Elecriciy Markes Working Paers WP-EM-24 Price Formaion and Marke Power in he German Wholesale Elecriciy Marke in 2006 Hannes Weig and Chrisian von Hirschhausen Ocober 2007 Dresden Universiy of Technology Chair for Energy Economics and Public Secor Managemen
Price Formaion and Marke Power in he German Wholesale Elecriciy Marke in 2006 Hannes Weig and Chrisian von Hirschhausen Corresonding auhor: Hannes Weig Dresden Universiy of Technology Dearmen of Business Managemen and Economics Chair of Energy Economics and Public Secor Managemen D 01069 Dresden Germany Phone: +49- (0)351 463-39770 Fax: +49-(0)351-463-39763 Hannes.Weig@u-dresden.de Absrac: From 2002 o 2006, German wholesale elecriciy rices more han doubled. The urose of his aer is o esimae he rice comonens in 2006 in order o idenify he facors resonsible for he increase. We develo a comeiive benchmark model, aking ino accoun ower lan characerisics, fuel and CO 2 -allowance rices, wind generaion, cross-border flows, uni commimen and sar-u condiions, o esimae he difference beween generaion coss and observed marke rices for every hour in 2006. We find ha rices a he German wholesale marke (EEX) are above comeiive levels for a large fracion of he observaions. We verify he robusness of he resuls by carrying ou sensiiviy analyses. We also address he issue of revenue adequacy. Key words: elecriciy, Germany, marke ower JEL-code: L13, L94, D 43
1 Inroducion Marke ower is a significan issue for resrucured elecriciy markes around he world. A he same ime, quesions abou resource adequacy of invesmens in generaion have resurged boh in he U.S. and in Euroe, driven by concerns abou suly securiy. The German elecriciy marke has undergone significan changes in he las decade, ye he scienific discussion abou he aroriae marke design is sill in is infancy. Since he firs EU liberalizaion direcive 96/92/EC was romulgaed, Germany has aken almos a decade o address criical issues such as nework ariff regulaion and marke monioring. Since 2006, he newly esablished regulaor ( Bundesnezagenur ) has ublished cos-based revisions of ransmission and disribuion nework ariffs, and is now considering alernaive insrumens of congesion managemen, cross-border rading, ec; incenive regulaion should be oeraional by 2009. Curren oliical discussion has begun o focus on he generaion secor, esecially since average so rices a he Euroean Energy Exchange (EEX) rose by almos 125% from 2002 o 2006. However, a rice increase is no roof of malfuncioning markes or marke ower abuse; during he same eriod fuel rices rose significanly and he Euroe s emissions allowance rading scheme was imlemened. On he oher hand, he oligoolisic srucure of Germany s generaion marke aricularly lends iself o abuse, wih a duooly conrolling over 55% of marke share, and he larges four firms owning almos 85%. This aer analyzes he level of comeiion in he counry s wholesale elecriciy markes, by comaring he observed rices wih esimaed coss and marke clearing rices under he hyohesis of erfec comeiion. We develo a comeiive benchmark model esing he observed EEX marke rices for 2006. We hyohesize ha he oligoolisic srucure of elecriciy generaion leads o significan rice mark-us when comared o shor-erm marginal coss. In he nex secion, a survey of marke ower analysis in oher counries (mainly he US. and he UK) and he mos recen sudies on Germany are rovided. Secion 3 resens he comeiive benchmark model and inroduces he daa. The analysis is based on ublicly available daa on elecriciy rices, generaion caaciies and coss, wind inu, and cross-border flows for 2006. We find ha he observed rices exceed marginal coss esecially in eak load siuaions. We also resen he earned revenues of generaors in 2006 based on he model s so marke srucure. The resuls are confirmed by sensiiviy analyses ha accoun for lan availabiliy and rice uncerainy. We conclude ha marke ower is an influenial feaure of Germany s elecriciy markes, and should be addressed by more comeiion-oriened marke design. 2 Lieraure review on marke ower 2.1.1 Inernaional emirical lieraure Marke ower normally is defined as he abiliy o rofiably aler rices away from comeiive levels (Mas-Collel e al. 1995,. 383). Thus one of he main quesions of esimaing marke ower abuse is 2
