1. Markets for Dierentiated Electric Power Products Smart Grid Markets Integration of Renewables, Pricing, Modeling, and Optimization Emerging Topics in Interconnected Systems Sean P. Meyn Joint work with: In-Koo Cho, Anupama Kowli, Matias Negrete-Pincetic, Ehsan Shaeeporfaard, Uday Shanbhag, and Gui WangLaboratory for Cognition & Control in Complex SystemsDepartment of Electrical and Computer EngineeringUniversity of FloridaThanks to NSF, AFOSR, and DOE / TCIPG June 26, 2012

2. Markets for Dierentiated Electric Power ProductsConclusions in advanceTraditional fossil fuels will be history to our great grandchildren2 / 34 3. Markets for Dierentiated Electric Power ProductsConclusions in advanceWe need renewable energy, but how do we create a new energyinfrastructure to support this?2 / 34 4. Markets for Dierentiated Electric Power ProductsConclusions in advanceWe need renewable energy, but how do we create a new energyinfrastructure to support this?Some required elements:2 / 34 5. Markets for Dierentiated Electric Power ProductsConclusions in advanceWe need renewable energy, but how do we create a new energyinfrastructure to support this?Some required elements: Electricity must treated as a service and not a commodity: Gas turbine generation provides regulatory service. So could HVAC Smart Grid programs have helped to create a framework for greater service dierentiation Real time control will be an essential element to combat volatility and ensure reliability 2 / 34 6. Markets for Dierentiated Electric Power ProductsConclusions in advanceTraditional fossil fuels will be history to our great grandchildrenWe need renewable energy, but how do we create a new energyinfrastructure to support this?Some required elements: Electricity must treated as a service and not a commodity: Gas turbine generation provides regulatory service. So could HVAC Smart Grid programs have helped to create a framework for greater service dierentiation Real time control will be an essential element to combat volatility and ensure reliabilityReal time prices have little or no value here: This is supported by theory and history.2 / 34 7. Outline1 Smart Grid in 20122 Some Science3 Conclusions & Suggestions4 References3 / 34 8. Smart Grid in 2012Nodal Power Prices$20,000per MWhOtahuhu Stratford$10,000$00 4am9am2pm7pm Smart Grid 2012 4 / 34 9. Smart Grid in 2012EIA 2011 StudySmart grid legislative and regulatory policies and case studiesMany success stories: Millions of smarter meters installed all over the globePNNL study: Automation of water heaters and other appliancesprovided ancillary service in the Olympic peninsulaLarge buildings such as hotels, and energy-intensive companies suchas IBM, Google, and ALCOA have contracts in place to help stabilizethe grid, encouraged by FERC Ruling 745 Market-Based Demand Response Compensation Rule: Electric utilities and retail market operators are now required to pay demand response resources the market price (LMP) for energy 5 / 34 10. Smart Grid in 2012Increasing Leverage of FlexibilityConstellation Energy & NJP&L: Awards gift cards and rate reductions to residentsfor control of air conditioners; company sells exibility as ancillary service.www.eia.gov/analysis/studies/electricity/pdf/smartggrid.pdf, December 12, 2011Energy department to launch new energy innovation hubfocused on advanced batteries and energy storage.www.energy.gov, February 7, 2012 Honeywell And Hawaiian Electric To Use Demand Response To Integrate Renewables And Reduce Fossil Fuel Dependence.www.honeywell.com, February 2, 2012Axion Powers PowerCube Battery Energy StorageSystem Integrated Into PJM Utility Grid.www.axionpower.com, November 22, 2011 First small-scale demand-side projects in PJM providing frequency regulation. www.sacbee.com, November 21, 20116 / 34 11. Smart Grid in 2012EIA 2011 StudySmart grid legislative and regulatory policies and case studiesMany success stories ... and failuresResidential consumers have high expectations,Predictable cost savingsThey may distrust those tampering with their appliances.They distrust meters they believe interfere with appliances. 