Market Power in a Hydro-Dominated Wholesale Electricity Market - PowerPoint PPT Presentation

Market Power in a Hydro-Dominated Wholesale Electricity Market Shaun McRae and Frank Wolak April 8, 2017 ITAM and Program on Energy Sustainable Development, Stanford University

We study the market power in the Colombian wholesale elec- tricity market: a bid-based, hydro-dominated system • Majority of generation capacity in Colombia is hydroelectric • Susceptible to periodic shortfalls in water inflows during El Niño events • Market prices are determined using price and quantity bids submitted by generation owners • Other Latin American electricity markets use cost-based dispatch 1

Much larger increase in wholesale price during 2015–16 El Niño event despite similar 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 2

Why do we study this question? • General interest in the use of wholesale electricity markets as a data-rich “laboratory” for understanding firm behavior • Policy tension between “regulators” and “markets” in electricity • Most restructured electricity markets have an increasingly large role for regulation in determining short-term prices and long-term investment • How should we balance the costs and benefits of regulation in these markets? 3

Colombian electricity market

Share of thermal generation has been increasing since 2009, even in years with no adverse hydrological conditions Quarterly generation (TWh) 15 10 5 0 2000 2005 2010 2015 Hydro Thermal Cogen Wind 4

Most new capacity investment in past decade has been in hy- droelectric generation 15 Generation capacity (GW) 10 5 0 2000 2005 2010 2015 Hydro Thermal Cogen Wind 5

Comparison of El Niño events

What explains the large difference in prices between the two most recent El Niño events? • Mean price in 2009–10 El Niño: 185 COP/kWh (US$95/MWh) • Mean price in 2015–16 El Niño: 675 COP/kWh (US$217/MWh) • Market structure (institutions and actors) changed little between the two events • Was there a difference in the hydrological conditions or fuel prices? 6

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 7

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 8

Note that natural gas was inframarginal during both El Niño events (so diesel prices are what matter) 80 60 Million MMBTU 40 20 0 2006 2008 2010 2012 2014 2016 Coal Natural Gas Diesel/Fuel Oil 9

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 10

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 11

Market power in wholesale electricity markets

Every day and hour, electricity generators submit a step function supply curve to the system operator 1000 S 1 ( p ) 750 COP/kWh 500 250 0 0 1000 2000 3000 4000 MW 12

System operator determines market price where the aggregate supply curve crosses aggregate demand (perfectly inelastic) 1000 System demand S ( p ) 9319 MW 750 COP/kWh 500 System price 250 322 COP/kWh 0 0 5000 10000 15000 MW 13

Residual demand for a firm is the difference between system demand and the aggregate offers of all other firms 1000 System demand SO 1 ( p ) 9319 MW 750 COP/kWh 500 250 DR(250) = 4147 MW DR(125) = 5682 MW 0 0 5000 10000 15000 MW 14

Generation firms can choose the optimal (price, quantity) com- bination along their residual demand curve 1000 Generation S 1 ( p ) 1797 MW 750 COP/kWh 500 System price 250 322 COP/kWh DR 1 0 0 2500 5000 7500 10000 MW 15

Residual demand and offer curve at 18:00 hrs on September 18, 2015: EPM 2500 EPMG offer Hydro Thermal 2000 COP/kWh 1500 1000 500 Scarcity price Dispatch price RD EPMG generation 0 0 2500 5000 7500 10000 MW 16

Residual demand and offer curve at 18:00 hrs on September 25, 2015: EPM 2500 EPMG offer Hydro Thermal 2000 COP/kWh 1500 1000 Dispatch price 500 Scarcity price RD EPMG generation 0 0 2500 5000 7500 10000 MW 17

Residual demand and offer curve at 18:00 hrs on October 2, 2015: EPM 2500 EPMG offer Hydro Thermal 2000 Dispatch price COP/kWh 1500 1000 500 Scarcity price RD EPMG generation 0 0 2500 5000 7500 10000 MW 18