o deermine he righ aroximaion of comeiive levels. The modeling aroach used is generally referred o as comeiive benchmark. Comlex aroaches like Courno or Suly Funcion Equilibria ofen use i as a saring oin or as addiional informaion o classify he model resuls. 1 The chief goal of he benchmarking aroach is o esimae a comeiive suly funcion in erms of marginal coss. In a fully comeiive marke no layer can influence he clearing rice; hus he simulaed suly funcion in combinaion wih a given demand level yields he comeiive benchmark. Arranging he lans according o increasing marginal coss yields he comeiive suly curve and he difference beween simulaed and observed marke rices allows quanifying he exen of marke ower. Sof (2002,. 129) shows ha marginal cos ricing suffices o cover he caial cos of invesmen, because rice sikes will occur in eriods of shorages. An in-deh discussion of he issue is rovided by Hogan (2007), Cramon and Sof (2006), and Joskow (2007). A his oin, we noe ha he marginal coss should se he comeiive rices when he marke is characerized by overcaaciy. When monoolisic, ofenimes verically inegraed elecriciy comanies redominaed, here was neiher room nor need for marke ower analysis. The resrucuring of he Norh American and Briish elecriciy markes oened he way o rigorous marke ower analysis. Wolfram (1999) was among he firs o aly a comeiive benchmark analysis o he elecriciy marke of England and Wales. She found significan markus during he observed eriod covering 18 monhs in 1992, 1993 and 1994, alhough he generaors were no aking full advanage of he inelasic demand as oligooly models redic. Borensein, Bushnell and Wolak (2002) and Joskow and Kahn (2002) used he comeiive benchmark aroach o analyze he California marke. Boh found ha in summer 2000, observed rices differed from he comeiive benchmark rice levels which could no be exlained by load, imors, gas rices or NO x -allowance rices. Mansur (2001) underook an analysis of he PJM marke calculaing a demand-weighed Lerner index of 0.293, an indicaor of significan marke ower abuse. A drawback of comeiive benchmark analysis is he necessary simlificaion when esimaing he suly curve. Elecriciy markes are highly comlex and access o informaion is generally sarse; herefore, models make assumions ha may influence he oucome. Tyically he simulaion is saic neglecing sar-u and shu-down coss or minimum load consrains. Missing informaion abou lan ouages may comound he oucome. Also, he grid is no generally considered a marke comonen. Thus, nework congesion which can lead o marke rices above marginal coss is ignored. Harvey and Hogan (2002) underook a sensiiviy es of comeiive benchmark analysis by reroducing he resuls and esimaing he imac of varying assumions, and concluded ha he differences obained by simulaion could resul from he real-world consrains ha were omied from he model. 1 For a comrehensive overview abou differen aroaches of measuring and modeling marke ower see Twomey e al. (2004). 3
2.1.2 German emirical lieraure The wholesale elecriciy marke in Germany is dominaed by four comanies owning abou 85% of convenional ower lan caaciy. The German Carel Office assumes a dominan duooly consising of E.ON and RWE owning abou 60% of generaion (Bundeskarellam, 2006). Given his oligoolisic srucure, he quesion arises wheher he observed marke oucomes reresen comeiive behavior or wheher marke ower is alied. Müsgens (2006) firs simulaed a comrehensive marginal cos model of he German marke for he eriod of June 2000 o June 2003. He used a linear oimizaion model o esimae he comeiive marke rices. Saring in 2000 he observed and modeled marke rices coincided unil fall 2001, followed by a break leading o a divergence beween hem ha lased unil he end of he observaion eriod. He assumed ha sraegic comany behavior and learning effecs were he main reasons for he observed differences. Nex, Ellersdorfer (2005) used a wo-eriod Courno model o sudy he imac of long-erm conracs on he oligoolisic model. A comeiive benchmark used as well also concluded ha a significan difference beween modeled and observed marke rices exised. In a more recen sudy, Schwarz and Lang (2006) analyzed German elecriciy rices by esimaing he imac of fundamenal rice comonens such as fuel rice develomen and allowance rices. They found ha from 2000 unil 2005, rising fuel rices and in 2005, allowance rices were he major rice influencers. However, saring in 2003, he imac of marke ower increased and herefore influenced rices. Our aer follows Schwarz and Lang (2006) by exending he analysis o 2006. The Secor Inquiry issued by he Euroean Commission (2007) adds a oliical view o he marke ower debae. Mos of is conclusions are alicable o