7 / 34 12. Smart Grid in 2012EIA 2011 StudySmart grid legislative and regulatory policies and case studiesMany success stories ... and failuresResidential consumers have high expectations,Predictable cost savingsThey may distrust those tampering with their appliances.They distrust meters they believe interfere with appliances.Moreover, the value of ancillary service obtained via demand response maybe reduced because of uncertainty of the level of consumer response.7 / 34 13. Smart Grid in 2012EIA 2011 StudySmart grid legislative and regulatory policies and case studiesMany success stories ... and failuresResidential consumers have high expectations,Predictable cost savingsThey may distrust those tampering with their appliances.They distrust meters they believe interfere with appliances.Moreover, the value of ancillary service obtained via demand response maybe reduced because of uncertainty of the level of consumer response.... yet, prices to devices are coming our way!Terry Boston, CEO PJM, ISGT 20127 / 34 14. Smart Grid in 2012EIA 2011 StudySmart grid legislative and regulatory policies and case studiesMoreover, the value of ancillary service obtained via demand response maybe reduced because of uncertainty of the level of consumer response.... yet, prices to devices are coming our way!Terry Boston, CEO PJM, ISGT 2012My concern: real-time pricing not TOU or contracts7 / 34 15. Smart Grid in 2012EIA 2011 StudyCase studies ... very little to say on real-time prices "The active participation of final demand in the wholesale market is essential to managing the greater intermittency of renewable resources and in limiting the ability of wholesale electricity suppliers to exercise unilateral market power. A demand that is able to reduce its consumption in real-time in response to higher prices limits the ability of suppliers to exercise unilateral market power in a formal wholesale market such as the California ISO"(http://www.stanford.edu/group/fwolak/cgi- bin/sites/default/files/files/little_hoover_testimony_wolak_sept_2011.pdf) -F. Wolak"Virtually all economists agree that the outcome [of the California crisis] was exacerbated by the inability of the demand side of themarket to respond to real or artificial supply shortages. This realization prompted my research stream on real-time electricitypricing."- S. BorensteinMy concern: real-time pricing not TOU or contracts 8 / 34 16. Smart Grid in 2012Winds Cause Price SpikesMidwest ISO today: Friday afternoon, March 4, 2011 3:30 p.m.-2000.00 9 / 34 17. Smart Grid in 2012Winds Cause Price SpikesMidwest ISO today: Friday afternoon, March 4, 2011 3:50 p.m. -762.55 10 / 34 18. Smart Grid in 2012Winds Cause Price SpikesMidwest ISO today: Friday afternoon, March 4, 2011 4:15 p.m.-1881.07 11 / 34 19. Smart Grid in 2012Winds Cause Price SpikesMidwest ISO today: Friday afternoon, March 4, 2011 4:30 p.m. 12 / 34 20. Smart Grid in 2012Cold Causes Price SpikesTexas today: Winter of 2011Power Prices in Texas $/MWh3000 80$/MWhJanuary 31, 2011 February 2, 20112000 60 401000 20 1000105am 10am 3pm8pm500 5am 10am 3pm8pm 13 / 34 21. Smart Grid in 2012Cold Causes Price SpikesTexas today: Winter of 2011Power Prices in Texas $/MWh3000 80$/MWhJanuary 31, 2011 February 2, 20112000 60 401000 20 1000105am 10am 3pm8pm500 5am 10am 3pm8pmThere will be multiple autopsies of the causes for the latest power breakdowns ... Who protedo this near-meltdown and what can be done to incentivize power producers to maintainadequate reserve capacity for emergencies rather than waiting for emergency windfalls? HOUSTON CHRONICLE, Feb 12, 2011New report hits ERCOT, electricity deregulation: A report released Monday concludes thatelectric deregulation has cost Texas residential consumers more than $11 billion in higherrates... Dallas Morning News, Feb 14, 2011 13 / 34 22. Smart Grid in 2012Day-Ahead Market OutcomesTexas today: Summer of 2011ERCOT North Zone - August 1-30, 2011Hourly day-ahead, daily on-peak, and monthly weighted average prices3,000hourly, day-ahead price2,500wholesale price ($/MWh) daily, on-peak price2,000weighted average monthly price ($188/MWh)1,5001,00050001 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Source: U.S. Energy Information Administration, based on the Electric Reliability Council of Texas (ERCOT). Source: U.S. Energy Information Administration, based on the Electric Reliability Council of Texas (ERCOT). Note: ERCOT North Zone includes Dallas/Fort Worth metrometro region and surrounding areas of Northeast Texas. On-Peak Note: ERCOT North Zone includes Dallas/Fort Worth region and surrounding areas of Northeast Texas. On-Peak refers to the 16-hour16-hour time block from hours ending to 10:00 p.m. 10:00 p.m. CDT on weekdays, excluding NERC holidaysrefers to the time block from hours ending 7:00 a.m. 7:00 a.m. to CDT on weekdays, excluding NERC holidays.14 / 34 23. Smart Grid in 2012Madness in New ZealandNew Zealand today: March 25, 2011A typical day in the New Zealand power market on the N. IslandNodal Power Prices in NZ: $/MWh OtahuhuStratford100 50 04am 9am 2pm 7pm http://www.electricityinfo.co.nz/15 / 34 24. Smart Grid in 2012Madness in New ZealandNew Zealand today: March 26, 2011$25 million dollars extracted by the generators in just six hours Nodal Power Prices in NZ: $/MWhOtahuhu20,000Stratford10,0000 4am 9am 2pm7pm http://www.electricityinfo.co.nz/16 / 34 25. Smart Grid in 2012Madness in New ZealandNew Zealand today: March 26, 2011>$20 million dollars demanded back from Genesis Nodal Power Prices in NZ: $/MWhOtahuhu20,000Stratford10,0000 4am 9am 2pm7pm http://www.electricityinfo.co.nz/Preliminary view of NZ Electrical Authority: Genesis was not guilty ofmanipulative ... or deceptive conduct. However, high prices threatened to16 / 34 26. Smart Grid in 2012Madness in New ZealandNew Zealand today: March 26, 2011>$20 million dollars demanded back from GenesisNodal Power Prices in NZ: $/MWhOtahuhu 20,000Stratford 10,000 04am 9am 2pm7pm http://www.electricityinfo.co.nz/Preliminary view of NZ Electrical Authority: Genesis was not guilty ofmanipulative ... or deceptive conduct. However, high prices threatened toundermine condence in, and ... damage the integrity and reputation of thewholesale electricity market3:59 PM Friday May 6, 2011 www.nzherald.co.nz 16 / 34 27. Smart Grid in 2012PNNL Prices to Devices ProjectsAutomation in the market Transactive Controls: Market-Based GridWiseTM Controls for Building Systems $$$ Bid PriceP + kP Mean PriceBid CurveClearing Price Current ZoneP kDesired or TemperatureIdea Set Point Minimum Maximum Set Point Set Point Tset = 72oFTmax = 77oFAdjusted ZoneTmin = 67oF Tset,a = 70oF Tcurrent = 75oF ComfortSet Point Temperature 17 / 34 28. Smart Grid in 2012PNNL Prices to Devices ProjectsAutomation in the market Transactive Controls: Market-Based GridWiseTM Controls for Building Systems $$$ Bid PriceP + kP Mean PriceBid CurveClearing Price Current ZoneP kDesired or TemperatureIdea Set Point Minimum Maximum Set Point Set Point Tset = 72oFTmax = 77oFAdjusted ZoneTmin = 67oF Tset,a = 70oF Tcurrent = 75oF ComfortSet Point Temperature Proportional control: Comfort = k Price 17 / 34 29. Smart Grid in 2012PNNL Prices to Devices ProjectsAutomation in the marketTransactive Controls: Market-Based GridWiseTM Controls for Building Systems$/MWhMean Price Zone Bid Price Market Clearing Price300200100 Hour00 5 10 152025Proportional control: Comfort = k Price18 / 34 30. Smart Grid in 2012PNNL Prices to Devices ProjectsAutomation in the marketTransactive Controls: Market-Based GridWiseTM Controls for Building SystemsConsumerAngerMean Price Zone Bid Price Market Clearing Price300200100 Hour00 5 10 152025Proportional control: Comfort = k Price19 / 34 31. Smart Grid in 2012MIT Prices to Devices ProjectsAutomation in the market Market-Based Control @ MIT Fig. 4. Stochastic evolution of prices and demand Roozbehani et. al. 2010$$$ DemandConsumer Anger?100600Ask Munzer et. al. Mean Price Zone Bid Price Demand400 50200 0 Hour0 50 100 150Real Time Prices Can Be Ugly 20 / 34 32. Smart Grid in 2012MIT Prices to Devices ProjectsAutomation in the market Market-Based Control @ MIT Fig. 4. Stochastic evolution of prices and demand Roozbehani et. al. 2010$$$ DemandConsumer Anger?100600Ask Munzer et. al. Mean Price Zone Bid Price Demand400 50200 0 Hour0 50 100 150Real Time Prices Can Be Ugly Seen in Theory & Practice 20 / 34 33. Smart Grid in 2012The Future as seen by FERC TodayFERC Order 755: RTMs on the microsecond scale Regulation Required @ MISO6004002000-200-400TimeNew rules for fair treatment of resources participating in regulation marketsCurrent method of regulation compensation does not fairly account for theregulation service provided. 