Dynamic Modeling of Fossil Power Plants – Enhancing Flexibility for Renewable Energy Integration

1. DYNAMIC MODELLING OF FOSSIL POWER PLANTS – INCREASING FLEXIBILITY TO BALANCE FLUCTUATIONS FROM RENEWABLE ENERGY SOURES M. Hübel, Dr. J. Nocke, Prof. E. Hassel University of Rostock Institute of Technical Thermodynamics Baku, 23.05.2013

2. Overview • Motivation • Reference PowerPlant • Simulation and Validation • ExampleResults • Outlook Institute of Technical Thermodynamics – Dynamic Power Plant Simulation

3. Motivation German Electric Energy System 2020 Installed Capacities Photovoltaic: ~ 50 GW Wind: ~ 55 GW Consumer Load Maximum: ~ 80 GW Average: ~ 60 GW GRID FREQUENCY indicats deviations in the energy balance http://meltblog.de/wp-content/uploads/2013/02/Fotolia_45848443_XS.jpg Institute of Technical Thermodynamics – Dynamic Power Plant Simulation

4. Motivation German Electric Energy System 2020 Annual Production Photovoltaic: ~ 50 TWh Wind: ~ 120 TWh Annual Consumption ~ 600 TWh/a GRID FREQUENCY indicats deviations in the energy balance http://meltblog.de/wp-content/uploads/2013/02/Fotolia_45848443_XS.jpg Institute of Technical Thermodynamics – Dynamic Power Plant Simulation

5. Motivation German Electric Energy System 2020 Annual Production Photovoltaic: ~ 50 TWh Wind: ~ 120 TWh Annual Consumption ~ 600 TWh/a GRID FREQUENCY indicats deviations in the energy balance Fossil: >300 TWh http://meltblog.de/wp-content/uploads/2013/02/Fotolia_45848443_XS.jpg Institute of Technical Thermodynamics – Dynamic Power Plant Simulation

6. Motivation Role of Fossil Power Plants in the German Electric Energy System • Most of our consumed electric energy is from thermal power plants – today and in the next decades • Some grid services, e.g. Primary Control can currently be done only by thermal power plants • (too) little investments for modernization and optimization within this sector – high potential for optimization METHODE: Dynamic Modeling GOAL: Flexible power plants P Gradmax Pmin Decreasing Minimum Load Increasing Load Gradients • Identify restrictions • Develop optimization strategies • Comparison of scenarios t Operating Schedule Institute of Technical Thermodynamics – Dynamic Power Plant Simulation

7. Reference Power Plant Jänschwalde Block D • Year of commissioning: 1985 • combustible: lignite • generator output: 530 MW • Efficiency: 36% • live steam • mass flow rate: 2x230 kg/s • pressure: 162 bar • temperature: 535 °C C1 C2 D1 D2 Block C Block D Werk Y2 Lehrstuhl für Technische Thermodynamik – Dynamische Modellierung des Kraftwerks “Jänschwalde”

8. Overview on Power Plant / Model Structure Boiler Turbine Condensator LP-Preheaters Feedwater System HP-Preheaters Lehrstuhl für Technische Thermodynamik – Dynamische Modellierung des Kraftwerks “Jänschwalde”

9. Fundamental equations Outlet massflow Outlet enthalpy flux Mass balance Energy balance Momentum balance Heat transfer Inside wall at boundary layer according Fouriers α determined by Dittus-Boelter heat transfer equation (1-phase flow) or Chen-correlation (2-phase flow) Outlet p Toutside Tinside TFluid Δ p heat flux Inlet p Inlet massflow Inlet enthalpy flux

10. Simulation and Validation Input Data Results Institute of Technical Thermodynamics – Transient Modeling of the Lignite Power Plant “Jänschwalde”

11. Simulation and Validation Power Output P Generator P Generator Simulated Institute of Technical Thermodynamics – Transient Modeling of the Lignite Power Plant “Jänschwalde”

12. Simulation and Validation Boiler Temperatures Institute of Technical Thermodynamics – Transient Modeling of the Lignite Power Plant “Jänschwalde”

13. Simulation and Validation Preheater Temperatures Institute of Technical Thermodynamics – Transient Modeling of the Lignite Power Plant “Jänschwalde”

14. Simulation and Validation Preheater Temperatures Institute of Technical Thermodynamics – Transient Modeling of the Lignite Power Plant “Jänschwalde”

15. Example Results Fatigue in components for the reference scenario Result • Fartigueforthecomponentsvariesbetween 0,0008 and0,0051 % forthereferencescenario • Evaporator andSuperheater 2 arecriticalcomponents in dynamicoperation • Conclusion • Same inputscenariodones not leadto same fatiguebecauseof different temperatuesand different geometries Fartigueof Headers

16. Outlook Lastgradient Load gradient Scenarios 2.5%, 4%, 6% Mindestlast Min load scenarios 50%, 37.5%, 33%, 20 % different operationmodes Simulation ofcriticalloadand wind scenariosundervariationofloadgradient, min loadof PP Jänschwaldeoroperationofthe power plant in specialmode Stillstand Gradmax Pmin operation parameters special operation modes „shut down & restart“ „reduce to circulation mode“ Institute of Technical Thermodynamics – Effects of fluctuating Wind Power on Power plant operation

17. Thankyouforyourattention! Dipl.-Ing. M. Hübel Dr.-Ing. J. Nocke Prof. Dr.-Ing. E. Hassel Andthankstooursponsorsforfinancialsupport Institute of Technical Thermodynamics – Dynamic Power Plant Simulation