The value of intrad raday ay electr trici city ty trad ading ng – Evalua uatin ting situa uati tion-depend ndent nt opportunity tunity costs ts of flexible assets ts Timo Kern 2019 28.08.2019
Analysis lysis of Intraday day Trading ing in 2018 Absolut ute price ce deviat ation of of conti tinuo nuous us intrad raday ay trad ading ng and intrad aday ay auction Absolute price deviation of continuous intraday trading 0:00 >25 Representation of the absolute deviation from 4:00 20 mean continuous intraday and intraday auction in €/MWh price (ID3) and intraday 8:00 auction price in 2018 Time of day 15 Hardly any seasonal or 12:00 hourly dependency can be 10 recognized 16:00 Are the average revenu nues in 5 continuo inuous us intraday market 20:00 situa uatio ion-depend ndent nt? 24:00 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2 Month in 2018
Outline ine Methodolo odology y for dete termining mining average ge reve venu nues in the conti tinuou ous intrada day y market Factor ors influe fluenci cing g the leve vel l of of intrada day y reve venue opportu tuniti ties Concl clusion ion and use of of the findings dings 3
When is an electricit ricity y offering ing decision ion made in which ch market? Day-Ahead- Intraday- Continuous Intraday-Trading Auction Auction Zeit 12:00 15:00 16:00 0:00 Research topic: What revenue opportunities arise from continuous intraday trading? 4
Methodolog logy for deter termining ining reve venue opportunit unitie ies s in the he continu nuou ous s intraday day market Approach according to Weber et al.*: Relative Häufigkeitsdichte Prices in the continuous intraday market develop according to a stochastic process and price changes are normally distributed. Preis Approach ch Determina inatio ion n of the value lue of the intraday revenue nues by five parameters: 1. Distribution function of price changes (in Weber et al. Normal distribution) accor cording ding to to 2. The standard deviation 𝜏 the distribution Webe ber et al.*: *: 3. The expected value of the intraday price p at the time of evaluation 4. The marginal costs X 5. The amount of electricity offered 5 Weber et al.*: Berücksichtigung von Intraday-Optionalitäten im Rahmen der Redispatch-Vergütung
Methodolog logy for deter termining ining reve venue opportunit unitie ies s in the he continu nuou ous s intraday day market Relative Expected frequency density price Marginal costs Value of call option Price Approach ch Determina inatio ion n of the value lue of the intraday revenue nues by five parameters: 1. Distribution function of price changes (in Weber et al. Normal distribution) accor cording ding to to 2. The standard deviation 𝜏 the distribution Webe ber et al.*: *: 3. The expected value of the intraday price p at the time of evaluation 4. The marginal costs X 5. The amount of electricity offered 6 Weber et al.*: Berücksichtigung von Intraday-Optionalitäten im Rahmen der Redispatch-Vergütung
Methodolog logy for deter termining ining reve venue opportunit unitie ies s in the he continu nuou ous s intraday day market Relative Expected frequency density price Marginal costs Value of put option Price Approach ch Determina inatio ion n of the value lue of the intraday revenue nues by five parameters: 1. Distribution function of price changes (in Weber et al. Normal distribution) accor cording ding to to 2. The standard deviation 𝜏 the distribution Webe ber et al.*: *: 3. The expected value of the intraday price p at the time of evaluation 4. The marginal costs X 5. The amount of electricity offered 7 Weber et al.*: Berücksichtigung von Intraday-Optionalitäten im Rahmen der Redispatch-Vergütung
Assump mptio tion n Weber et al.: : Price changes es are distribu ibuted normall lly 8
Distrib ribut ution ion of of price changes from intraday aday auctio ion to to continu nuous ous intraday day tradin ing Consid nsideratio ion n of all l quarter- Empirical distribution hours of the year 2018 Normal distribution Superimposed normal Price differences show normal • distribution distributed characteristics only Relative frequency in strongly simplified assumption Distribution function from two • superimposed normal distributions represents empirical distribution much better Use of the superim imposed normal l distrib ibut utio ion n functio ion ID_Auction – ID3 9 ID_Auction = Price intraday auction ID3 = volume weighted average price of the last three hours in continuous intraday trading
