Masuring th impact of th uropan carbon trading dirctiv and th prmit assignmnt mthods on th Spanish lctricity sctor Pdro Linars, Francisco Javir Santos, Mariano Vntosa, Luis Lapidra Instituto d Invstigación Tcnológica. Univ. Pontificia Comillas. Sta. Cruz d Marcnado 26, 2815 Madrid, Spain. Tl. +34 91 54228 Fax. +34 915423176 pdro.linars@iit.upco.s Abstract. This papr asssss th conomic impact of th uropan Carbon missions Trading Dirctiv on th Spanish lctricity sctor. Although som othr studis hav bn carrid out bfor, our approach uss a mor dtaild modl for th Spanish lctricity sctor, what provids mor ralistic rsults both for th xpctd pric of th carbon allowanc and for th volution of lctricity prics, installd powr and firms rvnus in Spain. Rsults show that th implmntation of th Dirctiv will rsult in a significant incras of lctricity prics, and also, du to th Spanish pricing systm, in a larg incras in th rvnus of gnrating firms, unlss th rgulator intrvns. Rsults also show th diffrnt implications of diffrnt assignmnt mthods. This is spcially rlvant currntly givn that most uropan countris ar approving thir national assignmnt plans for 25-7 and hav to rvis thm for 28. Kywords: mission trading, Spanish lctricity sctor, assignmnt plans 1
1. Introduction Thr hav bn larg discussions latly in Spain ovr th sustainability of its currnt nrgy modl and how it will b affctd by th rcnt uropan policis rlatd with nrgy marts libralisation, rduction of CO 2 missions and promotion of rnwabl nrgis (Hrnandz t al, 24). And spcifically, th dbat has focusd mostly on th impact that th uropan Union Carbon missions Trading Dirctiv (C, 23) will hav on th Spanish lctricity sctor (basically, on lctricity prics and on th profitability of utilitis). This Dirctiv sts up, from th 1 st January 25, an uropan mart for carbon missions in ordr to comply mor fficintly with th compromiss undrtan by th uropan Union undr th Kyoto Protocol (namly, an 8% rduction in GHG missions compard to 199 lvls). Howvr, th Dirctiv is not xactly qual to th Protocol: it only applis to som sctors (basically, to industry, whras transport and th trtiary sctor ar lft out of th rgim); it will ntr into forc bfor th Protocol (it has stablishd a prliminary trading priod starting in 25); and it only covrs carbon missions and not th rst of grnhous gass. Th Dirctiv (or its accompanying documnts) also stablishs that th carbon prmits hav to b allocatd frly to thir most part, only proposing som idas on how to distribut thm among th sctors and firms affctd. Th final assignmnt has to b dcidd by th National Allocation Plans (NAPs), of which th Spanish on was approvd just in January 25 (RD 6/25). Howvr, th currnt NAP only covrs up to 27, and thrfor a nw on will b ndd for th ral Kyoto trading priod starting in 28. 2
This lattr aspct is spcially rlvant, givn that diffrnt allocation plans may hav diffrnt consquncs on th lctricity sctor as a whol, and on th diffrnt firms prsnt in Spain. Indd, this has cratd a battl btwn utilitis, contrary to th traditional common position. Howvr, most of th discussions hav bn hld on qualitativ grounds, or with rstrictd information, and thrfor it is difficult to draw spcific conclusions and policy rcommndations from it. Th objctiv of this papr is to bring som light into this discussion, by providing rasonabl stimats of th impact that th Dirctiv may hav on th lctricity sctor, not only on lctricity prics, but also on th tchnology mix, and on th rvnus of lctric utilitis. Although rsults ar focusd on th Spanish cas, th major conclusions may asily b xtrapolatd to othr uropan countris with similar rgulations. Th xisting litratur on th modlling of missions trading in th nrgy sctor is vry rich indd. Most of th xrciss hav bn carrid out with larg nrgyconomy-nvironmnt modls, of which a vry thorough rviw may b found for xampl in Huntington and Wyant (24). As for spcific applications, w may cit th wor of McKibbin t al (1999), Criqui and Viguir (2), Viguir t al (23), or Barrto and Kypros (24). Howvr, ths modls covr gnrally larg rgions and larg sctors, and thrfor ar not abl to provid spcific rsults for th lctricity sctor, which is a rlvant playr in many conomis, and crtaintly not spcific for th Spanish lctricity sctor, which is th objctiv of this study. Thrfor, mor dtaild modls ar ndd. 3
