Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion European energy equilibrium and decomposition Anes Dallagi EDF R&D – OSIRIS – Optimization methods and tools ICSP 2013 Bergamo, July 12th, 2013 1/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion Plan Some facts 1 Time decomposition 2 The long-term problems 3 What we need ? What we use ? The optimization process : from multiple to a single zone problem Decomposition and splitting methods for network problems 4 Scope and modeling issues First splitting scheme : one producer / one consumer Second splitting scheme : ♯ Z producers / one consumer The splitting algorithm : stochastic computing issues 5 Conclusion 6 2/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion Plan Some facts 1 Time decomposition 2 The long-term problems 3 What we need ? What we use ? The optimization process : from multiple to a single zone problem Decomposition and splitting methods for network problems 4 Scope and modeling issues First splitting scheme : one producer / one consumer Second splitting scheme : ♯ Z producers / one consumer The splitting algorithm : stochastic computing issues 5 Conclusion 6 3/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion EDF generation side vs. demand side Demand to be satisfied : EDF generation mix : Residential, industrial demand and 47 thermal units (fuel, coal and LT contracts ; gas turbine) ; Provision of energy by committing 58 nuclear units ; a number of turbines to be 50 hydro-valleys. Each hydro-valley running ; is a set of interconnected reservoirs Provision of spinning reserve by (150) and power plants (448). committing turbines to be in Water stock : 7000hm3 ; synchronized condensing mode ; 25 withdrawal options ; Provision of frequency-keeping Other : wind, solar, biomass in services from a selection of significant growth. turbines ; How to match supply to demand while minimizing costs ? 4/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion EDF generation side vs. demand side Demand to be satisfied : EDF generation mix : Residential, industrial demand and 47 thermal units (fuel, coal and LT contracts ; gas turbine) ; Provision of energy by committing 58 nuclear units ; a number of turbines to be 50 hydro-valleys. Each hydro-valley running ; is a set of interconnected reservoirs Provision of spinning reserve by (150) and power plants (448). committing turbines to be in Water stock : 7000hm3 ; synchronized condensing mode ; 25 withdrawal options ; Provision of frequency-keeping Other : wind, solar, biomass in services from a selection of significant growth. turbines ; How to match supply to demand while minimizing costs ? 4/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion EDF generation side vs. demand side Demand to be satisfied : EDF generation mix : Residential, industrial demand and 47 thermal units (fuel, coal and LT contracts ; gas turbine) ; Provision of energy by committing 58 nuclear units ; a number of turbines to be 50 hydro-valleys. Each hydro-valley running ; is a set of interconnected reservoirs Provision of spinning reserve by (150) and power plants (448). committing turbines to be in Water stock : 7000hm3 ; synchronized condensing mode ; 25 withdrawal options ; Provision of frequency-keeping Other : wind, solar, biomass in services from a selection of significant growth. turbines ; How to match supply to demand while minimizing costs ? 4/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion EDF generation side vs. demand side Demand to be satisfied : EDF generation mix : Residential, industrial demand and 47 thermal units (fuel, coal and LT contracts ; gas turbine) ; Provision of energy by committing 58 nuclear units ; a number of turbines to be 50 hydro-valleys. Each hydro-valley running ; is a set of interconnected reservoirs Provision of spinning reserve by (150) and power plants (448). committing turbines to be in Water stock : 7000hm3 ; synchronized condensing mode ; 25 withdrawal options ; Provision of frequency-keeping Other : wind, solar, biomass in services from a selection of significant growth. turbines ; How to match supply to demand while minimizing costs ? 4/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion Plan Some facts 1 Time decomposition 2 The long-term problems 3 What we need ? What we use ? The optimization process : from multiple to a single zone problem Decomposition and splitting methods for network problems 4 Scope and modeling issues First splitting scheme : one producer / one consumer Second splitting scheme : ♯ Z producers / one consumer The splitting algorithm : stochastic computing issues 5 Conclusion 6 5/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion The optimization process : time decomposition Investments, Stochastic Prices, Demand Long-term opti- MC forecast, approximate and technology mization problem export/import model LT forecast forecast Prices, Demand Mid-term optimi- and inflow Water values zation problem MT forecast Prices, Demand Short-term opti- Deterministic Operating and inflow accurate model mization problem schedule ST forecast 6/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion The optimization process : time decomposition Investments, Stochastic Prices, Demand Long-term opti- MC forecast, approximate and technology mization problem export/import model LT forecast forecast Prices, Demand Mid-term optimi- and inflow Water values zation problem MT forecast Prices, Demand Short-term opti- Deterministic Operating and inflow accurate model mization problem schedule ST forecast 6/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion The optimization process : time decomposition Investments, Stochastic Prices, Demand Long-term opti- MC forecast, approximate and technology mization problem export/import model LT forecast forecast Prices, Demand Mid-term optimi- and inflow Water values zation problem MT forecast Prices, Demand Short-term opti- Deterministic Operating and inflow accurate model mization problem schedule ST forecast 6/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems Decomposition and splitting methods for network problems The splitting algorithm : stochastic computing issues Conclusion The optimization process : time decomposition Investments, Stochastic Prices, Demand Long-term opti- MC forecast, approximate and technology mization problem export/import model LT forecast forecast Prices, Demand Mid-term optimi- and inflow Water values zation problem MT forecast Prices, Demand Short-term opti- Deterministic Operating and inflow accurate model mization problem schedule ST forecast 6/33 A. Dallagi European energy equilibrium and decomposition
Some facts Time decomposition The long-term problems What we need ? What we use ? Decomposition and splitting methods for network problems The optimization process : from multiple to a single zone problem The splitting algorithm : stochastic computing issues Conclusion Plan Some facts 1 Time decomposition 2 The long-term problems 3 What we need ? What we use ? The optimization process : from multiple to a single zone problem Decomposition and splitting methods for network problems 4 Scope and modeling issues First splitting scheme : one producer / one consumer Second splitting scheme : ♯ Z producers / one consumer The splitting algorithm : stochastic computing issues 5 Conclusion 6 7/33 A. Dallagi European energy equilibrium and decomposition
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