ae ecified; ayea mu be befoe he begiig of he fi eiod. cg Li of oce gou; ieally eablihed i MAPLIST:DEF a: CHP: DISTR: DMD: ELE: HPL: MISC: PRE: combied hea ad owe la diibuio oce demad device eleciciy oducig echology excludig CHP hea la micellaeou echology wih eegy ouu o fallig i he gou of he ohe eegy echologie efiey oce REF: RENEW: eewable eegy echology XTRACT: exacio oce. The ue may adju hi li o ay dijoi gou deied. The followig gou ae equied by he model ad heefoe mu o be deleed by he ue: IRE: ie-egioal exchage oce PRV: echology wih maeial ouu meaued i volume ui PRW: echology wih maeial ouu meaued i weigh ui NST: igh (off-eak) oage oce STG: oage oce STK: ockilig oce. eg all Exlici egio wihi he aea of udy. all Timelice diviio of a yea a ay of he lvl level. 2 l mileoy y Reeeaive yea fo he model eiod. eg Techologie modelled wih edogeou echology leaig. lvl Timelice level idicao; ieally fixed = ANNUAL SEASON WEEKLY DAYNITE. u ui uicom uica Li of all ui; maiaied i he file UNITS.DEF. ucgy e uc uiac Fixed ieal li of he key ye of vaiable: fixed = ACT CAP COMPRD COMCON FLO IRE NCAP. Ue ecified uique idicao fo a ue coai. 13

14 Idex 4 Aliae 5 Relaed Idexe 6 ucame ui Deciio The li of idicao aociaed wih vaiou aibue ha ca be efeeced i ue coai o be alied whe deivig a coefficie (e.g. he flow vaiable may be mulilied by he aibue FLOCOST o eee exediue aociaed wih aid flow i a ue coai if deied): = ACTCOST ACTBNDUP ACTBNDLO ACTBNDFX CAPBNDUP CAPBNDLO CAPBNDFX GROWTH FLOCOST FLODELIV FLOSUB FLOTAX NCAPCOST NCAPITAX NCAPISUB. Li of caaciy block ha ca be added i lumy iveme oio; defaul eleme 0-100; he eleme 0 decibe he cae whe o caaciy i added. uiac u Li of aciviy ui; maiaied i he file UNITS.DEF. uica u Li of caaciy ui; maiaied i he file UNITS.DEF. uico m u Li of commodiy ui; maiaied i he file UNITS.DEF. v modlyea ayea Uio of he e ayea ad coeodig o all modellig eiod. y allyea k ll daayea ayea modlyea mileoy Yea ha ca be ued i he model; defaul age ; ude ue cool by he dolla cool aamee $SET BOTIME yyyy ad $SET EOTIME i he <cae>.run file. 14

15 2.2 Ue iu e The ue iu e coai he fudameal ifomaio egadig he ucue ad he chaaceiic of he udelyig eegy yem model. The ue iu e ca be goued accodig o he ye of ifomaio elaed o hem: Oe dimeioal e defiig he comoe of he eegy yem: egio commodiie ocee; Se defiig he Refeece Eegy Syem (RES) wihi each egio; Se defiig he ie-coecio (ade) bewee egio; Se defiig he ime ucue of he model; Se defiig vaiou oeie of ocee o commodiie. The fomulaio of ue coai alo ue e o ecify he ye ad he feaue of a coai. The ucue ad he iu ifomaio equied o couc a ue coai i coveed i deail i Chae 5 ad heefoe will o be eeed hee. I he followig ubecio fi he e elaed o he defiiio of he RES will be decibed (ubecio 2.2.1) he he e elaed o he ime hoizo ad he ub-aual eeeaio of he eegy yem will be eeed (ubecio 2.2.2). The mechaim of defiig ade bewee egio of a muli-egioal model i dicued i ubecio Fially a oveview of all oible ue iu e i give i ubecio Defiiio of he Refeece Eegy Syem (RES) A TIMES model i ucued by egio (all). Oe ca diiguih bewee exeal egio ad ieal egio. The ieal egio () coeod o egio wihi he aea of udy ad fo which a RES ha bee defied by he ue. Each ieal egio may coai ocee ad commodiie o deic a eegy yem wheea exeal egio eve oly a oigi of commodiie (e.g. fo imo of imay eegy eouce o fo he imo of eegy caie) o a deiaio fo he exo of commodiie. A egio i defied a a ieal egio by uig i i he ieal egio e () which i a ube of he e of all egio all. A exeal egio eed o exlici defiiio all egio ha ae membe of he e all bu o membe of ae exeal egio. A TIMES model mu coi of a lea oe ieal egio he umbe of exeal egio i abiay. The mai buildig block of he RES ae ocee () ad commodiie (c) which ae coeced by commodiy flow o fom a ewok. A examle of a RES wih oe ieal egio (UTOPIA) ad wo exeal egio (IMPEXP MINRNW) i give i Figue 1. All comoe of he eegy yem a well a ealy he eie iu ifomaio ae ideified by a egio idex. I i heefoe oible o ue he ame oce ame i diffee egio wih diffee umeical daa (ad deciio if deied) o eve comleely diffee commodiie aociaed wih he oce. 15

16 Exeal egio Ieal egio UTOPIA IMPEXP OIL HYD URN FEQ HCO GSL DSL ELC RH RL TX NOX E01 E51 RHE E21 SRE E31 E70 RL1 RHO TXD MINRNW TXE TXG Figue 1: Examle of ieal ad exeal egio i TIMES Pocee A oce may eee a idividual la e.g. a ecific exiig uclea owe la o a geeic echology e.g. he coal-fied IGCC echology. TIMES diiguihe hee mai ye of ocee: Sadad ocee; Ie-egioal exchage ocee ad Soage ocee Sadad ocee The o-called adad ocee ca be ued o model he majoiy of he eegy echologie e.g. codeig owe la hea la CHP la demad device uch a boile coal exacio ocee ec. Sadad ocee ca be claified io he followig gou: PRE fo geeic eegy ocee; PRW fo maeial oceig echologie (by weigh); PRV fo maeial oceig echologie (by volume); REF fo efiey ocee; ELE fo eleciciy geeaio echologie; HPL fo hea geeaio echologie; CHP fo combied hea ad owe la; DMD fo demad device; DISTR fo diibuio yem; MISC fo micellaeou ocee 16