Concrning this dtaild modlling of th lctricity sctor undr missions trading schms, som wor was carrid out in th US undr th Clan Air Act (s.g. Hobbs (1993)), and rcntly in urop, Morthorst (21), Hindsbrgr t al (23), or Jnsn and Sytt (23) hav lood at th spcific impact of carbon trading on th Nordic countris lctricity sctor, spcially analysing its intraction with rnwabl nrgy promotion schms. Th problm with ths modls is that thy ar not abl to rprsnt adquatly lctricity sctors undr imprfct comptition, as is th cas for Spain 1. Only two studis wr found which modlld an oligopolistic mart undr missions trading rgims, Nagurny t al (1999) and Nagurny and Dhanda (2). Howvr, thy ar too gnral and unabl to cop with th tchnical spcificitis of th lctricity sctor. That is why in this papr, in ordr to provid ralistic stimats for lctricity prics, tchnology dploymnt, or firm rvnus, w hav usd a nw oligopolistic, gnration xpansion modl for th Spanish lctricity sctor, which has 1 For thos not familiar with it, th Spanish lctricity sctor is a rathr concntratd on, with two larg firms covring almost 8% of th gnration mart and only four mor small firms with som gnration capacity, which covr th rst of th mart. Th currnt nrgy mix is basically 2% hydro (dpnding on rainfall), 3% nuclar, 35% coal and 15% gas. Most of hydro and nuclar blong to th two largst firms. Thrfor, th conditions ar prsnt for an oligopolistic bhaviour of th lading firms, what dos hav consquncs on lctricity prics, but also on how th carbon mission pric is intrnalisd into th mart. Mor information about th Spanish lctricity systm may b found in Kahn (1996, 1998). 4
bn dvlopd at our Institut, th SPAM modl. This modl prsnts svral charactristics which ar lily to provid bttr stimats about th consquncs on th lctricity sctor than othr studis, namly: - th Spanish lctricity sctor is modlld to a larg dtail, thus providing usful and mor ralistic information of th impact of th Dirctiv on diffrnt utilitis and tchnologis. Although th lctricity sctor is not th major carbon mittr, with som 2% of th total carbon missions, it is crtainly th major playr within th missions trading schm (sinc it rprsnts mor than 5% of th total missions covrd by th Dirctiv), and thrfor it is important to modl it adquatly - contrary to most modlling xrciss, ours tas into account th oligopolistic structur of th sctor, what producs diffrnt rsults in th incorporation of th allowanc pric into th lctricity pric, compard to a prfct comptition assumption - although most modls usd rly on an xognous allowanc pric, our modl producs it ndognously, what provids mor flxibility to th analysis - th modl is not a static on, but simulats th xpansion of gnration, thrfor offring a viw of th futur ffcts on prics and tchnologis, and on th raction of firms. Th modl usd is dscribd in sction 2, whil th rsults obtaind undr diffrnt assumptions (namly, assignmnt mthods) ar prsntd in sction 3. Finally, sction 4 provids th conclusions drawn from th study. 5