21 / 34 34. Smart Grid in 2012The Future as seen by FERC TodayFERC Order 755: RTMs on the microsecond scale Regulation Required @ MISO6004002000-200-400TimeNew rules for fair treatment of resources participating in regulation marketsCurrent method of regulation compensation does not fairly account for theregulation service provided.Requires ISOs to pay resources based on actual service provided 21 / 34 35. Smart Grid in 2012The Future as seen by FERC TodayFERC Order 755: RTMs on the microsecond scale Regulation Required @ MISO6004002000-200-400TimeNew rules for fair treatment of resources participating in regulation marketsCurrent method of regulation compensation does not fairly account for theregulation service provided.Requires ISOs to pay resources based on actual service providedSounds fair enough! 21 / 34 36. Smart Grid in 2012The Future as seen by FERC TodayFERC Order 755: RTMs on the microsecond scale Regulation Required @ MISO6004002000-200-400 TimeNew rules for fair treatment of resources participating in regulation marketsPossible payment plan, consider1 of storage regulation, T d Payment S(t)| dt 0 dt22 / 34 37. Smart Grid in 2012The Future as seen by FERC TodayFERC Order 755: RTMs on the microsecond scale Regulation Required @ MISO6004002000-200-400 TimeNew rules for fair treatment of resources participating in regulation marketsPossible payment plan, consider1 of storage regulation, T d Payment S(t)| dt 0 dtSounds game-able enough!22 / 34 38. Some Science TorqueCostLowSpeedSome Science23 / 34 39. Some Science TorqueCostLowSpeedSome ScienceConcerning real-time pricing not TOU or contracts23 / 34 40. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesTheorem 1: When dynamics (temporal constraints) are taken intoaccount, price is never equal to marginal cost [5, 4, 3, 1] 24 / 34 41. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesTheorem 1: When dynamics (temporal constraints) are taken intoaccount, price is never equal to marginal cost [5, 4, 3, 1]Equilibrium priceThe equilibrium price process is a function of equilibrium reserves: P (t) = p (Re (t)) The marginal value of power to the consumer. 24 / 34 42. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesTheorem 1: When dynamics (temporal constraints) are taken intoaccount, price is never equal to marginal cost [5, 4, 3, 1]Equilibrium priceThe equilibrium price process is a function of equilibrium reserves: P (t) = p (Re (t)) The marginal value of power to the consumer.Proof: Lagrangian decomposition, as in the static Second Welfare Theorem, 24 / 34 43. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesTheorem 1: When dynamics (temporal constraints) are taken intoaccount, price is never equal to marginal cost [5, 4, 3, 1]Equilibrium priceThe equilibrium price process is a function of equilibrium reserves: P (t) = p (Re (t)) The marginal value of power to the consumer.Proof: Lagrangian decomposition, as in the static Second Welfare Theorem,or the proof of the Minimum Principle. 24 / 34 44. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesWhat is marginal value?It is not always obvious. With the introduction of network constraints,25 / 34 45. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesWhat is marginal value?It is not always obvious. With the introduction of network constraints,Prices can go well beyond marginal value (as dened in static model)Prices can go well below zero[Dynamic competitive equilibria in electricity markets. Wang et. al. 2011]25 / 34 46. Some ScienceEquilibrium with Dynamics & Network ConstraintsEntropic pricesWhat is marginal value?It is not always obvious. With the introduction of network constraints,Prices can go well beyond marginal value (as dened in static model)Prices can go well below zero[Dynamic competitive equilibria in electricity markets. Wang et. al. 2011]Without price-caps, Australia might look like an ecient equilibrium:10,000 19,000 1,4009,000 VictoriaDemand 1,200Tasmania1,000 Price (Aus $/MWh)8,000Price (Aus $/MWh)Volume (MW)1,000Volume (MW)7,000 Demand6,000800 10,0005,000 0Prices 6004,0003,0004002,000Prices 200 - 1,0001,0001,000 0 - 1,000 0 - 1,500 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 