Germany: wholesale markes show a high degree of sulier concenraion; verical inegraion is a dominan facor in many markes; inernaional rade is insufficien o rovide ressure on domesic roducers; here is a high degree of inransarency; rice formaion on elecriciy markes is comlex; and consumers have lile confidence in he comeiiveness of hese markes. Based on he Secor Inquiry, London Economics (2007) carried ou an in-deh analysis using realworld daa and confirmed ha he German wholesale elecriciy marke faced mark-us of u o 50% in he as few years. Furhermore an analysis of earned revenues revealed ha he wo larges German comanies would have earned 7 bn. from 2003 ill 2005 which is consider sufficien for covering invesmen and sar-u coss by London Economics. Oher sudies of Germany s comeiiveness have emloyed sraegic or economeric aroaches. Zachmann (2006) comared he German and Briish elecriciy markes using Markov Swiching, concluding ha he Briish marke had a closer relaion o marginal coss. Kemfer and Traber (2007) alied a sraegic model of he German elecriciy secor o combine marke ower and climae olicy analysis o find ha he German wholesale marke aained full comeiion. Hirschhausen and Zachmann (2007) esed he imac of emission allowance ricing on elecriciy wholesale rices in Germany. Based on an error correcion model and an auoregressive disribued lag model hey found 4
ha he rice for emission allowances is assed hrough asymmerically: allowance rice increases are ranslaed ino elecriciy rice increases more raidly han decreases. However, he imac of marke ower on rice formaion is no unilaerally acceed. General elecriciy marke analyses of Germany wih resec o marke ower are resened by Weber and Vogel (2007) and Ockenfels (2007a). These and oher auhors agree ha he lack of full informaion in he emirical model aroaches is viewed as a source of unreliabiliy. Due o a see meri order close o eak caaciy, he imacs of incorrec availabiliy or rice assumions can roduce large, absolue errors. In addiion he non-linear comlexiy of elecriciy markes wih many exernal imac facors (wind seed, emeraure, and echnical resricions) conribue o he difficuly of designing a fully realisic model. Swider e al. (2007) show hese issues exemlary for exising model aroaches and secific ime eriods. Like Harvey and Hogan (2002) hey show ha every model has some level of uncerainy and hus will roduce a range of ossible oucomes. Melzian and Ehlers (2007) sudied he ricing mechanism a he EEX, and concluded ha he srucure of he German marke makes EEX rices an imroer benchmark. They argue ha since rice formaion a he EEX is mainly driven by missing or excess caaciy of forward conracs, he rice canno be considered as sysem marginal rice. Ehlers and Erdmann (2007) also analyzed he EEX ricing formaion and concluded ha he raded volumes and suly and demand curves do no allow a significan rice maniulaion. We assume ha EEX rices ac as he benchmark for mos bilaeral and long-erm rades in Germany s elecriciy marke because i is he only ransaren rice available. The roblem of fixed cos covering and shor-erm marginal coss has been addressed by Müller (2007) and Ockenfels (2007b). Müller simulaed a simlified elecriciy marke wih base, mid and eak load unis o esimae he revenues each lan ye earns in a comeiive marke based on shorerm marginal coss. He concluded ha in an oimal marke segmenaion wih resec o insalled caaciy, even base load lans will no cover heir fixed coss. Ockenfels (2007b) argues ha under comeiive condiions, marke rices above marginal coss are ossible and necessary o cover fixed coss. Whenever demand exceeds available caaciies, he marke rice is se according o consumers willingness o ay. Due o he low elasiciy in elecriciy markes his can lead o significan mark-us on marginal coss. We noe, however, ha his siuaion did no revail in 2006 since he German elecriciy marke was subjec o overcaaciies. 2 Secion 4.3 of our aer discusses fixed cos covering in more deail. 3 Model and Daa This secion describes he aroach o he comeiive benchmark analysis and he daa used, he objecive being o derive esimaes for he rue marginal coss which are hen comared wih he rices a Germany s wholesale elecriciy marke EEX. The model simulaes a wholesale marke in which all 2 In 2006, overall convenional caaciy was 103 GW, wih a sysem eak load of 86.2 GW. A his eak, he marke had surlus caaciies of 8.4 GW in addiion o 7.9 GW sysem reserves and an exor surlus of 2.1 GW (VDN, 2006). 5