2. Th modl As mntiond abov, th modl usd to simulat th prsnt and futur bhaviour of th Spanish lctricity sctor undr th U carbon dirctiv is an oligopolistic, gnration xpansion modl dvlopd at Instituto d Invstigación Tcnológica, th SPAM modl. 2.1 Modlling th lctricity mart Traditionally, th simulation of th opration and planning of th lctricity sctor has bn carrid out with cost minimisation modls. Howvr, ths modls ar not wll suitd to th nw framwor dvlopd by th lctricity sctor rstructuring and libralisation in most countris. Indd, this libralisation has brought forward oligopolistic structurs in many countris, which rsult in a diffrnt bhaviour of th agnts in thir profit maximization. This situation has gratly stimulatd th fforts of th rsarch community to dvlop modls that considr imprfct comptition, of which an xtnsiv rviw is givn in Vntosa t al (25). On of th approachs (Rivir t al, 21) to th rsolution of this problm is to considr a mart in which companis compt in quantity of output and gnrating capacity as in th Nash-Cournot gam.th assumption of gnration companis bhaving as Cournot playrs has bn xtnsivly usd to conduct lctricity mart analysis. Howvr, a numbr of drawbacs sm to qustion th applicability of th Cournot modl. Th most important on stms from th fact that undr th Cournot approach, gnrators stratgis ar xprssd in trms of quantitis and not in trms of supply curvs. Hnc, quilibrium prics ar dtrmind only by 6
th dmand function bing thrfor highly snsitiv to dmand rprsntation and usually highr to thos obsrvd in rality. Incorporating th Conjctural Variations (CV) approach dscribd in traditional microconomics thory (Vivs (1999)) has bn a way to ovrcom this limitation. Th CV approach is asy to introduc into Cournot-basd modls sinc rsulting modls can b statd as Linar Complmntarity Problm (Cottl t al, 1992). This approach changs th conjcturs that gnrators ar xpctd to assum about thir comptitors stratgic dcisions, in trms of th possibility of futur ractions (conjctural variations). Th CV approach allows th raction of comptitors whn a firm is dciding its optimal production. This raction coms out from firms supply functions and dmand curv. This raction can b modlld by th so-calld firm s rsidual dmand function. This function is diffrnt for ach firm and rlats ach firm s production with th mart pric. It can b obtaind by mans of subtracting th rmaining comptitors supply functions from th mart dmand curv. A rlvant assumption of this modl is that firms opration dcision-maing occurs simultanously. Two publications García-Alcald t al. (22); Day t al. (22) suggst considring this approach in ordr to improv Cournot pricing in lctricity marts. Concptually, th structur of th modl usd in this papr corrsponds to various simultanous optimizations for ach firm, th maximization of its profits subjct to its particular tchnical constraints -. Ths optimization problms ar lind togthr through th mart pric rsulting from th intraction of all of thm. Th lctricity mart is modlld by th dmand function that rlats th supplid dmand to th lctricity pric. It is assumd in this papr that th total dmand at ach load lvl is a linar function of th pric. 7
Th modl assums that firms ma thir capacity-xpansion dcisions as in a Nash quilibrium. Formally, th invstmnt mart quilibrium dfins a st of capacitis such that no firm, taing its comptitors capacitis as givn, wishs to chang its own capacity unilatrally (Vntosa t al, 22; Murphy and Smrs, 22). Thrby, ach firm chooss its nw maximum capacity so that its own profit is maximizd. Th Nash assumption implis that firms invstmnt dcision-maing occurs simultanously. As in many lctricity gnration-xpansion modls, capacity xpansion or tchnology substitution is assumd to happn within on yar, what is clarly a simplification, although not so significant currntly bcaus of th short commissioning priods for gas combind-cycls. For tchnologis with long commissioning priods such as nuclar this is taing into account by incrasing thir invstmnt costs with th appropriat capital intrst costs. Th xpansion modl considrs a hypr-annual scop dividd into diffrnt tim sgmnts: priods, sub priods and load lvls. Th priods coincid with yars, ach sub priod groups svral months whil th grouping of th pa, platau, and offpa hours mas up th load lvls. 2.2 Modlling th mission-basd prmit mart. Th modl considrs that th participants of th prmits mart ar th lctricity companis and th rst of sctors covrd by th Dirctiv, which trad with th prmits, and th govrnmnt, which sts th amount of prmits in th mart. Th modl is abl to rprsnt ithr auctions for th prmits or grandfathring. 8