24:00 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 24:0025 / 34 47. Some ScienceSustainable business? Illinois: July 1998California: July 2000Spinning reserve prices PX prices $/MWh 5000 Purchase Price $/MWh70 250Previous week 60 400020050 300015040 2000 30 10020 1000 501000 MonTues Weds Thurs FriWedsThurs Fri SatSun MonTues Weds Ontario: November, 2005 Texas: February 2, 2011Marginal value of electricity,Forecast Demand Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5$/MWh210003000Average price is usually $3018000 2000$250,000/MWh (?)15000Hourly Ontario Energy Price $/MWhLast Updated 11:00 AM Predispatch 72.79 Dispatch 90.822000 1000Forecast Prices1500$/MWh1000 5000 036 9 12 15 18 21 36 9 12 15 18 21 3 6 9 12 15 18 21 Time 5005am 10am 3pm8pmTuesWedsThurs 26 / 34 48. Some ScienceSustainable business? Illinois: July 1998California: July 2000Spinning reserve prices PX prices $/MWh 5000 Purchase Price $/MWh70 250Previous week 60 400020050 300015040 2000 30 10020 1000 501000 MonTues Weds Thurs FriWedsThurs Fri SatSun MonTues Weds Ontario: November, 2005 Texas: February 2, 2011Marginal value of electricity,Forecast Demand Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5$/MWh210003000Average price is usually $3018000 2000$250,000/MWh (?)15000Hourly Ontario Energy Price $/MWhLast Updated 11:00 AM Predispatch 72.79 Dispatch 90.822000 1000Forecast Prices1500$/MWh1000 5000 036 9 12 15 18 21 36 9 12 15 18 21 3 6 9 12 15 18 21 Time 5005am 10am 3pm8pmTuesWedsThurs However, 26 / 34 49. Some ScienceSustainable business? Illinois: July 1998California: July 2000Spinning reserve prices PX prices $/MWh 5000 Purchase Price $/MWh70 250Previous week 60 400020050 300015040 2000 30 10020 1000 501000 MonTues Weds Thurs FriWedsThurs Fri SatSun MonTues Weds Ontario: November, 2005 Texas: February 2, 2011Marginal value of electricity,Forecast Demand Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5$/MWh210003000Average price is usually $3018000 2000$250,000/MWh (?)15000Hourly Ontario Energy Price $/MWhLast Updated 11:00 AM Predispatch 72.79 Dispatch 90.822000 1000Forecast Prices1500$/MWh1000 5000 036 9 12 15 18 21 36 9 12 15 18 21 3 6 9 12 15 18 21 Time 5005am 10am 3pm8pmTuesWedsThurs However, Theorem 2: In this equilibrium, the average price is precisely the average marginal cost Proof: Lagrangian relaxation of initial condition. 26 / 34 50. Some ScienceSustainable business? Illinois: July 1998California: July 2000Spinning reserve prices PX prices $/MWh 5000 Purchase Price $/MWh70 250Previous week 60 400020050 300015040 2000 30 10020 1000 501000 MonTues Weds Thurs FriWedsThurs Fri SatSun MonTues Weds Ontario: November, 2005 Texas: February 2, 2011Marginal value of electricity,Forecast Demand Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5$/MWh210003000Average price is usually $3018000 2000$250,000/MWh (?)15000Hourly Ontario Energy Price $/MWhLast Updated 11:00 AM Predispatch 72.79 Dispatch 90.822000 1000Forecast Prices1500$/MWh1000 5000 036 9 12 15 18 21 36 9 12 15 18 21 3 6 9 12 15 18 21 Time 5005am 10am 3pm8pmTuesWedsThurs However, Theorem 2: In this equilibrium, the average price is precisely the average marginal cost Proof: Lagrangian relaxation of initial condition.Is this a sustainable business? 26 / 34 51. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 75527 / 34 52. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costs27 / 34 53. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation:Includes G and dt G,dshut-down, O&M, investment, ...27 / 34 54. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation: TorqueIncludes G and dt G,dCostLowshut-down, O&M, investment, ...What is marginal cost?Speed27 / 34 55. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation: TorqueIncludes G and dt G,dCostLowshut-down, O&M, investment, ...What is marginal cost?SpeedTheorem 3: If c(G,dt G)d= ce (G) +cw ( dt G) d then27 / 34 56. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation: TorqueIncludes G and dt G,dCostLowshut-down, O&M, investment, ...What is marginal cost?SpeedTheorem 3: If c(G,dt G)d= ce (G) +cw ( dt G) d thenE[P ] = E[ ce (G)]27 / 34 57. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation:TorqueIncludes G and dt G,d Cost Lowshut-down, O&M, investment, ...What is marginal cost? SpeedTheorem 3: If c(G,dt G)d= ce (G) + cw ( dt G)dthenE[P ] = E[ ce (G)]= lots of missing money 27 / 34 58. Some ScienceMore Engineering: Where is the Missing Money?Addressing FERC Order 755World-view, from eyes of a coal generator operator:Control must respect dynamics & costsCost of generation:TorqueIncludes G and dt G,d Cost Lowshut-down, O&M, investment, ...What is marginal cost? SpeedTheorem 3: If c(G,dt G)d= ce (G) + cw ( dt G)dthenE[P ] = E[ ce (G)]= lots of missing moneyCompetitive equilibrium never compensates for wear and tear. 27 / 34 59. Conclusions & SuggestionsConclusions & Suggestions 28 / 34 60. Conclusions & SuggestionsEconomics and EngineeringArbitrage between Nukes and Turbines?29 / 34 61. Conclusions & SuggestionsEconomics and EngineeringArbitrage between Nukes and Turbines?Any power engineer knows: Nuclear generation and gas turbines providedierent services, and are not just delivering electrons.29 / 34 62. Conclusions & SuggestionsEconomics and EngineeringArbitrage between Nukes and Turbines?Any power engineer knows: Nuclear generation and gas turbines providedierent services, and are not just delivering electrons. So FERC is on the right track ... 29 / 34 63. Conclusions & SuggestionsEconomics and EngineeringArbitrage between Nukes and Turbines?Any power engineer knows: Nuclear generation and gas turbines providedierent services, and are not just delivering electrons. So FERC is on the right track ...TdWhat about the other policy makers? Payment S(t)| dt0 dt29 / 34 64. Conclusions & SuggestionsEconomics and EngineeringArbitrage between Nukes and Turbines?Any power engineer knows: Nuclear generation and gas turbines providedierent services, and are not just delivering electrons. So FERC is on the right track ...TdWhat about the other policy makers? Payment S(t)| dt0 dt ... One result of this divorce of the theory from its subject matter has been that the entitites whose decisions economists are engaged in analyzing have not been made he subject of study and in consequence lack any substance. ...consumers without humanity, rms without organization, and even exchange without marketsR. Coase, 198829 / 34 65. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. 30 / 34 66. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. 30 / 34 67. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. Risk to suppliers: Average prices coincide with average marginal cost. 30 / 34 68. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. Risk to suppliers: Average prices coincide with average marginal cost. Why stay in such a risky business? 30 / 34 69. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. Risk to suppliers: Average prices coincide with average marginal cost. Why stay in such a risky business?The real world 30 / 34 70. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. Risk to suppliers: Average prices coincide with average marginal cost. Why stay in such a risky business?The real worldVolatile prices are observed all over the world Benets to consumers are not clear, and innovation is slow 30 / 34 71. Conclusions & SuggestionsSummary of Research at Illinois & FloridaThe current RTM paradigm must be reconsideredConclusions of our research, under the most optimistic assumptionsVolatile prices are to be expected in real time electricity markets in anecient equilibrium. Prices are never equal to marginal cost. Risk to suppliers: Average prices coincide with average marginal cost. Why stay in such a risky business?The real worldVolatile prices are observed all over the world Benets to consumers are not clear, and innovation is slow Market power is a reality, and symmetric information is absurd:Strategic behavior can lead to a new crisis each year! 30 / 34 72. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredWhy have real time markets?No value has been demonstrated for real-time markets.31 / 34 73. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredWhy have real time markets?No value has been demonstrated for real-time markets.Empirical evidence: We cannot distinguish robbery from eciency. 31 / 34 74. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredWhy have real time markets?No value has been demonstrated for real-time markets.Empirical evidence: We cannot distinguish robbery from eciency.Is This A Free Market For Fire Fighters? 