Diagnosing the Causes of the Recent El Nio Event and Recommendations - PowerPoint PPT Presentation

Shaun D. McRae and Frank A. Wolak December 5, 2016 ITAM and Program on Energy Sustainable Development, Stanford University Diagnosing the Causes of the Recent El Niño Event and Recommendations for Reform

Introduction

• Provide comprehensive analysis market performance from 2000 to 2016 • Period covers two El Niño Events • Focus on explaining differences in market outcomes across two events • Focus on performance Reliability payment Mechanism (Firm Energy Obligation) • Provide Recommendations for • Reform of reliability mechanism • Long-term market reforms 1 Diagnosing Causes of Recent El Niño Event and Recommenda- tions for Reform

Generation and New Investment

2 Quarterly electricity generation in TWh, by type of generator Quarterly generation (TWh) 15 10 5 0 2000 2005 2010 2015 Hydro Thermal Cogen Wind

3 Quarterly generation capacity in GW, by type of generator 15 Generation capacity (GW) 10 5 0 2000 2005 2010 2015 Hydro Thermal Cogen Wind

4 Higher thermal utilization from mid-2012 onward 80 Capacity utilization (%) 60 Hydro 40 20 Thermal 0 Jan 2000 Jan 2005 Jan 2010 Jan 2015

5 Much larger increase in Bolsa price during 2015-16 despite sim- ilar thermal utilization rate to 2009-10 80 Hydro Cap. util. (%) 60 40 20 Thermal 0 Bolsa price (COP/kWh) 1200 800 400 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016

6 Quarterly fuel consumption by thermal generators 80 60 Million MMBTU 40 20 0 2006 2008 2010 2012 2014 2016 Coal Natural Gas Diesel/Fuel Oil

7 Rise in Colombian natural gas prices after the end of price reg- ulation and the opening of the wholesale gas market 30000 End Guajira price regulation COP per MMBTU 20000 10000 0 2008 2010 2012 2014 2016 Guajira Cusiana Henry Hub

8 Diesel prices (in pesos) in 2015-16 similar to 2009-10 80000 60000 COP per MMBTU Barrancabermeja 40000 20000 US Gulf Coast 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016

• Increase in hydroelectric generation from 2000 to 2009-2010 El Niño Event • Decline in hydroelectric generation from peak in 2011 • Increase in thermal generation from 2012 forward • Virtually all new capacity since 2010 has been hydroelectric • Higher thermal utilization rate from mid-2012 forward • Similar significant increase in thermal and significant decline in hydroelectric utilization rates in during both El Niño Events • Much larger Bolsa price during 2015-2016 versus 2009-2010 El Niño Event largely unrelated to input fuel price changes 9 Conclusions from Generation and New Investment

Availability of Hydroelectric Energy

10 Annual reservoir inflows were similar during 2009-10 and 2015- 16 El Niño events 60 Annual river flow (TWh) 40 20 0 2000 2005 2010 2015

11 Annual average hydro reservoir levels show similar water levels from 2012 to 2015 as during the 2009-10 El Niño event 12.5 10.0 Mean reservoir level (TWh) 7.5 5.0 2.5 0.0 2000 2005 2010 2015

12 Recent additions to hydro generation capacity have added less water storage capacity, relative to existing capacity 30 TWh and TWh/quarter 20 10 0 2000 2005 2010 2015 Capacity Storage Generation

13 Hydro spill during 2014 and 2015 is higher than it was during 2009-10 El Niño event 15 Spill (% of hydro gen) 10 5 0 2000 2005 2010 2015

• Similar monthly inflows during 2009-2010 and 2015-2016 El Niño Events • Steady decline in monthly inflows starting in 2011 • Low Water levels from 2012 to 2015 (very similar to 2009-2010 El Niño Event) • New hydroelectric generation capacity did not add as much water storage capacity on per MW of installed capacity basis as existing hydroelectric capacity • Spill during 2014 and 2015 higher than 2009 14 Conclusions from Water Availability Analysis

Reliability Payment Mechanism (RPM)

15 Reliability payments make up about 15% of revenue for largest three firms: EPM 1500 Billion Colombian pesos 1200 900 600 300 0 −300 −600 2008 2010 2012 2014 2016 AGC Services Firm Energy Reconciliations Bolsa Price Energy Net Firm Energy Refund Start−up Payment

16 Reliability payments make up about 15% of revenue for largest three firms: Emgesa 1500 Billion Colombian pesos 1200 900 600 300 0 −300 −600 2008 2010 2012 2014 2016 AGC Services Firm Energy Reconciliations Bolsa Price Energy Net Firm Energy Refund Start−up Payment

17 Reliability payments make up about 15% of revenue for largest three firms: Isagen 1500 Billion Colombian pesos 1200 900 600 300 0 −300 −600 2008 2010 2012 2014 2016 AGC Services Firm Energy Reconciliations Bolsa Price Energy Net Firm Energy Refund Start−up Payment