demand is cleared via a single marke rocess. However, only abou 20% of oal consumion is raded via he EEX. Since he EEX is he only ublic source available, we assume he EEX so marke acs as benchmark and as a marker rice for OTC rading. Demand (load) daa is rovided by UCTE for each hour in 2006. We assume ha rading is a comeiive aciviy, so ha only generaors exercise marke ower. 3.1 Model formulaion The model is designed as a cos-minimizing aroach wih a given hourly demand level d ha mus be saisfied: min coss = ( c g ) +,, saru (1) s.: d = g energy balance (2) g min on g g max caaciy consrain (3) The model minimizes he oal generaion coss consising of he sum of marginal generaion coss c and he necessary sar-u coss (saru). The generaion g of each lan mus remain wihin he minimum and maximum caaciy consrains in case he lan is oeraing. The saus of a lan is deermined wih he binary condiion variable on. The oal sum of generaion mus equal he exernally defined demand d in any considered hour. The imeframe for each model run is one monh. Nework consrains are no considered and hus losses are no aken ino accoun. Since fossil lans are resriced by hermal condiions, hey canno be urned on/off wihin seconds. According o ye of lan, sar-u can ake a few minues (small gas urbines) u o several days (nuclear). Therefore, i is necessary o decide on he saus of a lan before he acual demand siuaion occurs. Following Takrii e al. (1998), we define a minimum online and offline consrain: { + L 1 T} on 1 τ on on, τ = + 1,...,min, { + l 1 T} on 1 τ on 1 on, τ = + 1,...,min, online consrain (4) offline consrain (5) Since he ime inerval referred o is one hour, only he offline consrain has been used, assuming ha each lan can be shu down afer one hour of oeraion. Nuclear lans are assumed o suly base load and herefore are mus-run lans ha canno be shu down. We assume ha gas urbines and hydro lans are able o go online wihin an hour. Therefore, no searae consrains are necessary. Coal, seam and CCGT lans are modeled wih secific sar-u imes l according o Schröer (2004,. 39). Sar-u coss are based on DENA (2005,.280). These coss are added as a cos block saru in he eriod of he sar-u. As Germany has a large fracion of combined hea and ower roducing lans (CHP) aricularly in he indusry secor, hese lans are reaed as mus run lans wih a secific minimum ouu level. We assume ha CHP lans mus run a leas 50% of heir maximum 6
elecrical caaciy in winer, 30% in sring and fall, and 20% in summer. A deailed hourly hea rofile is no used. The only way o sore larger amouns of elecriciy is by using hydro umed-sorage lans (PSP). In our model, PSPs can eiher demand elecriciy and fill heir sorage or use he sored energy and generae elecriciy. If hey run in um mode (PSP u ), 75% 3 of he consumed energy will be added o he sorage (PSP sorage ) and increase he demand level d of he energy balance. If hey run in generaion mode (PSP down ), he aroriae amoun of energy is aken from sorage and considered as normal generaion g in he energy balance: + 1 sorage 0,75* PSPu PSPdown PSPsorage PSP = + PSP u + PSP down g max PSP sorage equaion (6) firs caaciy consrain (7) PSP down P sorage second caaciy consrain (8) The model is imlemened in GAMS as a combinaion of a mixed ineger roblem for he uni commimen and an oimizaion roblem wih fixed binary lan condiion variables for he acual disach. 3.2 Generaion caaciy and demand level The hourly demand level for Germany (UCTE, 2007) ranges beween 75 GW a eak and 35 GW a off-eak imes. The German elecriciy marke is a winer-eaking marke wih significanly less demand in he summer monhs. Generaion caaciy is characerized by overcaaciy. Toal generaion caaciy is abou 120 GW including renewable energy sources (VDN, 2005). The basic lan lis we obained from VGE (2005, 2006) includes all convenional faciliies in Germany wih more han 100 MW generaion caaciies by lan and fuel yes. Available/insalled caaciy may differ according o weaher condiions, mainenance, or ouages, requiring adjusmens o reven an overesimaion of available lan caaciy and an underesimaion of rices in our simulaion. To accoun for hese effecs, seasonal availabiliy facors for each lan ye are used according o Hoser (1996) wih he highes level of availabiliy in winer monhs. Since our analysis is based on single hours, he generalizaion can lead o divergences in secific cases (e.g., a lan ouage of a large coal block). We defined a minimum running caaciy for each lan according o DENA (2004,. 