This prmit mart is modlld as a prfctly comptitiv on. So th claring pric of th mart will b th crossing of th prmits aggrgatd dmand curv with th supply curv. Th supply curv is st to b a constant quantity of prmits dtrmind by th govrnmnt. Th aggrgatd dmand curv is th sum of dmands of vry company at vry prmit pric (which is in turn basd on its marginal abatmnt costs). This assumption implis that th quilibrium of th prmits mart should maximiz th profit for ach participant, obtaind ithr by slling its prmits or by buying thm in ordr to produc mor lctricity. So th rsolution of th mart quilibrium implis that in ach considrd priod, th modl should maximiz th objctiv function of ach company, including costs and bnfits from th prmits mart. Th lin btwn th prmits mart and vry firm s optimization program is th constraint that sts th mission of pollutants to th amount of prmits ownd by ach company. Th approach dvlopd in this papr for doing this consists in lining th mission prmits mart to th rsolution of th Conjctural Variations (CV) approach that sts th lctricity mart quilibrium so th quilibria of both marts can b solvd simultanously. This implis th formulation of th mission-basd prmits mart as a LCP. 9
2.3 Gnral structur of th whol modl Th gnral structur of th modl is shown in Figur 1, whr z rprsnts th opration profit of ach company [1,...,], x th dcision variabls and th st of constraints h and g ar particularizd for ach company. Figur 5. Mart quilibrium. Optimization Program of Firm 1 Optimization Program of Firm Optimization Program of Firm ( ) maximiz : z y 1 1 ( ) maximiz : z y ( ) maximiz : z y subjct to 1 : hj g 1 subjct to : h j g subjct to : h g j Pric-m(y) lctricity Mart Prmit amount Q mission Prmit Mart Th prvious mart quilibrium problm can b statd in trms of an LCP schm by mans of stting th first ordr optimality Karush-Kuhn-Tucr conditions associatd to th st of maximization programs (s figur 6). Figur 6. Mart quilibrium as a linar complmntarity problm. 1
11 KKT Optimality Conditions of Firm 1 KKT Optimality Conditions of Firm KKT Optimality Conditions of Firm mission Prmit Mart lctricity Mart Pric-m(y) Prmit amount Q ( ) ( ) g g h, y, y, y, 1 1 1 1 1 j 1 j 1 1 1 1 1 y μ μ λ μ λ μ λ λ L L L L ( ) ( ) g g h, y, y, y, j j y μ μ λ μ λ μ λ λ L L L L ( ) ( ) g g h, y, y, y, j j y μ μ λ μ λ μ λ λ L L L L In figur 2, L rprsnts th Lagrangian function of th corrsponding optimization problm and λ and μ rprsnt th dual variabls associatd to th st of h and g constraints rspctivly. Th optimality conditions can b writtn down as thr sts of quations. Th first on cancls th gradint of th Lagrangian function with rspct to th dcision variabls x. Th scond st (th gradint of th Lagrangian function with rspct to th dual variabls λ) coincids with th h quality constraints thmslvs. Th third on is formd by th complmntary slacnss conditions associatd to th inquality constraints g. As a rsult of th modl assumptions, grouping togthr all companis systm of quations lads to an LCP. Th whol modl, that is a CV-mart sub-modl plus a Nash-xpansion planning sub-modl, subjct to th nvironmntal rstriction of th prmits mart, dfins th opration, th invstmnt, prmits purchass and pricing of both lctricity and prmits that simultanously satisfy th first ordr optimality conditions of all firms and that of th prmits mart. A full mathmatical structur of th modl is prsntd in Lapidra t al (23).