18 Reliability payments make up a larger share of revenue for in- dependent thermal generators (over 50% for some plants) 1500 Billion Colombian pesos 1200 900 600 300 0 −300 −600 2008 2010 2012 2014 2016 AGC Services Firm Energy Reconciliations Bolsa Price Energy Net Firm Energy Refund Start−up Payment

• Large suppliers that own thermal and hydroelectric units earn vast majority of revenues from energy sales at Bolsa price • Except for EPM, Net Firm Energy Refunds were positive for large firms during 2015-2016 El Niño Event • Reconciliation are typically negative for large firms • For independent thermal generators, Firm Energy revenues are large fraction of total revenues and reconciliation are typically positive Remaining unit owners in total look like large hydroelectric and thermal generation owners 19 Conclusions from RPM Analysis

Offer Prices and Market Prices

20 Distribution of the ratio of accepted offer prices to the scarcity price: hydro units 50000 40000 30000 Number of accepted offers 2009 20000 10000 0 50000 40000 30000 2015 20000 10000 0 0 1 2 3 4 Ratio of offer price to scarcity price

21 Distribution of the ratio of accepted offer prices to the scarcity price: thermal units 30000 20000 Number of accepted offers 2009 10000 0 30000 20000 2015 10000 0 0 1 2 3 4 Offer price / Scarcity price

22 Reservoir water levels and daily offer prices: Guatape (EPM) 125 % of reservoir max NPV 100 75 50 Level 25 NEP 0 Offer (pesos/kWh) 2000 1500 1000 500 0 Jul 2013 Jan 2014 Jul 2014 Jan 2015 Jul 2015 Jan 2016 Jul 2016

23 Reservoir water levels and daily offer prices: Pagua (Emgesa) 125 % of reservoir max NPV 100 75 Level 50 NEP 25 0 Offer (pesos/kWh) 2000 1500 1000 500 0 Jul 2013 Jan 2014 Jul 2014 Jan 2015 Jul 2015 Jan 2016 Jul 2016

24 Reservoir water levels and daily offer prices: Guavio (Emgesa) 125 % of reservoir max NPV 100 75 Level 50 25 NEP 0 Offer (pesos/kWh) 1000 750 500 250 0 Jul 2013 Jan 2014 Jul 2014 Jan 2015 Jul 2015 Jan 2016 Jul 2016

25 Reservoir water levels and daily offer prices: Jaguas (Isagen) 125 % of reservoir max NPV 100 75 50 25 NEP 0 Offer (pesos/kWh) 900 600 300 0 Jul 2013 Jan 2014 Jul 2014 Jan 2015 Jul 2015 Jan 2016 Jul 2016

26 Reservoir water levels and daily offer prices: Chivor (AES Chivor) 125 % of reservoir max NPV 100 Level 75 NEP 50 25 0 Offer (pesos/kWh) 2000 1000 0 Jul 2013 Jan 2014 Jul 2014 Jan 2015 Jul 2015 Jan 2016 Jul 2016

• Distribution of [P(Offer)/P(Scarcity)] for hydro units similar in 2009 and 2015, with few values greater than 1 • Distribution of [P(offer)/P(Scarcity)] for thermal units has much higher frequency of values above 1 during 2015 • Offer behavior consistent with desire to run hydro units rather than thermal units during first two quarters of 2015 • Offer prices of hydro units owned by large suppliers were not significantly higher than in 2013 and 2014 until final two quarters of 2015 • Substantial increase in all offer prices of hydro units following XM announcement on September 22, 2015 about reservoir levels 27 Conclusions from Offer Prices and Market Prices Analyses

Forward Contract and Firm Energy Positions

Supplier k ’s variable profit during hour h : (1) Expression excludes payments for providing ancillary services and positive and negative reconciliation payments (so that 28 Impact of Forward Contracts and Firm Energy Value on Offers π hk ( P h ( Bolsa )) = ( Q hk ( Ideal ) − Q hk ( Contract )) × min ( P h ( Bolsa ) , P h ( Scarcity )) + P hk ( Contract ) Q hk ( Contract ) + Q hk ( Firm ) P h ( Firm ) + [ Q hk ( Ideal ) − Q hk ( Firm )] × max ( 0 , (( P h ( Bolsa ) − P h ( Scarcity ))) − C k ( Q hk ( Ideal )) , Q hk ( Ideal ) = Q hk ( Actual ) ), and start-up payments

(2) Supplier k ’s variable profit during hour h : of supplier to raise or lower Bolsa price by exercising unilateral market power 29 ( P ( Bolsa ) < P ( Scarcity ) ) Forward Contracts and Offer Behavior π hk ( P h ( Bolsa )) = ( Q hk ( Ideal ) − Q hk ( Contract )) × P h ( Bolsa ) + P hk ( Contract ) Q hk ( Contract ) + Q hk ( Firm ) P h ( Firm ) − C k ( Q hk ( Ideal )) , Value of Q hk ( Contract ) relative to Q hk ( Ideal ) impacts incentive