280). Par of he available caaciy may be sold abroad and herefore can no be used o cover he German demand. Lack of ublicly available informaion resrics he ossibiliy o deal wih his issue direcly wihin he lan lis. Therefore, we calculaed he oal rading balance based on acual cross-border ower flows (ETSOVisa, 2007). 4 The resuling ne flow ino or ou of Germany is considered in he oal demand level. Thus when energy is imored, a orion of Germany s demand is covered by foreign lans, reducing he necessary amoun of domesic generaion and vice versa. However, he 3 Following Müller (2001), modern PSPs have an average efficiency beween 70 and 80%. 4 The values for cross-border flows have been comleed using ublicly available informaion from he four TSOs and Nordel. 7
modeled rices reresen he uer bound in cases of ne exors, since lans above marke rice can be used for exors, and a lower bound in cases of ne imors since a foreign generaor can se he marke rice in Germany. Germany has a large amoun of renewable energy, in aricular wind (19 GW in 2006) and he acual demand level o be saisfied by convenional lans varies considerably. Therefore, we reduced demand by calculaing he hourly wind inu for he analyzed days. 5 We negleced oher renewable sources like solar and bio mass due o heir relaively small insalled caaciies. 3.3 Cos esimaes and sar-u condiions To esimae he marginal cos curve ( meri order ) for elecriciy generaion fuel ye and fuel rices are needed. The efficiency of each lan is esimaed using he age as a roxy: for coal, lignie, oil/gas fired seam lans, CCGT lans and gas urbines, he link beween he age and he efficiency are aken from Schröer (2004). Nuclear lans are assumed o have an average efficiency of 33% (Müller, 2001) and hydro lans have 100% efficiency. Fuel rices for coal, oil and naural gas are based on wholesale rice levels of reference, hus we do no consider ransoraion coss or ransmission fees. 6 The rice for seam coal is based on rices for inernaionally raded coal a ARA, daily naural gas rices are aken from he Duch marke TTF, and oil rices are daily Bren rices. For nuclear lans, fuel coss of 3 /MWh are assumed leading o generaion coss of 9 /MWh. 7 As here exiss no global marke for lignie, exracion coss of 1.76 /GJ as shown in he high rice scenario in Schneider (1998) are used; his figure over- raher han underesimaes he real coss. Hydro lans are assumed o have no fuel coss. Hydro lans ac as rice akers like every oher lan ye. PSPs are modelled as eiher demand or generaors and hus have no exernal marginal coss. The resuling imac on he rice level is obained by oimizing umed sorage usage and accouning for he generaion coss needed o relenish he sorage (see Secion 3.1). In addiion o fuel coss an ulif aymen for variable oeraing exenses is used for each lan ye (EWI, 2005): coal lans have addiional exenses of 2 /MWh, nuclear 3 /MWh, gas-fired 0.5 /MWh, and hydro lans 1 /MWh. Wih he inroducion of Euroe s emission allowance rading scheme in 2005 an addiional cos elemen has o be considered when esimaing elecriciy rices. Allowance rices can be accouned for as ooruniy coss of roducion. Therefore, we calculaed lan-secific CO 2 -emissions based on efficiency and lan ye following Game (2004). The emissions are valued wih he allowance rice aken from EEX (2007b) and added o he fuel and oeraion coss. 5 The acual energy inu deends on wind seeds and is ublished on an hourly basis by he four German TSOs. 6 Due o he volailiy of wholesale rices aricularly for oil and naural gas, generaors are execed o sign conracs for heir fuel suly. The ricing deails of hese conracs are no ublicly available. We assume ha wholesale rices are sufficien o reflec he average rice level. However, his can lead o divergences for secific lans. 7 Nuclear is no he marginal sulier in he relevan eriods, so ha he esimae of is marginal coss does no change he resuling rices. 8