Assump mptio tion n Weber et al.: : The expected ted value lue of continuous uous intraday aday trading ing corresponds nds to to the intrad raday ay auctio tion n value lue*. *. 10 * at the time of the auction (gate closure)
11 Impact ct of of daytim ime on expectatio ation of of intraday aday prices Time of of day 0:00 6:00 12:00 18:00 24:00 Consid nsideratio ion n of all l quarter- hours of the year 2018 3 Slight day/night price • in €/MWh dependence can be 2017 2 assumed ion iatio 1 ion in When looking at individual age deviat • quarter-hours, it is difficult uctio to identify dependencies 0 ID3 - ID_Auct Average Average, expected price -1 deviation of zero seems to be reasonable 2018 -2 -3 11
12 Impact ct of of day ahead residual ual load forecast st on expectation ation of of intraday aday prices Day ahead ad forecas ast resiudal iudal loa oad in GW <20 20-30 30-40 40-50 >50 Consid nsideratio ion n of all l quarter- hours of the year 2018 3 Higher expected continuous • ion in €/MWh intraday prices for low 2017 2 residual load forecast ion iatio 1 Lower expected continuous age deviat • intraday prices for high uctio residual load forecast 0 ID3 - ID_Auct Average Residual load dependent -1 average price deviation has impact on expected revenues 2018 of continuous intraday -2 trading -3 12
Assump mptio tion n Weber et al.: : The standar ard devia iation* ion* for each quarter ter-hour our product should ld be calcu cula late ted once a a month 13 * Of the deviation between the volume-weighted prices of the last three hours before close of trading and the prices of the intraday opening auction
Impact ct of of daytim ime on standar ard deviatio ation of of intraday aday prices Time of of day 0:00 6:00 12:00 18:00 24:00 Consid nsideratio ion n of all l quarter- hours of the year 2018 30 Slight day/night price • ion in €/MWh uncertainty can be assumed 2017 25 ion When looking at individual • iatio quarter-hours, it is difficult to d deviat 20 identify specific uncertainties uction of prices ard ID3 - ID_Auc 15 andar From empirical data it is not Stand reasonable to use specific standard deviations for 2018 10 specific day times 5 14
Impact ct of of day ahead residual ual load forecast st on standar dard devia iation ion of of intrad aday ay prices Day ahead ad forecas ast resiudal iudal loa oad in GW <20 20-30 30-40 40-50 >50 Consid nsideratio ion n of all l quarter- hours of the year 2018 30 High price uncertainty for • ion in €/MWh very low and high residual 2017 25 load forecasts ion iatio Low price uncertainty for • d deviat 20 moderate residual load uction forecasts ard ID3 - ID_Auc 15 andar Residual load forecast has Stand huge impact on price uncertainty of continuous 2018 10 intraday prices 5 15
Evaluati aluation on of of situ tuation ation-de depen ende dent reven enues es at conti tinu nuous ous intrad raday tradi ding ng Exe xempla mplary Biogas plant • Marginal costs: 60 €/MWh inve vesti tiga gati tion on • Electricity price in the intraday auction: 59 €/MWh • Average ge expe pect cted reve venues in High residual load forecast conti tinuou ous intrada day tradin ding 1 Expe pecta ctati tion on va value lue: : 59 €/MWh 6,7 €/MWh Standa dard d devi viati tion on: 18 €/MWh Low residual load forecast 2 Expe pecta ctati tion on va value lue: : 61 €/MWh 10,2 €/MWh Standa dard d devi viati tion on: 23 23 €/MWh Moderate residual load forecast 3 Expe pecta ctati tion on va value lue: : 59 €/MWh 3,1 €/MWh Standa dard d devi viati tion on: 9 9 €/MWh Expected revenues at continuous intraday trading vary strongly in dependence of residual load forecast! 16
Timo o Kern Forschungsgesellschaft für Energiewirtschaft mbH Am Blütenanger 71 Forschungsgesellschaft für 80995 München Energiewirtschaft mbH Tel.: +49(0)89 15 81 21 – 0 Tel.: +49(0)89 15 81 21 – 35 Email: info@ffe.de Internet: www.ffegmbh.de Email: tkern@ffe.de Twitter: @FfE_Muenchen
Analysis lysis of price structur ures s of the cont. Intrad aday ay trading ing Cha haracteris istic ics of continu inuous us 120,00 intraday prices Transaction price in €/MWh 100,00 Trading takes place mainly in the • three hours before delivery 80,00 Preis in €/MWh Partly high volatility • 60,00 40,00 15qh4 15qh3 20,00 15qh2 15qh1 0,00 06.08. 15:00 06.08. 21:00 07.08. 03:00 07.08. 09:00 07.08. 15:00 Time of trading Handelszeitpunkt 18
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