17 via he e cma(cg). Thi gouig doe o affec he oeie of he adad ocee 10 o he maix bu i ieded fo eoig uoe. The e i maiaied i he MAPLIST.DEF file ad may be adjued by ue io ay li of dijoi echology gou of iee wih ome eicio a oed i Table 1. The oology of a adad oce i ecified by he e o(cio) of all quadule uch ha he oce i egio i coumig (io = IN ) o oducig (io = OUT ) commodiy c. Uually fo each ey of he oology e o a flow vaiable (ee VARFLO i Chae 4) will be ceaed. Whe he o-called educio algoihm i acivaed ome flow vaiable may be elimiaed ad elaced by ohe vaiable (ee PART III chae 4). The aciviy vaiable (VARACT) of a adad oce i equal o he um of oe o eveal commodiy flow o eihe he iu o he ouu ide of a oce. The aciviy of a oce i limied by he available caaciy o ha he aciviy vaiable eablihe a lik bewee he ialled caaciy of a oce ad he maximum oible commodiy flow eeig o leavig he oce duig a yea o a ubdiviio of a yea. The commodiy flow ha defie he oce aciviy ae ecified by he e cacu(cgu) whee he commodiy idex cg may be a igle commodiy o a ue-defied commodiy gou. The commodiy gou defiig he aciviy of a oce i alo called Pimay Commodiy Gou (PCG). Oil OIL Aciviy i PJ Dieel Commodiy gou CGSRE DSL GSL Gaolie Refiey SRE All commodiie i PJ Defiiio of commodiy gou Defiiio of oce aciviy COMGMAP(cgc) = {UTOPIA.CGSRE.DSL UTOPIA.CGSRE.GSL} PRCCG(cg) = {UTOPIA.SRE.CGSRE} PRCACTUNT(cgu) = {UTOPIA.SRE.CGSRE.PJ} Figue 2: Examle of he defiiio of a commodiy gou ad of he aciviy of a oce Ue-defied commodiy gou ae ecified by mea of he e comgma(cgc) which idicae he commodiie (c) belogig o he gou (cg). I ode o aly a uedefied commodiy gou i coecio wih a oce (o oly fo he defiiio of he oce aciviy bu alo fo ohe uoe e.g. i he afomaio equaio EQPTRANS) oe ha o aig he commodiy gou cg o he oce by ecifyig he ccg(cg). Thu i i oible o ue he ame commodiy gou ame fo diffee ocee. A examle fo he defiiio of he aciviy of a oce i how i Figue 2. I ode o defie he aciviy of he oce SRE a he um of he wo ouu flow of gaolie (GSL) ad dieel (DSL) oe ha o defie a commodiy gou called CGSRE coaiig hee wo commodiie. The ame of he commodiy gou ca be abiaily choe by he modelle. 10 The oly exceio ae maeial oceig echologie of ye PRW o PRV whee he gouig may affec he ceaio of he ieal e cg (ee Table 4). 17

18 I addiio o he aciviy of a oce oe ha o defie he caaciy ui of he oce. Thi i doe by mea of he e ccau(cgu) whee he idex cg deoe he imay commodiy gou. I he examle i Figue 3 he caaciy of he efiey oce i defied i moe/a (megaoe oil equivale). Sice he caaciy ad aciviy ui ae diffee (moe fo he caaciy ad PJ fo he aciviy) he ue ha o uly he coveio faco fom he eegy ui embedded i he caaciy ui o he aciviy ui. Thi i doe by ecifyig he aamee ccaac(). I he examle ccaac ha he value Oil OIL Aciviy i PJ Dieel Commodiy gou CGSRE DSL GSL Gaolie Refiey SRE All commodiie i PJ Caaciy i moe/a Defiiio of caaciy ui Coveio faco fom caaciy o aciviy ui PRCCAPUNT(cgu) = {UTOPIA.SRE.CGSRE.MTOE} PRCCAPACT UTOPIASRE = Figue 3: Examle of he defiiio of he caaciy ui I migh occu ha he ui i which he commodiy(ie) of he imay commodiy gou ae meaued i diffee fom he aciviy ui. A examle i how i Figue 4. The aciviy of he ao echology CAR i defied by commodiy TX1 which i meaued i aege kilomee PKM. The aciviy of he oce i howeve defied i vehicle kilomee VKM while he caaciy of he oce CAR i defied a umbe of ca NOC. DSL Aciviy i vehicle kilomee VKM Ca CAR TX1 Commodiy ui Paege kilomee PKM Caaciy i # of ca NOC Defiiio of oce aciviy PRCACTUNT(cgu) = {UTOPIA.CAR.TX1.PKM} Defiiio of caaciy ui PRCCAPUNT(cgu) = {UTOPIA.CAR.TX1.NOC} Coveio faco fom caaciy o aciviy ui PRCCAPACT UTOPIA CAR = Coveio faco fom aciviy ui o commodiy ui PRCACTFLO UTOPIA 2000CARTX1 = 1.5 Figue 4: Examle of diffee aciviy ad commodiy ui 18

19 The coveio faco fom caaciy o aciviy ui ccaac decibe he aveage mileage of a ca e yea. The oce aamee cacflo(ycg) coai he coveio faco fom he aciviy ui o he commodiy ui of he imay commodiy gou. I he examle hi faco coeod o he aveage umbe of eo e ca (1.5) Ie-egioal exchage ocee Ie-egioal exchage (IRE) ocee ae ued fo adig commodiie bewee egio. They ae eeded fo likig ieal egio wih exeal egio a well a fo modellig ade bewee ieal egio. A oce i ecified a a ie-egioal exchage oce by ecifyig i a a membe of he e cma( IRE ). If he exchage oce i coecig ieal egio hi e ey i equied fo each of he ieal egio adig wih egio. The oology of a ie-egioal exchage oce i defied by he e oie(allegcomallc) aig ha he commodiy com i egio alleg i exoed o he egio all (he aded commodiy may have a diffee ame c i egio all ha i egio alleg). Fo examle he oology of he exo of he commodiy eleciciy (ELCF) fom Face (FRA) o Gemay (GER) whee he commodiy i called ELCG via he exchage oce (HVGRID) i modelled by he oie ey: oie( FRA ELCF GER ELCG HVGRID ). The fi ai of egio ad commodiy ( FRA ELCF ) deoe he oigi ad he ame of he aded commodiy while he ecod ai ( GER ELCG ) deoe he deiaio. The ame of he aded commodiy ca be diffee i boh egio hee ELCF i Face ad ELCG i Gemay deedig o he choe commodiy ame i boh egio. A wih adad ocee he aciviy defiiio e cacu(cgu) ha o be ecified fo a exchage oce belogig o each ieal egio. The ecial feaue elaed o ieegioal exchage ocee ae decibed i ubecio Soage ocee Soage ocee ae ued o oe a commodiy eihe bewee eiod o bewee imelice. A oce () i ecified o be a ie-eiod oage (IPS) oce fo commodiy ( c ) by icludig i a a membe of he e cgi(c). I a imila way a oce i chaaceied a a geeal imelice oage (TSS) by icluio i he e cg(c). A ecial cae of imelice oage i a o-called igh-oage device (NST) whee he commodiy fo chagig ad he oe fo dichagig he oage ae diffee. A examle fo a igh oage device i a elecic heaig echology which i chaged duig he igh uig eleciciy ad oduce hea duig he day. Icludig a oce i he e c() idicae ha i i a igh oage device which i chaged i imelice(). Moe ha oe imelice ca be ecified a chagig imelice he oecified imelice ae aumed o be dichagig imelice. The chagig ad dichagig commodiy of a igh oage device ae ecified by he oology e (o). I hould be oed ha fo ie-eiod oage ad geeal imelice oage ocee he commodiy eeig ad leavig he oage i ecified by he e cgi(c) ad cg(c) eecively. Ohe commodiy flow ae o emied i combiaio wih hee wo oage ye ad hece he oology e o i o alicable o hee oage. A fo adad ocee he flow ha defie he aciviy of a oage oce ae ideified by ovidig he e cacu(c) ey. I coa o adad ocee he aciviy of a oage oce i howeve ieeed a he amou of he commodiy beig oed i he oage oce. Accodigly he caaciy of a oage oce decibe he maximum commodiy amou ha ca be ke i oage. 19

