15 th Conference Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction Mapping of Thermal Energy Integration Retrofit Assessment of Industrial Plants Luciana Savulescu, Zoé Périn-Levasseur and Marzouk Benali Prague, Czech Republic, August 25-29, 2012
Outline Sustainability through PI A Canadian Perspective Energy Efficiency Strategies Novel Approach for Energy Assessment Steam Mapping Waste Heat Mapping Conclusions 2
Our Strategy 3
Heat Exchangers creating inefficiencies Composite Curves Minimum energy consumptions and saving potential HEN Retrofit Design Modified Network Pinch Approach 4
NRCan s PI Incentive Program Participants Across Canada Actual Fuel Savings 6.6 PJ/year Implementation rate: 55% Enough to heat 100,000 family homes Renewable Electricity 50 MW 6 6 1 2 22 13 3 GHG Reductions Equivalent to < 100,000 cars Economic Activity Water Savings Production Increase Total 53 PI studies funded 1-2 3-5 6-10 11-15 >16 5
Industry Issues INCREASE THROUGHPUT 6
Energy Efficiency Strategies Techniques Energy Audit Simulation-based Analysis Process Control, Monitoring and Targeting Process Integration Techniques Characteristics Equipment-based analysis Do not account for the interactions within the energy system Obvious opportunities Complex large amount of info Inefficiencies are not indicated Link to operations, not design Low-hanging fruit measures Global system-based approach Account for the interactions within the energy system Evaluation of savings prior to design 7
PI Approach High Pressure Steam Low pressure steam Medium pressure steam T Heat Pump Pinch Cooling Water Refrigeration H 8
Challenges for PI Methodology issues Balance: Simplified assumptions vs. Practical elements to capture the complexity of the process Application issues Data gathering and data uncertainties Highly specialized expertise requirement Industry issues Particular plant bottlenecks (operation and economics) Application and interpretation of composite curves. Complementary way? 9
Steam Mapping Mill Engineers Mill Simulation Capture the information on steam use from the process perspective, as it illustrates the cold streams energy demand Relate the pressure level and the amount of steam consumed with its corresponding process energy load and temperature levels 10
Heat Exchanger Network Composite Curves Name Load Name Hot side Tin Tout Name Cold side Tin Tout Base Case 5000 kw Energy Savings 2200 kw Q H =2800 kw (kw) Hot Stream ( C) ( C) Cold Stream ( C) ( C) Heater 1 1000 Steam - - CSH1 10 30 Heater 2 2500 Steam - - CSH2 35 80 Heater 3 1500 Steam - - CSH3 100 120 Temperature ( C) Effluent/Waste Heat Pinch (50 C) T min =10 C Heater 3 HEX1 2000 HS1 97 50 CS1 30 65 HEX2 5000 HS2 55 30 CS2 5 35 Heater 2 Effluent 3000 Effluent 45 30 Environment - - Heater 1 Q C =800 kw Energy Load (kw) Composite curves provide the energy saving targeting 2200 kw Pinch temperature 50 C to guide the screening of inefficiencies Indirectly information on the location on heaters 11
Steam Mapping 140 0.4 Temperature ( C) 120 100 80 60 50 40 Zone 3 1500kW 30% Zone 2 1700kW 34% Zone 1 0.22 0.36 0.18 0.33 0.35 0.3 0.25 0.2 0.15 0.1 Economic Penalty (M$/year) 20 1800kW 36% 0.05 0 CSH1-Heater 1 CSH2-Heater 2 CSH3-Heater 3 Steam Users Econ. Zone1 Econ Zone 2 Econ Zone3 0 Preliminary energy target 1800 kw (36%) Steam use inefficiency in Heater 1 and Heater 2 Heater 1 economic penalty is 0.22 M$/y, assuming a 7$/GJ Heater 2 economic penalty is 0.18 M$/y 12
Kraft Process Steam Demand Mapping Overall steam distribution Low pressure steam Medium pressure steam 13
Waste Heat Mapping Represent the process heat sources as energy loads and temperature levels Facilitate the screening of energy recovery opportunities when combined with the steam mapping diagram 14
Waste Heat Mapping 180 2 160 Zone 1.8 Temperature ( C) 140 120 100 80 60 50 40 2.4 MW 6% Zone 16.4 MW 38% 12.5 MW 4.1 11.1 MW 7 MW 6.3 MW 1.4 Zone 8.4 7.6 2.8 3.5 2.1 3.5 3.5 2.5 MW 1.2 1.3 2.2 MW 1.2 MW 0.3 0.6 0.3 1.6 1.4 1.2 1 0.8 0.6 0.4 Economic Benefit (M$/y) 20 24 MW 56% 0.2 0 PM1 effluent PM2 effluent RB flue gases Dryer exhaust Selected Waste Heat Sources Alcalin effluent Screens effluent Saving benefit in zone 1 Saving benefit in zone 2 Saving benefit in zone 3 PM: paper machine, PB: power boiler PB blowdown 0 15
Steam and Waste Heat Mapping Assembly 200 180 160 Steam users Waste heat MP/LP 4.3 MW 140 120 100 80 60 50 40 MP 25.6 MW MP 9 MW LP 8.8 MW MP 5 MW 7 MW 1.2 MW LP 6 MW 6.3 MW LP 2.5 5 MW 12.5 MW 11.1 MW 2.2 MW Temperature ( C) 20 Pulp dryer PM air preheating BL evaporation Water deaerator Bleaching PM1 whitewater RB air preheating PM1 effluent PM2 effluent PB flue gases Dryer exhaust Alcalin effluent Screening effluent PB blowdown 0-20 Heat demands versus Waste heat sources PM: paper machine, Bl: black liquor, RB: recovery boiler, PB: power boiler 16
Benefits of the Visualization Thermal mapping provides a novel framework to illustrate: the global distribution of steam use current profile without loosing the specifics through merging rapid screening of steam use inefficiencies as load/economics the potential and economics of waste energy the waste heat recovery opportunities Improve the communication with mill engineers Facilitate the understanding of the PI concepts by industry A way to increase the demand for PI studies A descriptive framework prior to detailed PI case studies 17
Optimal Process and Technology Integration UTILITY SYSTEM KRAFT PROCESS Biorefinery NEW BIOREFINERY TECHNOLOGY Data Collection for retrofit Connect with industry Implement project Understand the process Take decisions Get closer to sustainability goals 18
PI: A Step Towards Sustainability From Research to Implementation Temperature ( C) 180 160 140 120 100 50 80 60 40 20 0 Research Zone 2.4 MW 6% Zone 16.4 MW 38% 24 MW 56% 12.5 MW 4.1 11.1 MW PM1 effluent PM2 effluent 7 MW RB flue gases 6.3 MW 1.4 Zone 8.4 7.6 2.8 3.5 Dryer exhaust Selected Waste Heat Sources Saving benefit in zone 1 Saving benefit in zone 2 Sav 2.1 3.5 3.5 PM: paper machine, PB: power boiler A e Integration Software Technologies Retrofit Solutions Incentives Communication Data Collection Training Case Studies Decision-support support Implementation 19
Acknowledgments Financial support Program on Energy Research and Development of Natural Resources Canada 20
Thank you for your attention Luciana Savulescu, Research Scientist Industrial Systems Optimization Email: luciana.savulescu@nrcan.gc.ca Telephone: +1 (450) 652-0275