3. An application to th Spanish lctricity sctor Th modl dscribd abov has bn usd to simulat th impact of th carbon trading mchanism on th Spanish lctricity mart. First, a gnral cas study is shown, and thn th impact of th diffrnt assignmnt mthods is prsntd. 3.1 Gnral cas study Th gnral cas study analyss th xpansion of th Spanish lctricity systm for th nxt tn yars (25-214). Th six xisting gnrating firms hav bn considrd (although thir nams hav bn omittd), plus othr possibl nw ntrants. Th invstmnt capacity of th firms has bn limitd to a diffrnt numbr of powr plants to b built in a crtain priod of 5 yars. All th powr plants blonging to th gnrators hav bn aggrgatd into on group pr tchnology and firm, in ordr to rduc th siz of th modl. Th tchnologis considrd hav bn nuclar (NCL), ful (FO), natural gas (GN), gas combind cycls (CCGT), domstic coal (HLL), importd coal (CI), brown lignits (LGP), blac lignits (LGN), rgulating hydro (RG), run-of-th-rivr hydro (FLU), and pumping units (BOMB). In addition, othr tchnologis hav bn considrd which may b installd in th futur: suprcritical coal (CSC), biomass (BIO), wind (OL), and advancd nuclar (NLCAV). Ths tchnologis hav bn chosn sinc thy ar, according to xprts, th most lily to ntr into th systm du to thir closnss to commrcial status. In fact, biomass and wind nrgy alrady participat in th systm, although in a vry small proportion. Suprcritical coal is considrd by many as th 12
way to us coal in a clan mannr, whras by advancd nuclar w nam th nxt gnration of nuclar powr plants which is alrady dvlopd in som countris. Th charactrisation of ths futur tchnologis has bn basd on th STRIS databas (C, 24). Th paramtrs for all tchnologis ar shown in Tabl 1a, 1b and 1c of th Appndix. As for th carbon missions mart, th amount of prmits usd has bn th total amount stablishd by th Spanish National Allocation Plan (RD 6/25), that is, 16 Mt. Howvr, as said bfor, th Plan only covrs th priod 25-7. From 28, th Govrnmnt nvisags that missions should not b highr than thos of 199 incrmntd in a 24%, so th total amount of prmits from 28 to 214 will b 147.8 Mt. It has to b notd that this is th whol amount of prmits distributd among all sctors covrd by th Dirctiv. Howvr, only th lctricity sctor has bn modlld in dtail. Th rst of sctors ar much mor difficult to modl adquatly, bcaus of thir disaggrgation (thr ar many small CO 2 -producing facilitis, with vry diffrnt charactristics) and lac of data. Howvr, this sam disaggrgation allows to assum that thy will bhav as pric-tars in th missions mart, and thrfor thy may b modlld as a comptitiv fring by mans of a rsidual dmand function. This dmand function is th aggrgatd marginal abatmnt cost curv for all ths sctors in Spain, and has bn obtaind from th PRIMS modl (Capros t al, 21). Of cours, sinc th Dirctiv sts up an uropan prmit mart, allowing trad btwn countris, th xpctd rsults for th allowanc pric may b diffrnt than thos simulatd hr. On th on hand, th Spanish nrgy tchnologis and th 13
nrgy mix ar similar to th uropan avrag, so th marginal abatmnt costs curvs (which ultimatly dfin th pric of th allowanc) would b xpctd to b similar. Howvr, sinc th siz of th mart whn nlargd to an uropan scal will b much largr, abatmnt opportunitis may incras and thrfor th xpctd pric of th prmit should b lowr. Th problm is that this uropan mart has not bn dfind yt, sinc thr ar still som countris without a dfinitiv NAP (and thrfor, th total amount of prmits to b distributd in urop is unnown 2 ). Thrfor, w considrd it mor advisabl to simulat just th Spanish mart with no trad, assuming that th ral prmit pric may b somwhat lowr. Rgarding othr rlvant assumptions for th modl, th annual growth of lctricity dmand has bn st as an annual avrag of 3%, basd on th stimations of th Spanish govrnmnt (MINR, 22). Th slop of th lctricity dmand curv has bn st at 6 /MWh.MW. Also for th two largst firms a rsidual dmand curv slop has bn considrd of 1.3 /MWh.MW. Data from ths slops hav bn tan from Garcia-Alcald t al (22), whr a procdur for stimating thm is prsntd. 3.2 Assignmnt mthods Svral assignmnt mthods ar usually proposd concrning th allocation of carbon mission prmits, som of thm bttr and som of thm wors (s.g. Vstrdal and Svndsn (24), Böhringr and Lang (24) or Hasslnipp (23)). 2 It has to b rmindd that th Dirctiv dos not covr all carbon missions, and thrfor dos not qual th rductions imposd by th Kyoto Protocol. 14