20 Baed o he oage chaaceizaio give by cgi cg o c fo a oce ieally a cma( STG ) ey i geeaed o u he oce i he gou of he oage ocee. A fuhe cma ey i ceaed o ecify he ye of oage ( STK fo ie-oeiod oage STS fo ime-lice oage ad NST fo a igh-oage device) Commodiie A meioed befoe he e of commodiie ( c ) i a ube of he commodiy gou e (cg). A commodiy i TIMES i chaaceied by i ye which may be a eegy caie ( NRG ) a maeial ( MAT ) a emiio --o eviomeal imac ( ENV ) a demad commodiy ( DEM ) o a fiacial eouce ( FIN ). The commodiy ye i idicaed by membehi i he commodiy ye maig e (comma(comyec)). The commodiy ye affec he defaul ee of he commodiy balace equaio. Fo NRG ENV ad DEM he commodiy oducio i omally geae ha o equal o coumio while fo MAT ad FIN he defaul commodiy balace coai i geeaed a a equaliy. The ye of he commodiy balace ca be modified by he ue fo idividual commodiie by mea of he commodiy limi e (comlim(clim)). The ui i which a commodiy i meaued i idicaed by he commodiy ui e (comui(cuicom)). The ue hould oe ha wihi he GAMS code of TIMES o ui coveio e.g. of imo ice ake lace whe he commodiy ui i chaged fom oe ui o aohe oe. Theefoe he oe hadlig of he ui i eiely he eoibiliy of he ue (o he ue ieface) Defiiio of he ime ucue Time hoizo The ime hoizo fo which he eegy yem i aalyed may age fom oe yea o may decade. The ime hoizo i uually li io eveal eiod which ae eeeed by ocalled mileoe yea ((allyea) o mileoy(allyea) ee Figue 5). Each mileoe yea eee a oi i ime whee deciio may be ake by he model e.g. iallaio of ew caaciy o chage i he eegy flow. The aciviy ad flow vaiable ued i TIMES may heefoe be coideed a aveage value ove a eiod. The hoe oible duaio of a eiod i oe yea. Howeve i ode o kee he umbe of vaiable ad equaio a a ize ha ca be oceed by he cue oluio ad eoig ofwae a well a comue hadwae a eiod uually comie eveal yea. The duaio of he eiod do o have o be equal o ha i i oible ha he fi eiod which uually eee he a ad i ued o calibae he model o hioic daa ha a legh of oe yea while he followig eiod may have loge duaio. Thu i TIMES boh he umbe of eiod ad he duaio of each eiod ae fully ude ue cool. The begiig yea of a eiod B(allyea) i edig yea E(allyea) i middle yea M(allyea) ad i duaio D(allyea) have o be ecified a iu aamee by he ue (ee Table 12 i ubecio 3.1.3) exce fo a yea whee B=E=mileoy. To decibe caaciy iallaio ha ook lace befoe he begiig of he model hoizo ad ill exi duig he modelig hoizo TIMES ue addiioal yea he ocalled a yea (ayea(allyea)) which ideify he coucio comleio yea of he aleady exiig echologie. The amou of caaciy ha ha bee ialled i a ayea i ecified by he aamee NCAPPASTI(allyea) alo called a iveme. Fo a oce a abiay umbe of a iveme may be ecified o eflec he age ucue i he exiig caaciy ock. The uio of he e mileoy ad ayea i called modelyea (o v). The yea fo which iu daa i ovided by he ue ae called daayea (daayea(allyea)). The daayea do o have o coicide wih modelyea ice he eoceo will ieolae o exaolae he daa ieally o he modelyea. All 20

Valuing Bonds and Stocks

Valuing Bonds and Stocks Leaig Objecives 5- Valuig Bods ad Socks 5 Copoae Fiacial Maageme e Emey Fiey Sowe 5- Udesad ypical feaues of bods & socks. Lea how o obai ifomaio abou bods ad socks. Ideify he mai facos ha affec he value

More information

Derivative Securities: Lecture 7 Further applications of Black-Scholes and Arbitrage Pricing Theory. Sources: J. Hull Avellaneda and Laurence

Derivative Securities: Lecture 7 Further applications of Black-Scholes and Arbitrage Pricing Theory. Sources: J. Hull Avellaneda and Laurence Deivaive ecuiies: Lecue 7 uhe applicaios o Black-choles ad Abiage Picig heoy ouces: J. Hull Avellaeda ad Lauece Black s omula omeimes is easie o hik i ems o owad pices. Recallig ha i Black-choles imilaly

More information

Economic Papers Series

Economic Papers Series Pape No. ( Ecooic Pape Seie Macoecooic Model of Public Deb Sevici Capaciy ad Deb Maaee Deb i o a ae of coce a lo a i i aaeable ad uaiable. Deb aaee i he poce by which he ovee acquie ad ue he deb effecively

More information

Time value of money Interest formulas Project evaluations Inflation and CPI Financial risk and financing

Time value of money Interest formulas Project evaluations Inflation and CPI Financial risk and financing 2YHUYLHZ )LQDQLDO$QDO\VLV 3ULHU Hioshi Sakamoo Humphey Isiue of ublic Affais Uivesiy of Miesoa Time value of moey Iees fomulas ojec evaluaios Iflaio ad CI iacial isk ad fiacig A5721 Moey - 1 A5721 Moey

More information

Long-Term Care (LTC) Insurance Application I-Hsin Li

Long-Term Care (LTC) Insurance Application I-Hsin Li Log-Tem Cae (LTC Isuae Aliaio I-Hsi Li Eoomis Deame Idiaa Uivesiy Wylie Hall 0 00 S. Woodlaw Bloomigo, IN 0 ili@idiaa.edu Absa Due o a agig oulaio ad he aid gowh of log-em ae (LTC exeses, i is imoa o udesad

More information

The Use of Credit Bureau Information in the Estimation of Appropriate Capital and Provisioning Requirements. Michael Falkenheim and Andrew Powell

The Use of Credit Bureau Information in the Estimation of Appropriate Capital and Provisioning Requirements. Michael Falkenheim and Andrew Powell he Use of Cedi ueau Ifomaio i he simaio of ppopiae Capial ad Povisioig Requiemes Michael Falkeheim ad dew Powell Ceal ak of geia Pepaed fo he Wold ak Poec o Cedi ueaus. Pelimiay Commes Welcome he auhos

More information

Highly Reliable Two-Dimensional RAID Arrays for Archival Storage

Highly Reliable Two-Dimensional RAID Arrays for Archival Storage Highly Reliable Two-Dimeioal RAID Array for Archival Sorage Jeha-Fraçoi Pâri Comuer Sciece De. Uiveriy of Houo Houo, TX 77- jari@uh.edu Thoma Schwarz, S. J. Deo. de Iformáica y Ciecia de la Comuació U.