31 / 34 75. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredWhy have real time markets?No value has been demonstrated for real-time markets.Empirical evidence: We cannot distinguish robbery from eciency.Is This A Free Market For Fire Fighters? Why then would you use real-time prices to control devices? 31 / 34 76. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredWhy have real time markets?No value has been demonstrated for real-time markets.Empirical evidence: We cannot distinguish robbery from eciency.Is This A Free Market For Fire Fighters? Why then would you use real-time prices to control devices? The EIA study shows that there are alternatives 31 / 34 77. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredAlternativesTOU prices for peak shaving,andContracts for real-time demand-response services 32 / 34 78. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredAlternativesTOU prices for peak shaving,andContracts for real-time demand-response servicesSuccessful contracts today: Constellation Energy, Alcoa, residential poolpumps, commercial buildings (see new work at Univ. of Florida), ...Eciency loss, but utility and consumers each have reliable services 32 / 34 79. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredAlternativesNew Smart appliances that can facilitate these contractsControl theory to make this all work: We dont know why the grid is so robust today. Introducing all of these dynamics will lead to new control challenges.32 / 34 80. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredAlternativesNew Smart appliances that can facilitate these contractsControl theory to make this all work: We dont know why the grid is so robust today. Introducing all of these dynamics will lead to new control challenges.Energy policy that is guided by an understanding of both physics andeconomics 32 / 34 81. Conclusions & SuggestionsThe current RTM paradigm must be reconsideredAlternativesNew Smart appliances that can facilitate these contractsControl theory to make this all work: We dont know why the grid is so robust today. Introducing all of these dynamics will lead to new control challenges.Energy policy that is guided by an understanding of both physics andeconomicsThank You! 32 / 34 82. Conclusions & SuggestionsPre-publication version for on-line viewing. Monograph available for purchase at your favorite retailerAugust 2008 Pre-publication version for on-line viewing. Monograph to appear Februrary 2009More information available at http://www.cambridge.org/us/catalogue/catalogue.asp?isbn=9780521884419 Control TechniquesMarkov Chains FORandComplex Networks Stochastic StabilityP n (x, ) f 0 sup Ex [SC (f )] < C (f ) < V (x) f (x) + bIC (x) Sean MeynS. P. Meyn and R. L. TweedieReferences 33 / 34 83. ReferencesReferences G. Wang, M. Negrete-Pincetic, A. Kowli, E. Shaeepoorfard, S. Meyn, and U. Shanbhag. Dynamic competitive equilibria in electricity markets. In A. Chakrabortty and M. Illic, editors, Control and Optimization Theory for Electric Smart Grids. Springer, 2011. M. Negrete-Pincetic and S. Meyn. Where is the Missing Money? The impact of generation ramping costs in electricity markets. In preparation, 2012. G. Wang, A. Kowli, M. Negrete-Pincetic, E. Shaeepoorfard, and S. Meyn. A control theorists perspective on dynamic competitive equilibria in electricity markets. In Proc. 18th World Congress of the International Federation of Automatic Control (IFAC), Milano, Italy, 2011. S. Meyn, M. Negrete-Pincetic, G. Wang, A. Kowli, and E. Shaeepoorfard. The value of volatile resources in electricity markets. In Proc. of the 10th IEEE Conf. on Dec. and Control, Atlanta, GA, 2010. I.-K. Cho and S. P. Meyn. Eciency and marginal cost pricing in dynamic competitive markets with friction. Theoretical Economics, 5(2):215239, 2010. H. Hao, A. Kowli, T. Middelkoop, P. Barooah, and S. Meyn. Using exible HVAC power consumption of commercial buildings for regulation service to the grid. UF TR, 2012 U.S. Energy Information Administration. Smart grid legislative and regulatory policies and case studies. December 12 2011. http://www.eia.gov/analysis/studies/electricity/pdf/smartggrid.pdf34 / 34