Recent and future needs on the operation of combined cycle power plants. Kilian Link, Siemens, Energy Sector

Transcription

1 Recent and future needs on the operation of combined cycle power plants. Kilian Link, Siemens, Energy Sector For internal use only / For Siemens internal AG use only All / Copyright rights reserved. notice

2 Agenda The basic principle of combined cycle power plants (CCPP) Transition of the energy system (e.g. Germany) Market needs. Demand on flexibility. Integration of solar and wind power. Examples for challenging issues of control and decision making. Page 2

3 Sectors and Divisions as of October 1, 2011 Energy Healthcare Industry Infrastructure & Cities Divisions Fossil Power Generation Wind Power Solar & Hydro Oil & Gas Energy Service Power Transmission Divisions Imaging & Therapy Systems Clinical Products Diagnostics Customer Solutions Divisions Industry Automation Drive Technologies Customer Services Divisions Rail Systems Mobility and Logistics Low and Medium Voltage Smart Grid Building Technologies OSRAM 1) 1) In fiscal 2011, Siemens announced its intention to publicly list OSRAM and, as an anchor shareholder, to hold a minority stake in OSRAM AG over the long term Page 3

4 Basic principle of a CCPP and why it is benficial Heat recovery steam generator Electrical energy Gas turbine plant: 1 Air intake 2 Compressor 3 Gas turbine 4 Heat recovery steam generator 5 Generator 6 Transformer Air Fuel 9 4 Exhaust gas Steam turbine plant: 7 Steam turbine 8 Condenser 9 Feeding pump 10 Generator 11 Transformer 12 Circulating pump Life steam Condensate 1200 Temperature [ C] Electrical energy Cooling tower Cooling air Fresh water High efficiency (world record over 60% efficiency, May 2011) Low invest. Flexible Operation. Gas-Cycle Steam-Cycle 0 Page Entropy S G and Energy S St F ES [kj/k] EN PTEC PE

5 Common single shaft configuration combined with a HRSG with 3 pressure stages plus reheat. Heat recovery steam generator LP main steam HP main steam LP IP HP Cold reheat Gas turbine Generator Steam turbine Feed Water Pump Hot reheat Condensate Extraction Pump Condensate Page 5 SIPICS. PG Fossil Power Generation. W81. 3_3_1_0_4/c Siemens Power Generation All Rights Reserved

6 Future market needs Wind Power Solar Power Lowest Investment Highest Efficiency Highest Flexibility CO 2 emission reduction increasing gas prices Page 6

7 Operating flexibility Power Generation in Germany: Challenges with a high share of renewable energy Change in the generation structure Residual load (load-renewable in feed) 2020 TWh 800 GW Weekly average 700 Hydro Nuclear Coal Oil Gas Renew. 600 consumption Jan 31.Dec Increasing mismatch between generation and load to be compensated by backup and storage Source: Siemens Energy Strategy December 2010 Page 7

8 Today s power generation provided by renewables in Germany? Today s Power Mix in Germany Today's Wind Power in Germany Today's Solar Power in Germany Page 8

9 Operating flexibility forecast Germany We need flexible plants in the future: Power Generation Scenario 2020 (Germany) Typical Summer Week (June 2020) residual load [MW] 20,000 15,000 10,000 5, ,000-10,000 0 High wind day Load ramps: Average: ~4 times faster* Max.:~10 times faster* Peaks 9h 6h 10h 8h 11h * compared to Overload today's max time [h] 11h Peak 2 GW 4 GW 2 GW 6h 1 GW 2 GW 8h 9h 6 GW 10h 100% daily start-stop Germany 2020: Up to 100% of the non-renewable fleet requires daily start-stop operation, load ramps of about 200 MW/min to be covered Page 9

10 Operating flexibility different aspects Highest efficiency throughout the whole load range Optimized start up and shutdown operation Load ramps Fast starts Stable operation in case of grid incidents Netz- Stabilisierung On Demand Load ramps Park load Backup power Page 10

11 Siemens Application How MODRIO adresses these requirements Non linear model predictive control Super heating Set point steam Temperature Pressure Feed water controller Mass Flow Set point feed water superheater evaporator economizer Page 11

12 Siemens Application How does MODRIO addresses these requirements Non linear model predictive control Least square objective Optimizer e.g. JModelica Cost function Constraints DCS SPPA T3000 State estimation Model predictive controller Measured values, Signals,... Plant Model Plant Page 12

13 The operator will need some guidance in the future Control reserve Profit target Energy Price Capacity Charge? Electricity Volatile Prices CO 2 Fuel Cost of Operation Remaining Lifetime Start up/ Shutdown Revision Planning Page 13

14 Plant control will evolve into high sophisticated software. The business model of controllable power plants will change focus form steady state operation of flexibility.. Development processes of software will be applied to control design and implementation. Control guys will be bothered with real world s non linearity. Innovation will be boosted with respect to modeling. On- and offline Optimization. Diagnosis. Operator guidances. Page 14

15 Your Feedback Thank you for your attention! Page 15