Basically, prmits may b auctiond or grandfathrd (with combinations btwn thm), and in cas of grandfathring, also diffrnt options may b studid: basd on historical missions, basd on actual and xpctd missions, basd on nrgy producd, tc. All mthods hav bn analysd in this papr. Th mthod chosn by th Spanish govrnmnt is not a clar-cut on, rathr an intrmdiat btwn historical and xpctd missions. It should b notd also that th uropan Dirctiv dos not allow for auctioning in th first assignmnt priod (25-7), and th Spanish govrnmnt viws ar also against this option in a first stag. Thrfor, th auction option may b somwhat unralistic currntly. Howvr, w hav dmd it usful to also prsnt its rsults in ordr to provid som rfrnc for th othr mthods, and also bcaus it might b considrd an option for 28. It should also b rmindd that th only variabl affctd by th choic of th assignmnt mthod will b th arnings of th gnrating firms (and of cours public rvnus), givn that, if prfct comptition is assumd for th missions mart, th pric of th prmit and th amount mittd will not b affctd. 3.3 Rsults Th main rsults of th simulation ar shown in Tabl 2. Both th rsults of th simulation with and without CO 2 rstrictions ar shown in ordr to highlight th stimatd impacts of th Dirctiv. In this first tabl th lctricity pric, th mission prmit pric, amount of missions and amount of nw invstmnts ar shown. Non of thm dpnd, as mntiond abov, on th assignmnt mthod chosn so thy ar common for all of thm. 15
Tabl 2. xpctd lctricity and carbon prics, missions and invstmnt in CCGT (prics xprssd in constant 24) Yar Dmand lctricity mission missions Invstmnt in TWh pric c /Wh prmit pric Mton CO 2 CCGT MW /ton CO 2 Dir. No Dir. Dir. No Dir. Dir. No Dir. Dir. No Dir. 25 181.8 2.73 2.51 3.19-73.43 85.34 2444 26 186.51 2.74 2.51 3.48-74.62 89.69 3254 27 192.11 2.75 2.56 3.79-75.33 94.37 4148 28 197.85 2.83 2.6 6.15-69.97 98.12 6188 245 29 23.79 2.85 2.61 6.71-7.93 1.95 7219 982 21 29.9 2.87 2.61 7.31-72.16 13.88 8222 174 211 216.19 2.9 2.62 7.97-73.41 16.84 9254 2522 212 222.67 2.92 2.62 8.69-74.98 19.9 1255 333 213 229.32 3.11 2.62 13.94-7.72 112.85 12242 4173 214 236.2 3.16 2.62 15.19-72.37 115.49 13378 544 As may b sn, onc th missions trading rgim ntrs into forc, thr appars a pric for CO 2 missions, which rachs up to 15 /t for th priod considrd, incrasing stadily as dmand riss (what is consistnt with othr studis rsults). Part of this cost of th mission is incorporatd into lctricity prics, which incras mor than 2% compard with th situation without th Dirctiv. Carbon missions ar vry much rducd compard to th situation without Dirctiv, and in fact th lctricity sctor rducs mor its missions than othr sctors, rducing its shar of missions from th currnt 55% to a 46% in th first priod and to a 49% from 28. 16
Th Dirctiv also incntiviss th construction of nw CCGTs, up to 134 MW in 214, which ma up for th rduction in th us of coal powr plants as shown in Figur 3. No othr nw tchnologis ntr into th systm, basically bcaus th prmit pric is not nough to compnsat thir highr variabl costs (and in th cas of suprcritical coal, bcaus its significant mission rat is pnalisd). It has to b notd that no support masurs for rnwabls hav bn assumd in th futur, in ordr to isolat th ffcts of th Dirctiv. Figur 3. Shar of tchnologis undr th Dirctiv 1% 9% 8% 7% % 6% 5% 4% CCGT LGN LGP CI HLL RG FLU NCL 3% 2% 1% % 25 26 27 28 29 21 211 212 213 214 Th dcras in th us of coal is vry much slowr in th cas without CO 2 rstrictions, as shown in Figur 4, whr it is shown that suprcritical coal would b comptitiv without CO 2 rstrictions (installing som 25 MW in this cas). Figur 4. Shar of tchnologis without CO 2 rstrictions 17
