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DYNAMIC MODELLING OF FOSSIL POWER PLANTS – INCREASING FLEXIBILITY TO BALANCE FLUCTUATIONS FROM RENEWABLE ENERGY SOURES Baku, 23.05.2013 M. Hübel, Dr. J.

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Presentation on theme: "DYNAMIC MODELLING OF FOSSIL POWER PLANTS – INCREASING FLEXIBILITY TO BALANCE FLUCTUATIONS FROM RENEWABLE ENERGY SOURES Baku, 23.05.2013 M. Hübel, Dr. J."— Presentation transcript:

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

2 Overview 1.Motivation 2.Reference PowerPlant 3.Simulation and Validation 4.Example Results 5.Outlook Institute of Technical Thermodynamics – Dynamic Power Plant Simulation 2

3 Motivation German Electric Energy System 2020 Institute of Technical Thermodynamics – Dynamic Power Plant Simulation 3 Installed Capacities Photovoltaic:~ 50 GW Wind:~ 55 GW GRID FREQUENCY indicats deviations in the energy balance Consumer Load Maximum:~ 80 GW Average:~ 60 GW

4 Motivation German Electric Energy System 2020 Institute of Technical Thermodynamics – Dynamic Power Plant Simulation 4 Annual Production Photovoltaic:~ 50 TWh Wind:~ 120 TWh GRID FREQUENCY indicats deviations in the energy balance Annual Consumption ~ 600 TWh/a

5 Motivation German Electric Energy System 2020 Institute of Technical Thermodynamics – Dynamic Power Plant Simulation 5 Annual Production Photovoltaic:~ 50 TWh Wind:~ 120 TWh GRID FREQUENCY indicats deviations in the energy balance Annual Consumption ~ 600 TWh/a Fossil: >300 TWh

6 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 Operating Schedule GOAL: Flexible power plants P min Grad max t P Decreasing Minimum Load Increasing Load Gradients METHODE: Dynamic Modeling Identify restrictions Develop optimization strategies Comparison of scenarios

7 7 Lehrstuhl für Technische Thermodynamik – Dynamische Modellierung des Kraftwerks “Jänschwalde” 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

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

9 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) Inlet massflow Outlet massflow heat flux Inlet enthalpy flux Outlet enthalpy flux Inlet p Outlet p Δ p T outside T inside T Fluid Fundamental equations

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

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

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

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

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

15 Fartigue of Headers Result Fartigue for the components varies between 0,0008 and 0,0051 % for the reference scenario Evaporator and Superheater 2 are critical components in dynamic operation Conclusion Same input scenario dones not lead to same fatigue because of different temperatues and different geometries Example Results Fatigue in components for the reference scenario

16 different operation modes Simulation of critical load and wind scenarios under variation of load gradient, min load of PP Jänschwalde or operation of the power plant in special mode operation parameters P min Grad max Load gradient Scenarios 2.5%, 4%, 6% special operation modes „shut down & restart“ „reduce to circulation mode“ StillstandLastgradientMindestlast Min load scenarios 50%, 37.5%, 33%, 20 % Outlook 16 Institute of Technical Thermodynamics – Effects of fluctuating Wind Power on Power plant operation

17 Thank you for your attention! Dipl.-Ing. M. Hübel Dr.-Ing. J. Nocke Prof. Dr.-Ing. E. Hassel 17 Institute of Technical Thermodynamics – Dynamic Power Plant Simulation And thanks to our sponsors for financial support


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