More information

THE PRINCIPLE OF THE ACTIVE JMC SCATTERER. Seppo Uosukainen

THE PRINCIPLE OF THE ACTIVE JMC SCATTERER. Seppo Uosukainen THE PRINCIPLE OF THE ACTIVE JC SCATTERER Seppo Uoukaie VTT Buildig ad Tapot Ai Hadlig Techology ad Acoutic P. O. Bo 1803, FIN 02044 VTT, Filad Seppo.Uoukaie@vtt.fi ABSTRACT The piciple of fomulatig the

More information

1. Time Value of Money 3 2. Discounted Cash Flow 35 3. Statistics and Market Returns 49 4. Probabilities 81 5. Key Formulas 109

1. Time Value of Money 3 2. Discounted Cash Flow 35 3. Statistics and Market Returns 49 4. Probabilities 81 5. Key Formulas 109 1. Time Value of Money 3 2. Discouned Cash Flow 35 3. Saisics and Make Reuns 49 4. Pobabiliies 81 5. Key Fomulas 109 Candidae Noe: This is a lenghy Sudy Session ha, along wih Sudy Session 3, you should

More information

MFGsoft. Software User Manual

MFGsoft. Software User Manual ISSN 60-0956 MFGsof Muli-Fucioal GPS/Galileo Sofwae Sofwae Use Maual Vesio of 004 Guochag Xu GeoFoschugsZeum Posdam Depame : Geodesy ad Remoe Sesig Telegafebeg A7, 4473 Posdam, Gemay Ocobe 004 Scieific

More information

Introduction to Hypothesis Testing

Introduction to Hypothesis Testing Iroducio o Hyohei Teig Iroducio o Hyohei Teig Scieific Mehod. Sae a reearch hyohei or oe a queio.. Gaher daa or evidece (obervaioal or eerimeal) o awer he queio. 3. Summarize daa ad e he hyohei. 4. Draw

More information

HFCC Math Lab Intermediate Algebra - 13 SOLVING RATE-TIME-DISTANCE PROBLEMS

HFCC Math Lab Intermediate Algebra - 13 SOLVING RATE-TIME-DISTANCE PROBLEMS HFCC Mah Lab Inemeiae Algeba - 3 SOLVING RATE-TIME-DISTANCE PROBLEMS The vaiables involve in a moion poblem ae isance (), ae (), an ime (). These vaiables ae elae by he equaion, which can be solve fo any

More information

Generalized Difference Sequence Space On Seminormed Space By Orlicz Function

Generalized Difference Sequence Space On Seminormed Space By Orlicz Function Ieaoa Joa of Scece ad Eee Reeach IJSER Vo Ie Decembe -4 5687 568X Geeazed Dffeece Seece Sace O Semomed Sace B Ocz Fco A.Sahaaa Aa ofeo G Ie of TechooCombaoeIda. Abac I h aewe defe he eece ace o emomed

More information

CHAPTER 22 ASSET BASED FINANCING: LEASE, HIRE PURCHASE AND PROJECT FINANCING

CHAPTER 22 ASSET BASED FINANCING: LEASE, HIRE PURCHASE AND PROJECT FINANCING CHAPTER 22 ASSET BASED FINANCING: LEASE, HIRE PURCHASE AND PROJECT FINANCING Q.1 Defie a lease. How does i differ from a hire purchase ad isalme sale? Wha are he cash flow cosequeces of a lease? Illusrae.

More information

Learning Objectives. Chapter 2 Pricing of Bonds. Future Value (FV)

Learning Objectives. Chapter 2 Pricing of Bonds. Future Value (FV) Leaig Objectives Chapte 2 Picig of Bods time value of moey Calculate the pice of a bod estimate the expected cash flows detemie the yield to discout Bod pice chages evesely with the yield 2-1 2-2 Leaig

More information

Pricing strategy of e-commerce platform under different operational models

Pricing strategy of e-commerce platform under different operational models Picing saegy of e-coece lafo unde diffeen oeaional odels Shuihua Han, Yufang Fu School of Manageen, Xiaen Univesiy, Xiaen, 36000, China Absac: We odel icing saegy unde lafo coeiion wih diffeen e-coece

More information

Understanding Financial Management: A Practical Guide Guideline Answers to the Concept Check Questions

Understanding Financial Management: A Practical Guide Guideline Answers to the Concept Check Questions Udestadig Fiacial Maagemet: A Pactical Guide Guidelie Aswes to the Cocept Check Questios Chapte 4 The Time Value of Moey Cocept Check 4.. What is the meaig of the tems isk-etu tadeoff ad time value of

More information

Circle Geometry (Part 3)

Circle Geometry (Part 3) Eam aer 3 ircle Geomery (ar 3) emen andard:.4.(c) yclic uadrilaeral La week we covered u otheorem 3, he idea of a convere and we alied our heory o ome roblem called IE. Okay, o now ono he ne chunk of heory

More information

Why we use compounding and discounting approaches

Why we use compounding and discounting approaches Comoudig, Discouig, ad ubiased Growh Raes Near Deb s school i Souher Colorado. A examle of slow growh. Coyrigh 000-04, Gary R. Evas. May be used for o-rofi isrucioal uroses oly wihou ermissio of he auhor.

More information

Pricing Strategies of Electronic B2B Marketplaces with Two-Sided Network Externalities

Pricing Strategies of Electronic B2B Marketplaces with Two-Sided Network Externalities -7695-145-9 $17. c IEEE 1 Poceedig of the 5th Aual Hawaii Iteatioal Cofeece o Sytem Sciece HICSS-5-7695-145-9 $17. IEEE Poceedig of the 5th Hawaii Iteatioal Cofeece o Sytem Sciece - Picig Stategie of Electoic

More information

Money Math for Teens. Introduction to Earning Interest: 11th and 12th Grades Version

Money Math for Teens. Introduction to Earning Interest: 11th and 12th Grades Version Moey Math fo Tees Itoductio to Eaig Iteest: 11th ad 12th Gades Vesio This Moey Math fo Tees lesso is pat of a seies ceated by Geeatio Moey, a multimedia fiacial liteacy iitiative of the FINRA Ivesto Educatio

More information

Modeling the Yield Curve Dynamics

Modeling the Yield Curve Dynamics FIXED-INCOME SECURITIES Chape 2 Modeling he Yield Cuve Dynamics Ouline Moivaion Inees Rae Tees Single-Faco Coninuous-Time Models Muli-Faco Coninuous-Time Models Abiage Models Moivaion Why do we Cae? Picing

More information

Valuing Long-Lived Assets

Valuing Long-Lived Assets Valuing Long-Lived Asses Olive Tabalski, 008-09-0 This chape explains how you can calculae he pesen value of cash flow. Some vey useful shocu mehods will be shown. These shocus povide a good oppouniy fo

More information

Design of Beams (Flexural Members) (Part 5 of AISC/LRFD)

Design of Beams (Flexural Members) (Part 5 of AISC/LRFD) Desig of Beams (leual emes) (Pa 5 of AISC/RD) Refeeces 1. Pa 5 of e AISC RD aual. Cae ad Aedi of e AISC RD Secificaios (Pa 16 of RD aual) 3. Cae ad Aedi of e Commea of e AISC RD Secificaios (Pa 16 of RD

More information

OPTIONS ON PENSION ANNUITY

OPTIONS ON PENSION ANNUITY 06 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 3, 007 OPION ON PNION NNUIY hulamih. Goss *, Rami Yosef **, Ui Benzion *** bsac We inoduce a uoean (eoic) call oion on a ension annuiy. he

More information

HUT, TUT, LUT, OU, ÅAU / Engineering departments Entrance examination in mathematics May 25, 2004