The marginal generaion coss c of a lan in any considered hour consis of he fuel coss based on lan efficiency η and fuel rice, oeraing coss, and ooruniy coss for emissions based on lansecific CO 2 emissions and he allowance rice a he EEX: 1 c = fuelrice + oeraion coss + emissions CO2 rice marginal coss of generaion (9) η 4 Resuls and sensiiviy analysis We comare he modeled marke rices wih observed riced a he EEX for all hours of 2006, obaining markus, wihheld caaciy and earned revenues for fixed coss coverage. To esify he resuls wo sensiiviy analyses are carried ou. Firs he uncerainy regarding exac fuel rices is considered by increasing gas and oil rices (which mainly influence eak unis). Second, lan availabiliy is reduced o esimae he imac of uncerainy abou echnical and exernal resricions on generaion srucures. 4.1 Marke ower and rice mark-us The basic model aroach uses welve runs (one for each monh) o simulae he wholesale marke in 2006 and find he comeiive marke oucomes. The simulaed rices and he EEX rices behave similarly wih a clear segmenaion beween off- eak and eak rices. However, in off-eak eriods, EEX rices ofen dro below marginal generaion coss and someimes even reach zero, whereas he model rices reach a level, reresening coal and lignie fired base load lans. In general, rices below marginal coss are exlained by sar-u condiions since he emorary shu-down of a base load lan can become more exensive han mainaining oeraions wihou revenues. Because our model is based on erfec knowledge, we noe ha he rice difference may be due o asymmeric informaion (e.g., bidders wrong execaions abou marke condiions. Furhermore he model includes emission allowance rices as ooruniy coss whereas bidders may vary beween full, arial and no cos as hrough. Model rices in eak rice eriods were generally below he observed rices a he EEX. Figure 1 shows he model rices and he observed rices ordered from highes o lowes EEX rice. The resuls clearly show ha high EEX rices generally do no have an equivalen high comeiive rice counerar. In he off-eak segmen EEX rices and model rices are beween 30 and 40 /MWh. However, EEX rices decrease owards zero while modeled rices end owards a coal lan equivalen. In he mid-rice segmen he EEX rices increase from 40 o abou 60 /MWh while he model rices exhibi volailiy ranging from 28 o 65 /MWh wih a high number of rice combinaions ha diverge srongly from each oher. This rend coninues for eak rice siuaions where EEX rices increase owards heir yearly eak of more han 2000 /MWh while model rices remain beween 40 and 95 /MWh. However, in eak eriods, he comeiive rices in he model ended o be lower han EEX rices. The average rice in 2006 a he EEX is 50.79 /MWh whereas he model average is abou 11% lower 9
wih 45.28 /MWh. For he eak segmen (weekdays 8am-8 m), he difference is more sriking wih a model average rice of 52.31 /MWh (abou 30% below he observed average of 74.48 /MWh). For off-eak hours including holidays and weekends, he observed rices are lower wih an average of 38.23 /MWh comared o 41.54 /MWh in he model. Focusing only on weekdays, his divergence is reduced o 1.4 /MWh or 3%. Using he underlying demand, he oal exenses a he EEX rice level are 3.6 bn higher han in he model. 4.2 Caaciy wihheld To esimae he difference in quaniies beween he model and he EEX, we calculaed he caaciy wihheld for weekday hours 8am- 8m (off-eak and weekend hours show a high degree of rices below marginal generaion coss). Furhermore, marke ower abuse is execed o occur mainly when demand is close o he caaciy limi. To obain he wihheld caaciy all available lan caaciies wih marginal coss below he EEX rice bu no oeraing in he corresonding modeled soluion for each hour are summed u. In 2006, he average amoun of caaciy wihheld during eak hours is abou 8 GW, bu i varies hroughou he year. Figure 2 Shows ha he average values in he firs wo monhs of around 9 GW, he ga hen narrows significanly from March unil June, even reaching an average of -2 GW in Aril. Afer July, he caaciy wihheld again increases, wih average values beween 8.5 and 14 GW. The high number of values above 10 GW indicaes he exisence of sraegic comany behavior. Figure 1: Price Comarison Model and EEX 10
Figure 2: Caaciy wihheld during workday eak hours (8am 8m) 30 000 20 000 10 000 MW 0-10 000 Jan Jan Jan Feb Feb Feb Mar Mar Ar Ar Ar May May Jun Jun Jun Jul Jul Aug Aug Aug Se Se Se Oc Oc Nov Nov Nov Dec Dec -20 000-30 000 4.3 Fixed cos coverage One furher oin of ineres is how comeiive marke oucomes ranslae ino revenues for fixed cos covering. Pricing is based on shor-erm marginal coss; herefore, comanies are execed o cover heir invesmen coss when generaors wih higher coss se he marke rice or caaciy is lower han demand, and boh siuaions can resul in rice sikes ha allow comanies o earn rens above heir generaion coss. As menioned, he German marke is frequenly subjec o overcaaciies. Thus, he rice level is execed o give no signal for new invesmens. The earned revenues do no ake ino accoun forward rading. Thus, he values reresen so marke