Two measures of ability to exercise unilateral market power based on residual demand curve DR hk ( p h ) 1 • Inverse semi-elasticity, η hk = − hk ( p h ) , quantifies 100 DR ′ COP per kWh increase in wholesale price from supplier k reducing its actual output by one percent • η hk measures the ability of supplier k to raise the market price at their actual level of output during hour h 19

Two measures of ability to exercise unilateral market power based on residual demand curve • Pivotal supplier frequency is the fraction of hours in the week that DR hk ( ∞ ) > 0, supplier k ’s residual demand is positive for all possible wholesale prices, meaning that some of supplier k ’s available capacity is required to serve demand during hour h • A pivotal supplier can raise the price has high it would like if it is willing to only sell its pivotal quantity, DR hk ( ∞ ) > 0 20

Empirical analysis of market power in Colombian electricity market

Offer prices and inverse semi-elasticities: EPM Inverse semi−elasticity 20 15 10 5 0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 21

Offer prices and proportion of pivotal hours: EPM Share pivotal hours 0.6 0.4 0.2 0.0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 22

Offer prices and inverse semi-elasticities: Emgesa Inverse semi−elasticity 20 15 10 5 0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 23

Offer prices and proportion of pivotal hours: Emgesa Share pivotal hours 0.6 0.4 0.2 0.0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 24

Offer prices and inverse semi-elasticities: Isagen Inverse semi−elasticity 20 15 10 5 0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 25

Offer prices and proportion of pivotal hours: Isagen Share pivotal hours 0.6 0.4 0.2 0.0 Offer price (COP/kWh) 2000 1500 1000 500 0 Jan 2008 Jan 2010 Jan 2012 Jan 2014 Jan 2016 26

Wholesale price is higher in those periods where firms have more market power on average (1) (2) (3) (4) Mean η 18 . 15 11 . 90 ( 6 . 16 ) ( 3 . 44 ) Mean pivotal (0/1) 858 . 22 200 . 12 ( 246 . 13 ) ( 138 . 19 ) Mean pivotal q (MW) 1 . 70 1 . 26 ( 0 . 21 ) ( 0 . 18 ) Hour × year Y Y Y Y Month-of-sample Y Y Y Y Gen bin × year Y Y Y Y Observations 73,742 73,742 73,742 73,742 27

Offer prices for largest firms are higher for those periods in which firms have greater market power (1) (2) (3) (4) 14 . 18 3 . 18 6 . 59 6 . 55 η ( 5 . 44 ) ( 1 . 79 ) ( 1 . 92 ) ( 2 . 21 ) Pivotal (0/1) 337 . 58 58 . 51 129 . 20 − 28 . 29 ( 99 . 58 ) ( 73 . 09 ) ( 44 . 95 ) ( 115 . 87 ) Generator AES Chivor Emgesa EPM Isagen Hour × year Y Y Y Y Month-of-sample Y Y Y Y Gen bin × year Y Y Y Y Observations 46,765 73,407 73,649 73,188 28

Conclusions from market power analysis • By inverse semi-elasticity measure η hk and pivotal supplier frequency all suppliers have little, if any ability to exercise unilateral market power until early 2014, even during 2009-2010 El Niño event • From October 2015 onwards, all suppliers both measures showed very large increase in unilateral ability to exercise market power • This fact explains remarkable increase in wholesale prices during 2015–16 El Niño event relative to 2009–10 29

Discussion

Declining availability factor led to many more hours in which at least one firm was pivotal in the 2015-16 El Niño event 20 15 GW 10 5 0 2006 2008 2010 2012 2014 2016 Nameplate Availability Availability (N−1) Max demand Pivotal Q 30

Most new generation investment in Colombia has been hydro- electric • Steady increase in electricity demand and share of thermal generation in total • Most new generation is hydroelectric, with relatively limited storage capacity • Increased susceptibility to declines in water inflows during El Niño events • Reduced buffer to deal with adverse hydrological conditions • This becomes even more important as climate variability increases 31