HUT, TUT, LUT, OU, ÅAU / Engineering departments Entrance examination in mathematics May 25, 2004 HUT, TUT, LUT, OU, ÅAU / Engineeing depamens Enane examinaion in mahemais May 5, 4 Insuions. Reseve a sepaae page fo eah poblem. Give you soluions in a lea fom inluding inemediae seps. Wie a lean opy of

More information

UNDERWRITING AND EXTRA RISKS IN LIFE INSURANCE Katarína Sakálová

UNDERWRITING AND EXTRA RISKS IN LIFE INSURANCE Katarína Sakálová The process of uderwriig UNDERWRITING AND EXTRA RISKS IN LIFE INSURANCE Kaaría Sakálová Uderwriig is he process by which a life isurace compay decides which people o accep for isurace ad o wha erms Life

More information

Semipartial (Part) and Partial Correlation

Semipartial (Part) and Partial Correlation Semipatial (Pat) and Patial Coelation his discussion boows heavily fom Applied Multiple egession/coelation Analysis fo the Behavioal Sciences, by Jacob and Paticia Cohen (975 edition; thee is also an updated

More information

APPLICATIONS OF GEOMETRIC

APPLICATIONS OF GEOMETRIC APPLICATIONS OF GEOMETRIC SEQUENCES AND SERIES TO FINANCIAL MATHS The mos powerful force i he world is compoud ieres (Alber Eisei) Page of 52 Fiacial Mahs Coes Loas ad ivesmes - erms ad examples... 3 Derivaio

More information

Bullwhip Effect Measure When Supply Chain Demand is Forecasting

Bullwhip Effect Measure When Supply Chain Demand is Forecasting J. Basic. Appl. Sci. Res., (4)47-43, 01 01, TexRoad Publicaio ISSN 090-4304 Joural of Basic ad Applied Scieific Research www.exroad.com Bullwhip Effec Measure Whe Supply Chai emad is Forecasig Ayub Rahimzadeh

More information

Solutions to Problems: Chapter 7

Solutions to Problems: Chapter 7 Solution to Poblem: Chapte 7 P7-1. P7-2. P7-3. P7-4. Authoized and available hae LG 2; Baic a. Maximum hae available fo ale Authoized hae 2,000,000 Le: Shae outtanding 1,400,000 Available hae 600,000 b.

More information

Chapter 30: Magnetic Fields Due to Currents

Chapter 30: Magnetic Fields Due to Currents d Chapte 3: Magnetic Field Due to Cuent A moving electic chage ceate a magnetic field. One of the moe pactical way of geneating a lage magnetic field (.1-1 T) i to ue a lage cuent flowing though a wie.

More information

Effect of Unemployment Insurance Tax On Wages and Employment: A Partial Equilibrium Analysis

Effect of Unemployment Insurance Tax On Wages and Employment: A Partial Equilibrium Analysis Effect of Unemployment nuance Tax On Wage and Employment: atial Equilibium nalyi Deegha Raj dhikai, Oklahoma Employment Secuity Commiion ynn Gay, Oklahoma Employment Secuity Commiion Jackie Bun, Texa &

More information

Finance Practice Problems

Finance Practice Problems Iteest Fiace Pactice Poblems Iteest is the cost of boowig moey. A iteest ate is the cost stated as a pecet of the amout boowed pe peiod of time, usually oe yea. The pevailig maket ate is composed of: 1.

More information

FORECASTING MODEL FOR AUTOMOBILE SALES IN THAILAND

FORECASTING MODEL FOR AUTOMOBILE SALES IN THAILAND FORECASTING MODEL FOR AUTOMOBILE SALES IN THAILAND by Wachareepor Chaimogkol Naioal Isiue of Developme Admiisraio, Bagkok, Thailad Email: wachare@as.ida.ac.h ad Chuaip Tasahi Kig Mogku's Isiue of Techology

More information

Chapter 4: Matrix Norms

Chapter 4: Matrix Norms EE448/58 Vesion.0 John Stensby Chate 4: Matix Noms The analysis of matix-based algoithms often equies use of matix noms. These algoithms need a way to quantify the "size" of a matix o the "distance" between

More information

Transformations. Computer Graphics. Types of Transformations. 2D Scaling from the origin. 2D Translations. 9/22/2011. Geometric Transformation

Transformations. Computer Graphics. Types of Transformations. 2D Scaling from the origin. 2D Translations. 9/22/2011. Geometric Transformation 9// anfomaion. Compue Gaphic Lecue anfomaion Wha i a anfomaion? Wha oe i o? anfom he cooinae / nomal veco of objec Wh ue hem? Moelling -Moving he objec o he eie locaion in he envionmen -Muliple inance

More information

29 March 2006. Application of Annuity Depreciation in the Presence of Competing Technologies II Telecom New Zealand

29 March 2006. Application of Annuity Depreciation in the Presence of Competing Technologies II Telecom New Zealand 29 Mach 2006 Applicaion of Annuiy Depeciaion in he Pesence of Compeing Technologies II Telecom ew Zealand Pojec Team Tom Hid (Ph.D.) Daniel Young EA Economic Consuling Level 6 33 Exhibiion See Melboune

More information

Managing Learning and Turnover in Employee Staffing*

Managing Learning and Turnover in Employee Staffing* Maagig Learig ad Turover i Employee Saffig* Yog-Pi Zhou Uiversiy of Washigo Busiess School Coauhor: Noah Gas, Wharo School, UPe * Suppored by Wharo Fiacial Isiuios Ceer ad he Sloa Foudaio Call Ceer Operaios

More information

CENTRAL HUDSON GAS & ELECTRIC CORPORATION A AND C LINE REBUILD PROJECT EXHIBIT 2 LOCATION OF FACILITIES

CENTRAL HUDSON GAS & ELECTRIC CORPORATION A AND C LINE REBUILD PROJECT EXHIBIT 2 LOCATION OF FACILITIES BEFOE THE NEW YOK STATE PUBLIC SEVICE COMMISSION I he Mae of he Applicaio of Ceal Huso Gas & Elecic Copoaio Fo a Ceificae of Eviomeal Compaibiliy a Public Nee Pusua o Aicle VII of he Public Sevice Law

More information

The Term Structure of Interest Rates

The Term Structure of Interest Rates The Term Srucure of Ieres Raes Wha is i? The relaioship amog ieres raes over differe imehorizos, as viewed from oday, = 0. A cocep closely relaed o his: The Yield Curve Plos he effecive aual yield agais

More information

A GLOSSARY OF MAIN TERMS

A GLOSSARY OF MAIN TERMS he aedix o his glossary gives he mai aggregae umber formulae used for cosumer rice (CI) uroses ad also exlais he ierrelaioshis bewee hem. Acquisiios aroach Addiiviy Aggregae Aggregaio Axiomaic, or es aroach

More information

REVISTA INVESTIGACION OPERACIONAL VOL. 31, No.2, 159-170, 2010

REVISTA INVESTIGACION OPERACIONAL VOL. 31, No.2, 159-170, 2010 REVISTA INVESTIGACION OPERACIONAL VOL. 3, No., 59-70, 00 AN ALGORITHM TO OBTAIN AN OPTIMAL STRATEGY FOR THE MARKOV DECISION PROCESSES, WITH PROBABILITY DISTRIBUTION FOR THE PLANNING HORIZON. Gouliois E.