based resuls. Fehler! Verweisquelle konne nich gefunden werden. shows he calculaed rens generaors earned according o he model. As noed above, he Euroean-wide emission allowance rading scheme includes a grandfahering mechanism ha allows he revenues from ooruniy ricing of allowances o be included in fixed cos covering. Hence, our model mus incororae boh revenues for each lan ye: one ha includes allowance rices as marginal generaion coss and one ha excludes hem. We use average invesmen coss as he benchmark. We can calculae an annuiy assuming average overnigh coss er MW, an ineres rae of 7%, and 40 years duraion for base and 25 years for eak unis. Only he values including allowance coss are relevan for esimaing marke comeiiveness. They reveal ha under modeled comeiive condiions, only nuclear lans can cover heir fixed coss, under EEX rice calculaions, boh nuclear and coal lans can cover heir coss, and in boh scenarios, eak load lans canno cover heir coss. 8 The resuls indicae ha no addiional caaciies are needed in he osulaed overcaaciy of he German marke. 9 8 The ossible rens for eak unis may increase since oher marke segmens (e.g., reserve markes) are no considered. 9 Anoher issue is he imac of he allowance rading mechanism on invesmen signals. The oliical inen is o foser invesmen in emission reducion mechanisms or ower lans wih low emission values like CCGT. However, he resuls o dae oin o an absence of invesmen aciviy. Due o he base load characer of mos coal lans and he grandfahering mechanism giving he larges bulk of allowances for free, he curren marke rices se a high incenive o inves in coal echnology raher han gas-fired unis. Based on he values for 2006, he curren sysem fails o fulfill he execed oliical objecives. 11
However, he resuls do no ermi us o conclude emirical which mechanism (comeiive sysem or he EEX marke) is adequae for fixed coss covering. Due o he long erm invesmen characer of ower lans, imorance of forward conracs, fuel rice variaions, exisence of oional markes like reserve markes, and he uncerain furher develomen of he emission allowance sysem in Euroe, consisen resuls regarding he issue of caaciy financing can only be answered wih long erm analyses. Table 1: Annually earned revenues for fixed cos covering er insalled MW in 2006 Plan Tye Nuclear (surlus) Lignie (surlus) Hard coal (surlus) Seam (surlus) CCGT (surlus) Gas urbine (surlus) Comeiive Model Including Excluding allowance coss allowance cos 234 100 234 100 (+46 600 ) (+46 600 ) 64 900 167 100 (-47 600 ) (+54 600 ) 60 300 147 700 (-29 700 ) (+57 700 ) 600 2 200 (-85 200 ) (-83 600 ) 5 000 11 000 (42 200 ) (-36 200 ) 160 320 (21 300 ) (-21 100 ) EEX rice based Annuiy of Including Excluding Invesmen allowance coss allowance cos cos 10 271 800 271 800 (+84 300 ) (+84 300 ) 187 500 114 500 216 600 (+2 000 ) (+104 100 ) 112 500 110 200 197 600 (+20 200 ) (+107 600 ) 90 000 1 700 3 300 (-84 100 ) (-82 500 ) 85 800 14 400 20 400 (-32 800 ) (-26 800 ) 47 200 70 230 (-21 400 ) (21 200 ) 21 450 4.4 Sensiiviy Analysis All model aroaches are subjec o simlificaions, assumions and mahemaical resricions. Furher, emirical analyses are affeced by missing informaion and ossible daa errors. We underook wo sensiiviy analyses o es he robusness of he obained resuls. Firs, he fuel rice level is varied by increasing rices for gas and oil by 10%. This should lead o an increase in eak rices when CCGT, gas urbines and oil- or gas-fired seam lans se he marke rice, while off-eak rices are unaffeced. Second, we varied ower lan availabiliy. Due o a lack of hourly availabiliy values only seasonal facors are used, which may misinerre he real availabiliy due o high emeraures, low waer levels or lan ouages. 11 The basic availabiliy values from Hoser (1996) are alered by reducing he winer availabiliy by 2%, he inermediae values by 3% and summer values by 4%. Table 2 shows he available caaciies in each season comared o he corresonding values a monhly eak load of 2004 (VDN, 2005). The imac of he changed fuel rices is only eviden during eak load siuaions when he according lan caaciies are needed. During hese imes he rice level slighly increases. The average marke rice increases o 46.54 /MWh (abou 8% below EEX rices); average eak rices are 2.5 above he base case and hus sill 26% below he observed ones. The imac of reduced lan availabiliy is 10 Nuclear lans are assumed o have overnigh cos of 2500 /kw, lignie 1500 /kw, coal 1200 /kw, seam 1000 /kw, CCGT 550 /kw, and gas urbines 250 /kw. 11 Ockenfels (2007a, b) discusses his oic in deail. Oher oenial model limiaions like sochasiciy, asymmeric informaion, and ooruniy ricing of cross-border ransacions and hydro lans are no considered in our sensiiviy analysis. 12