1% 9% 8% % 7% 6% 5% 4% 3% CSC CCGT LGN LGP CI HLL RG FLU NCL 2% 1% % 25 26 27 28 29 21 211 212 213 214 Th pric of lctricity dpnds havily on th cost of CCGTs, sinc thy ar usually th marginal plants. A rduction in th cost of gas will man a largr invstmnt in this tchnology, and thrfor lowr prics for CO 2 mission prmits. Howvr, lowr costs may also man lowr arnings for gnrators, bcaus of th marginal pric systm alrady mntiond. Limiting th amount of prmits will incras vry much th pric of lctricity, spcially if invstmnt is limitd and thrfor nw carbon-rduction tchnologis may not countrbalanc th ffct. Th pric of th prmit also incrass, as wll as th arnings of th firms. An intrsting rsult is that gnrating firms arnings ar not ngativly affctd by th Dirctiv, in fact thy may vn incras bcaus of th ris in lctricity prics. This may b obsrvd by comparing thir arnings (masurd as nt prsnt valu (NPV)) with thos obtaind without th carbon trading mchanism in Figur 5 (arnings with th Dirctiv corrspond to grandfathring basd on historical 18
missions, sinc that is th critria closr to th ral on applid by th Spanish govrnmnt). Figur 5. Diffrncs in gnrating firms arnings (in M -24, nt prsnt valu for 25-214). 12 1 8 Without Dirctiv With Dirctiv 6 4 2-2 1 2 3 4 5 6 Othr This is xplaind by th marginal pric rgulation of th Spanish lctricity systm. Undr this rgulation, Spanish lctricity prics ar st by th most xpnsiv plant rquird to mt dmand. Thrfor, if th cost of this marginal plant incorporats th cost of th allowanc, th lctricity pric will ris, and this will bnfit all producrs, whthr thy hav to buy allowancs or not. Givn th larg amount of nuclar and hydro in th Spanish systm, this mans that thr is a lot of nrgy which is rciving this xtra mony, and thrfor th incras in firms arnings. Th incras is largr in thos firms with a biggr shar of non-carbon tchnologis, sinc thy ar not so affctd by th Dirctiv, but do profit from th highr prics. 19
As for th impact of th diffrnt assignmnt mthods, as said bfor, it affcts th arnings of gnrating firms and also public rvnus (which ar not xamind hr). Th rsults ar shown in Tabl 3. Tabl 3. Gnrating firms s arnings undr diffrnt assignmnt mthods (in M - 24, nt prsnt valu for 25-214) Grandfathring Firm Without Basd on Basd on Basd on Auction Dirctiv historical ral historical missions missions nrgy 1 669 7643 7548 7889 7396 2 7312 9512 961 8771 8424 3 1927 253 2467 1887 1985 4-63 23 313-32 -116 5 278 785 819 225 368 6-284 -226-38 -568-45 Othr -6-56 6-168 -116 TOTAL 158 2391 2176 17735 17537 As might b xpctd, firms arnings incras if grandfathring basd on missions is usd, but not whn grandfathring is basd on historical nrgy production, sinc thn thos firms with lowr nrgy rats hav to buy mor prmits and do that outsid th lctricity sctor, what xplains th rduction in total arnings for th sctor. Th auction mthod producs lss arnings, but still highr than th situation without Dirctiv (what is xplaind by th marginal pricing mthod alrady mntiond). But th most intrsting ffct is not th global amount of arnings, which is somwhat similar, but th distribution of ths arnings among firms. Big firms ar bttr off with both grandfathring options, sinc thy hav mor powr installd and mor historical missions, whil small firms, which will invst mor, will s thir arnings rducd bcaus of th nd to buy prmits. Whn assigning prmits basd 2