More information

Southwark Regeneration in Partnership Programme

Southwark Regeneration in Partnership Programme Suhwak Regeeai i Paeship Pgamme Ou Visi: The cucil s visi f he bugh aims : Achieve susaiable evelpme by balacig evimeal, scial a ecmic ees esue a g qualiy f life f peple w a i he lg em. Ciue eflec u ivese

More information

Derivation of Annuity and Perpetuity Formulae. A. Present Value of an Annuity (Deferred Payment or Ordinary Annuity)

Derivation of Annuity and Perpetuity Formulae. A. Present Value of an Annuity (Deferred Payment or Ordinary Annuity) Aity Deivatios 4/4/ Deivatio of Aity ad Pepetity Fomlae A. Peset Vale of a Aity (Defeed Paymet o Odiay Aity 3 4 We have i the show i the lecte otes ad i ompodi ad Discoti that the peset vale of a set of

More information

Debt, Equity, and Taxes

Debt, Equity, and Taxes De, Equiy, ad Taxes By Dee Kesley * Coluia Uivesiy ad Yale Uivesiy ad Michael G Willias ** Uivesiy of Califoia, Los Aeles Jauay 0, 2002 We expess appeciaio fo isihful coes fo Aoio Beado, David Badfod,

More information

The LCOE is defined as the energy price ($ per unit of energy output) for which the Net Present Value of the investment is zero.

The LCOE is defined as the energy price ($ per unit of energy output) for which the Net Present Value of the investment is zero. Poject Decision Metics: Levelized Cost of Enegy (LCOE) Let s etun to ou wind powe and natual gas powe plant example fom ealie in this lesson. Suppose that both powe plants wee selling electicity into the

More information

Framework for Computation Offloading in Mobile Cloud Computing

Framework for Computation Offloading in Mobile Cloud Computing Famewok fo Computatio Offloadig i Mobile Cloud Computig Deja Kovachev ad Ralf Klamma Depatmet of Ifomatio Sytem ad Databae RWTH Aache Uiveity Abtact The iheetly limited poceig powe ad battey lifetime of

More information

Worked Examples. v max =?

Worked Examples. v max =? Exaple iction + Unifo Cicula Motion Cicula Hill A ca i diing oe a ei-cicula hill of adiu. What i the fatet the ca can die oe the top of the hill without it tie lifting off of the gound? ax? (1) Copehend

More information

Campus Sustainability Assessment and Related Literature

Campus Sustainability Assessment and Related Literature Campus Sustainability Assessment and Related Literature An Annotated Bibliography and Resource Guide Andrew Nixon February 2002 Campus Sustainability Assessment Review Project Telephone: (616) 387-5626

More information

Periodic Review Probabilistic Multi-Item Inventory System with Zero Lead Time under Constraints and Varying Order Cost

Periodic Review Probabilistic Multi-Item Inventory System with Zero Lead Time under Constraints and Varying Order Cost Ameica Joual of Applied Scieces (8: 3-7, 005 ISS 546-939 005 Sciece Publicatios Peiodic Review Pobabilistic Multi-Item Ivetoy System with Zeo Lead Time ude Costaits ad Vayig Ode Cost Hala A. Fegay Lectue

More information

Two degree of freedom systems. Equations of motion for forced vibration Free vibration analysis of an undamped system

Two degree of freedom systems. Equations of motion for forced vibration Free vibration analysis of an undamped system wo degee of feedom systems Equatios of motio fo foced vibatio Fee vibatio aalysis of a udamped system Itoductio Systems that equie two idepedet d coodiates to descibe thei motio ae called two degee of

More information

A formulation for measuring the bullwhip effect with spreadsheets Una formulación para medir el efecto bullwhip con hojas de cálculo

A formulation for measuring the bullwhip effect with spreadsheets Una formulación para medir el efecto bullwhip con hojas de cálculo irecció y rgaizació 48 (01) 9-33 9 www.revisadyo.com A formulaio for measurig he bullwhip effec wih spreadshees Ua formulació para medir el efeco bullwhip co hojas de cálculo Javier Parra-Pea 1, Josefa

More information

Reaction Rates. Example. Chemical Kinetics. Chemical Kinetics Chapter 12. Example Concentration Data. Page 1

Reaction Rates. Example. Chemical Kinetics. Chemical Kinetics Chapter 12. Example Concentration Data. Page 1 Page Chemical Kieics Chaper O decomposiio i a isec O decomposiio caalyzed by MO Chemical Kieics I is o eough o udersad he soichiomery ad hermodyamics of a reacio; we also mus udersad he facors ha gover

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

Standardized Coefficients

Standardized Coefficients Standadized Coefficient Ta. How do ou decide which of the X ae mot impotant fo detemining? In thi handout, we dicu one poile (and contoveial) anwe to thi quetion - the tandadized egeion coefficient. Fomula.

More information

How Much Can Taxes Help Selfish Routing?

How Much Can Taxes Help Selfish Routing? How Much Can Taxe Help Selfih Rouing? Tim Roughgarden (Cornell) Join wih Richard Cole (NYU) and Yevgeniy Dodi (NYU) Selfih Rouing a direced graph G = (V,E) a ource and a deinaion one uni of raffic from

More information

cooking trajectory boiling water B (t) microwave 0 2 4 6 8 101214161820 time t (mins)

cooking trajectory boiling water B (t) microwave 0 2 4 6 8 101214161820 time t (mins) Alligaor egg wih calculus We have a large alligaor egg jus ou of he fridge (1 ) which we need o hea o 9. Now here are wo accepable mehods for heaing alligaor eggs, one is o immerse hem in boiling waer

More information

Ranking of mutually exclusive investment projects how cash flow differences can solve the ranking problem

Ranking of mutually exclusive investment projects how cash flow differences can solve the ranking problem Chrisia Kalhoefer (Egyp) Ivesme Maageme ad Fiacial Iovaios, Volume 7, Issue 2, 2 Rakig of muually exclusive ivesme projecs how cash flow differeces ca solve he rakig problem bsrac The discussio abou he

More information

Estimation and Comparison of Chained CPI-U Standard Errors With Regular CPI-U Results (2000-2001)

Estimation and Comparison of Chained CPI-U Standard Errors With Regular CPI-U Results (2000-2001) 2003 Join Saisical Meeings - Secion on Suvey eseach Mehods Esimaion and ompaison of hained PI-U Sandad Eos Wih egula PI-U esuls (2000-2001) Owen J. Shoemake U.S. Bueau of Labo Saisics, 2 Mass Ave., NE,

More information

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern.