more disincive. During off-eak and mid-load eriods, he difference is raher small because he remaining caaciy is sill sufficien o kee a moderae rice level. During eak siuaions he rices are above he basic model resuls, aricularly in winer and summer monhs. This effec can be exlained by he see sloe of he meri order close o maximum caaciy in combinaion wih saru condiions ha lead o rices above marginal coss. On average a marke rice of 48.74 /MWh (4% below EEX rices) can be observed. Average eak rices increase o 59.55 /MWh (20% below observed rices). In boh sensiiviies he off-eak rices are lile affeced. However, even he reduced caaciy is sill sufficien o saisfy demand, hus no caaciy ren for eak unis can be execed. The average quaniy ga in eak hours is reduced o 6.7 GW in he fuel rice variaion scenario and o 5.8 GW in he availabiliy variaion scenario. The monhly aern remains similar o he base case wih average values above 10 GW in he second half of 2006 for boh sensiiviies. The adjusmens do no aler he obained resuls of he revenue analysis since he revenues of eak and coal unis are sill below fixed coss. Comaring he basic model wih he sensiiviy analyses and EEX rices shows ha he observed rice duraion curve has higher rices in abou 4500 h in 2006 (Figure 3). On he oher hand, EEX rices are lower han he modeled rices in 3000 h. 12 All model variaions have rice sikes of more han 200 /MWh (in cases of he availabiliy analysis also 500 /WMh), which are comarable bu generally sill lower han he maximum rices a he EEX. The mid- o eak-rice region (beween 50 and 100 /MWh) also roduces ineresing resuls: a general rice divergence of abou 10 /WMh is observed for more han 2000 h. This difference is only slighly affeced by he changed arameers of he sensiiviy analyses. Since hese differences are observed in rice regions ha do no indicae caaciy shorages, he quesion o raise is weaher missing informaion and model simlificaion are solely resonsible for he divergence. Table 2: Available caaciies Winer Inermediae Summer Basic model Reduced caaciy Values a eak load (VDN, 2005) Fossil lans 83 350 MW 77 850 MW 74 170 MW Pum sorage 3 900 MW 3 650 MW 4 150 MW Fossil lans 81 430 MW 74 960 MW 70 320 MW Pum sorage 3 770 MW 3 460 MW 3 900 MW Reliably available caaciy 83 130 MW 79 500 MW 74 370 MW 12 These values corresond o he rice duraion curves and no o acual model/eex rice combinaions. 13
Figure 3: Price duraion curves 5 Conclusion This aer analyzes he inensiy of comeiion in he German wholesale elecriciy marke in 2006. We es he hyohesis of revious lieraure for 2000 hrough 2005 ha finds significan marke ower abuse. Based on a comeiive benchmark model aking ino accoun lan efficiencies, fuel rices, emission allowance rices, cross-border flows, sar-u condiions, and umed sorage, we esimae comeiive marke oucomes. These are below EEX rices for a large fracion of he observaions, leading o an average marke rice in 2006 of 45.28 /MWh ha is 11% below he average rice a he EEX and abou 30% lower during eak imes. These differences add o he addiional exenses of abou 3.6 bn a he 2006 EEX rice level comared o he model resuls. To esimae he resuling quaniy disorion, we calculae he caaciy wihheld in eak hours and find ha on average abou 8 GW of caaciy are no running in he model, alhough he generaors have marginal generaion coss below EEX rices. These values vary for he differen monhs wih average values above 10 GW in he second half of 2006. We verify he robusness of he resuls by carrying ou wo sensiiviy analyses: firs, fuel rices for eak unis (oil and gas) are increased by 10%, and second, lan availabiliy is reduced. The laer has a significan imac on he obained resuls, increasing he average marke rice o 48.74 /MWh. However, he rice duraion curve sill shows more han 2000 h wih rices abou 10 /MWh below EEX rices. The models share an inabiliy o reroduce he decrease of he EEX rice duraion curve o zero since he modeled rices are sill a marginal generaion cos level even in low demand offeak hours. The average quaniy ga is reduced o 6.7 and 5.8 GW resecively. However, in he second half of 2006 hese values consanly remain above 10 GW. 14
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