on nrgy, firms with nuclar or hydro ar also bnfitd with prmits not ndd, but rsults ar mor similar to thos from an auction. 4. Conclusions This papr has prsntd som stimations of th conomic impact of th uropan carbon trading Dirctiv on th Spanish lctricity sctor, by using a dtaild oligopolistic modl for simulating th xpansion and opration of its gnrating facilitis. Som of th rsults ar as xpctd: lctricity prics incras up to 2% compard with th non-rstrictd situation, th pric of th CO 2 mission is st around 15 /t, what is consistnt with similar studis, nw invstmnts in CCGTs ar vry much incntivisd, and grandfathring assignmnt mthods incras firms arnings, with a rdistribution of arnings dpnding on siz and tchnology mix. Howvr, othr rsults ar somwhat surprising to som: givn th marginal pric systm in plac in th Spanish lctricity sctor, th arnings of th gnrating firms incras bcaus of th implmntation of th Dirctiv. Spcially thos firms with a largr shar of carbon-fr tchnologis rciv a larg amount of windfall profits, that is, undu bnfits causd by th suddn chang of rgulation. Ths windfall profits ar not dsirabl from th rgulation point of viw, sinc thy ar an undu cost for th customr and ar not rally rwarding ntrprnurship but rathr th status-quo cratd by formr rgulation. Howvr, thy ar vry difficult to avoid, sinc that would imply som typ of pric control, or allowing pooling btwn lctricity firms in th prmit mart (what has bn xplicity prohibitd by th Spanish govrnmnt in 21
ordr to allow for comptition to xist in th mart), or somwhat rdistributing arnings among firms. A dbat is currntly bing hld in this issu. All ths rsults ar of cours snsitiv to th amount of prmits distributd, to th cost of tchnologis (spcially CCGTs), but also to invstmnt rstrictions: firms may not hav nough financial flxibility to chang thir gnrating tchnologis and this may crat a larg volatility in lctricity and prmit prics. This also xplains that nuclar may not provid short-trm solutions to th problm vn if th currnt nuclar moratorium is liftd, givn th larg invstmnts involvd. Thrfor, rsults show that thr ar larg implications for th Spanish lctricity sctor of th uropan Dirctiv, which may also imply a crtain dgr of intrvntion by th rgulators. This may wll rquir a furthr and mor dtaild analysis of th situation, introducing for xampl a bttr tratmnt of th uncrtaintis ahad, of th invstmnts rstrictions, or of othr dcision paramtrs othr than profit maximization which may bttr dscrib firms bhaviour. Also furthr intractions with th rst of th Spanish conomy and with th uropan missions mart should b xplord. It has to b rmindd that in a short tim th NAP has to b rvisd for th nxt 28-212 priod, so all ths issus ar rally rlvant at this momnt. Acnowldgmnts Th authors ar gratful to Fundacion BBVA and to th uropan Commission (Contract 4.13/C/2 4/22) for thir conomic support to this wor, and also to two anonymous rfrs for thir constructiv commnts which hav gratly improvd this papr. Th usual disclaimr applis. 22
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Appndix Tabl 1a. Paramtrs for currnt thrmal powr plants Firm Tchnology Linal Quadratic Installd CO 2 variabl cost variabl cost powr mission rat cur/mwh cur/mw 2 h MW t/mwh 1 NCL-1 331.2 3358 HLL-1 153.41 121.95 CI-1 1563. 22.9 FO-1 4147.13 2337.78 GN-1 3937.35 83.79 CCGT-1 342.24 15.4 2 NCL-2 331.2 3641 HLL-2 1788.6 1462.96 LGP-1 1848.7 1469.99 LGN-1 1989. 11.93 CI-2 1382.2 1712.92 FO-2 4447 2.13 4.77 GN-2 472.16 1543.72 CCGT-2 395.21 12.4 3 NCL-3 331.3 739 HLL-3 1533.23 1498.9 LGP-2 1728. 583 1.27 FO-3 4147.74 447.76 GN-3 4225. 155.99 4 HLL-4 1884.6 544.9 LGN-2 1791.52 4.94 27
FO-4 3696.35 682.76 5 NCL-4 349. 165 HLL-5 1472.41 1588.92 CCGT-3 3997. 45.4 6 CCGT-4 395.32 8.4 Othr CCGT-5 366. 4.4 Sourc: Own laboration basd on CSN (1997) Tabl 1b. Paramtrs for currnt hydro powr plants Firm RG FLU BOMB Maximum Annual Avrag Maximum Rsrvoir powr inflows (GWh) running powr capacity (MW) powr (MW) (MW) (GWh) 1 315 1197 48 628 3 2 21 3785 52 149 515 3 85 25 25 28 9 4 475 324 55 34 5 5 27 352 5 6 Othr Sourc: Own laboration basd on CSN (1997) Tabl 1c. Paramtrs for nw tchnologis Tchnologis Linal variabl Quadratic Invstmnt CO 2 mission cost variabl cost cost rat cur/mwh cur/mw 2 h UR/W t/mwh CCGT 214 466.4 28
NCLAV 31 225 BIO 244 152 CSC 153 992.8 OL 96 Sourc: Own laboration basd on uropan Comission (24). 29