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern. 5.5 Fractios ad Decimals Steps for Chagig a Fractio to a Decimal. Simplify the fractio, if possible. 2. Divide the umerator by the deomiator. d d Repeatig Decimals Repeatig Decimals are decimal umbers

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

The dinner table problem: the rectangular case

The dinner table problem: the rectangular case The ie table poblem: the ectagula case axiv:math/009v [mathco] Jul 00 Itouctio Robeto Tauaso Dipatimeto i Matematica Uivesità i Roma To Vegata 00 Roma, Italy tauaso@matuiomait Decembe, 0 Assume that people

More information

Streamline Compositional Simulation of Gas Injections Dacun Li, University of Texas of the Permian Basin

Streamline Compositional Simulation of Gas Injections Dacun Li, University of Texas of the Permian Basin Abstact Steamlie Comositioal Simulatio of Gas jectios Dacu L Uivesity of Texas of the Pemia Basi Whe esevoi temeatues ae lowe tha o F ad essue is lowe tha 5sia, gas ijectios, esecially whe ijectats iclude

More information

Ultraconservative Online Algorithms for Multiclass Problems

Ultraconservative Online Algorithms for Multiclass Problems Jounal of Machine Leaning Reseach 3 (2003) 951-991 Submied 2/02; Published 1/03 Ulaconsevaive Online Algoihms fo Muliclass Poblems Koby Camme Yoam Singe School of Compue Science & Engineeing Hebew Univesiy,

More information

An iterative wave-front sensing algorithm for high-contrast imaging systems *

An iterative wave-front sensing algorithm for high-contrast imaging systems * An ieaive wave-fon sensing algoihm fo high-conas imaging sysems * Jiangpei Dou,, Deqing Ren,,,3 and Yongian Zhu, aional Asonomical Obsevaoies / anjing Insiue of Asonomical Opics & Technology, Chinese Academy

More information

NETWORK TRAFFIC PRIORITIZATION USING MAP OF ARRIVALS

NETWORK TRAFFIC PRIORITIZATION USING MAP OF ARRIVALS Seion 1. Statitic Method and Thei Alication Poceeding of the 11 th Intenational Confeence eliability and Statitic in Tanotation and Communication (elstat 11), 19 22 Octobe 2011, iga, Latvia,. 82-87. ISBN

More information

FM4 CREDIT AND BORROWING

FM4 CREDIT AND BORROWING FM4 CREDIT AND BORROWING Whe you purchase big ticket items such as cars, boats, televisios ad the like, retailers ad fiacial istitutios have various terms ad coditios that are implemeted for the cosumer

More information

ANNUITIES SOFTWARE ASSIGNMENT TABLE OF CONTENTS... 1 ANNUITIES SOFTWARE ASSIGNMENT... 2 WHAT IS AN ANNUITY?... 2 EXAMPLE 1... 2 QUESTIONS...

ANNUITIES SOFTWARE ASSIGNMENT TABLE OF CONTENTS... 1 ANNUITIES SOFTWARE ASSIGNMENT... 2 WHAT IS AN ANNUITY?... 2 EXAMPLE 1... 2 QUESTIONS... ANNUITIES SOFTWARE ASSIGNMENT TABLE OF CONTENTS ANNUITIES SOFTWARE ASSIGNMENT TABLE OF CONTENTS... 1 ANNUITIES SOFTWARE ASSIGNMENT... WHAT IS AN ANNUITY?... EXAMPLE 1... QUESTIONS... EXAMPLE BRANDON S

More information

T c k D E GR EN S. R a p p o r t M o d u le Aa n g e m a a k t o p 19 /09 /2007 o m 09 :29 u u r BJB 06 013-0009 0 M /V. ja a r.

T c k D E GR EN S. R a p p o r t M o d u le Aa n g e m a a k t o p 19 /09 /2007 o m 09 :29 u u r BJB 06 013-0009 0 M /V. ja a r. D a t a b a n k m r in g R a p p o r t M Aa n g e m a a k t o p 19 /09 /2007 o m 09 :29 u u r I d e n t if ic a t ie v a n d e m S e c t o r BJB V o lg n r. 06 013-0009 0 V o o r z ie n in g N ie u w la

More information

FEBRUARY 2015 STOXX CALCULATION GUIDE

FEBRUARY 2015 STOXX CALCULATION GUIDE FEBRUARY 2015 STOXX CALCULATION GUIDE STOXX CALCULATION GUIDE CONTENTS 2/23 6.2. INDICES IN EUR, USD AND OTHER CURRENCIES 10 1. INTRODUCTION TO THE STOXX INDEX GUIDES 3 2. CHANGES TO THE GUIDE BOOK 4 2.1.

More information

Annuities and loan. repayments. Syllabus reference Financial mathematics 5 Annuities and loan. repayments

Annuities and loan. repayments. Syllabus reference Financial mathematics 5 Annuities and loan. repayments 8 8A Futue value of a auity 8B Peset value of a auity 8C Futue ad peset value tables 8D Loa epaymets Auities ad loa epaymets Syllabus efeece Fiacial mathematics 5 Auities ad loa epaymets Supeauatio (othewise

More information

1/22/2007 EECS 723 intro 2/3

1/22/2007 EECS 723 intro 2/3 1/22/2007 EES 723 iro 2/3 eraily, all elecrical egieers kow of liear sysems heory. Bu, i is helpful o firs review hese coceps o make sure ha we all udersad wha his heory is, why i works, ad how i is useful.

More information

C o a t i a n P u b l i c D e b tm a n a g e m e n t a n d C h a l l e n g e s o f M a k e t D e v e l o p m e n t Z a g e bo 8 t h A p i l 2 0 1 1 h t t pdd w w wp i j fp h D p u b l i c2 d e b td S t

More information

Experiment #1: Reflection, Refraction, and Dispersion

Experiment #1: Reflection, Refraction, and Dispersion Expeimen #1: Reflecion, Refacion, and Dispesion Pupose: To sudy eflecion and efacion of ligh a plane and cuved sufaces, as well as he phenomenon of dispesion. Equipmen: Ray Box wih Slis Opical Accessoies

More information

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2 MECH 5 Egieerig Sciece 3 Eergy 3.3. No-Flow Eergy Equatio (NFEE) You may have oticed that the term system kees croig u. It is ecessary, therefore, that before we start ay aalysis we defie the system that

More information

Chapter 12 Static Equilibrium and Elasticity

Chapter 12 Static Equilibrium and Elasticity Chapte Static Equilibium ad Elaticity Coceptual Poblem [SSM] Tue o fale: (a) i 0 i ufficiet fo tatic equilibium to eit. i (b) i 0 i eceay fo tatic equilibium to eit. i (c) I tatic equilibium, the et toque

More information

FIRST UNIVERSITY OF NAPLES FEDERICO II PHD SCHOOL IN: INNOVATIVE TECHNOLOGIES FOR MATERIALS, SENSORS AND IMAGING. XXII CYCLE (2006-2009) THESIS

FIRST UNIVERSITY OF NAPLES FEDERICO II PHD SCHOOL IN: INNOVATIVE TECHNOLOGIES FOR MATERIALS, SENSORS AND IMAGING. XXII CYCLE (2006-2009) THESIS FRST UNERSTY OF NAPES FEDERCO PHD SCHOO N: NNOATE TECHNOOGES FOR MATERAS, SENSORS AND MAGNG. XX CYCE (6-9 THESS NUMERCA-ANAYTCA METHODS FOR PARTCE ACCEERATORS TUTOR Pof. TTORO G. ACCARO CANDDATE MARCO

More information

1.- L a m e j o r o p c ió n e s c l o na r e l d i s co ( s e e x p li c a r á d es p u é s ).

1.- L a m e j o r o p c ió n e s c l o na r e l d i s co ( s e e x p li c a r á d es p u é s ). PROCEDIMIENTO DE RECUPERACION Y COPIAS DE SEGURIDAD DEL CORTAFUEGOS LINUX P ar a p od e r re c u p e ra r nu e s t r o c o rt a f u e go s an t e un d es a s t r e ( r ot u r a d e l di s c o o d e l a

More information

Mechanics 1: Motion in a Central Force Field

Mechanics 1: Motion in a Central Force Field Mechanics : Motion in a Cental Foce Field We now stud the popeties of a paticle of (constant) ass oving in a paticula tpe of foce field, a cental foce field. Cental foces ae ve ipotant in phsics and engineeing.

More information

Clustering Process to Solve Euclidean TSP

Clustering Process to Solve Euclidean TSP Cluteig Poce to Solve Euclidea TSP Abdulah Faja *Ifomatic Depatmet, Faculty of Egieeig Uiveita Widyatama Badug Idoeia # Faculty of Ifomatio ad Commuicatio Techology Uiveiti Tekikal Malayia Melaka #*abd.faja@gmail.com,

More information

APPLICATION REQUIREMENTS Failure to include the following may delay the processing of your application.

APPLICATION REQUIREMENTS Failure to include the following may delay the processing of your application. BUILDING DEPAMEN (440) 937-7811 FAX (440) 937-7824 : All ontractors/ubcontractors FOM: ity of Avon Building Department JE: ontractor egistration and egistration equirements EGIAI I EQUIED OF ALL A AND

More information

Cruisin with Carina Motorcycle and Car Tour Guide

Cruisin with Carina Motorcycle and Car Tour Guide Ifi Tchlgy Slui Wh Swdih hpiliy V, ully. Cuii wih Ci Mcycl d C Tu Guid Ikp: Ci Th 290 Ru 100 W Dv, V 05356 800-745-3615 802-464-2474 L h g ll! Th d i ck, c, i d l x. My 17h, 18h, & 19h W ivi yu c cui h

More information

The Business Case for D om aink ey s I d ent ified M ail Andy Spillane V ic e P r es ident, Y ah o o! M February 13, 2006 ail 1 Fighting Spam & Email Abuse R eq uir es a M ulti-fac eted Appr o ac h DomainKeys

More information

Vibration Reduction of Gantry Crane Loads with Hoisting Using Finite Impulse Response (FIR) Digital Filters

Vibration Reduction of Gantry Crane Loads with Hoisting Using Finite Impulse Response (FIR) Digital Filters io Recio of Gy Ce Lo wih Hoiig Uig Fiie Ipe Repoe (FIR Digi Fie D. ECOOOU I. ATOIADIS Reech Ai Ai Pofeo Depe of echic Egieeig, io Techic Uiveiy of Ahe, Poyechic Cp, Zogfo, P. O. Bo 64078, 15710 GREECE.

More information

Valuation of Floating Rate Bonds 1

Valuation of Floating Rate Bonds 1 Valuation of Floating Rate onds 1 Joge uz Lopez us 316: Deivative Secuities his note explains how to value plain vanilla floating ate bonds. he pupose of this note is to link the concepts that you leaned

More information

Confidence Intervals for Linear Regression Slope

Confidence Intervals for Linear Regression Slope Chapter 856 Cofidece Iterval for Liear Regreio Slope Itroductio Thi routie calculate the ample ize eceary to achieve a pecified ditace from the lope to the cofidece limit at a tated cofidece level for

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

More examples for Hypothesis Testing

More examples for Hypothesis Testing More example for Hypothei Tetig Part I: Compoet 1. Null ad alterative hypothee a. The ull hypothee (H 0 ) i a tatemet that the value of a populatio parameter (mea) i equal to ome claimed value. Ex H 0:

More information

Pricing and Hedging Guaranteed Annuity Options via Static Option Replication 1

Pricing and Hedging Guaranteed Annuity Options via Static Option Replication 1 Picing and Hedging Guaaneed Annuiy Opions via Saic Opion Replicaion Anoon Pelsse Head of ALM Dep Pofesso of Mahemaical Finance Naionale-Nedelanden Easmus Univesiy Roedam Acuaial Dep Economeic Insiue PO

More information

9.5 Amortization. Objectives

9.5 Amortization. Objectives 9.5 Aotization Objectives 1. Calculate the payent to pay off an aotized loan. 2. Constuct an aotization schedule. 3. Find the pesent value of an annuity. 4. Calculate the unpaid balance on a loan. Congatulations!

More information

Domain 1: Designing a SQL Server Instance and a Database Solution

Domain 1: Designing a SQL Server Instance and a Database Solution Maual SQL Server 2008 Desig, Optimize ad Maitai (70-450) 1-800-418-6789 Domai 1: Desigig a SQL Server Istace ad a Database Solutio Desigig for CPU, Memory ad Storage Capacity Requiremets Whe desigig a

More information

Put the human back in Human Resources.

Put the human back in Human Resources. Put the human back in Human Resources A Co m p l et e Hu m a n Ca p i t a l Ma n a g em en t So l u t i o n t h a t em p o w er s HR p r o f essi o n a l s t o m eet t h ei r co r p o r a t e o b j ect

More information

Time Value of Money: The case of Arithmetic and Geometric growth and their Applications

Time Value of Money: The case of Arithmetic and Geometric growth and their Applications CHAPTER TE SPECIAL TOPICS I FIACE Time Value of Moey: The cae of Aithmetic a Geometic owth a thei Applicatio I. Itouctio Kowlee of how iteet compou i a coetoe of fiace a i iteal i fiacial eciio at the

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

OBJECT-ORIENTED & OBJECT- RELATIONAL DATABASES CS561-SPRING 2012 WPI, MOHAMED ELTABAKH

OBJECT-ORIENTED & OBJECT- RELATIONAL DATABASES CS561-SPRING 2012 WPI, MOHAMED ELTABAKH OBJECT-ORENTED & OBJECT- RELATONAL DATABAE C561-PRNG 2012 WP, MOHAMED ELTABAKH 1 Objec Oieed Dbe Hy Dbe HTORY OF DATABAE! Bck Begg file yem (1950)! e d fe poce ceed i h ceed ex hiechicl/ ewok (1960)!!!!

More information

Using Model Checking to Analyze Network Vulnerabilities

Using Model Checking to Analyze Network Vulnerabilities Uing Model Checking to Analyze Netwok Vulneabilitie Ronald W. Ritchey Paul Ammann * National Secuity Team Infomation and Softwae Engineeing Depatment Booz Allen & Hamilton Geoge Maon Univeity Fall Chuch,

More information

Confidence Intervals (2) QMET103

Confidence Intervals (2) QMET103 Cofidece Iterval () QMET03 Library, Teachig ad Learig Geeral Remember: three value are ued to cotruct all cofidece iterval: Samle tatitic Z or t Stadard error of amle tatitic Deciio ad Parameter to idetify:

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

March 2002. Report to the ACCC. Working Capital. Relevance for the Assessment of Reference Tariffs. The Allen Consulting Group

March 2002. Report to the ACCC. Working Capital. Relevance for the Assessment of Reference Tariffs. The Allen Consulting Group Mach 00 Repo o he ACCC Woking Capial Relevance fo he Assessmen of Refeence Taiffs The Allen Consuling Goup The Allen Consuling Goup Py Ld ACN 007 06 930 Melboune 4h Floo, 8 Exhibiion S Melboune Vicoia

More information