A knowledge-based system for Waste Heat Recovery. Richard Law

Transcription

1 A knowledge-based system for Waste Heat Recovery Richard Law

2 Author Background 3 rd Year PhD Student at Newcastle University School of Chemical Engineering and Advanced Materials Process Intensification Group (PIG) pig.ncl.ac.uk Work completed as part of EPSRC OPTITHERM project OPTImising THermal Energy Recovery, utilisation and Managament in the process industries 2

3 Contents Background Introduction to waste heat recovery (UK) Motivation & aims Methods Results Conclusions Further Work 3

4 Background: Waste Heat Recovery Why? UK Climate Change Act (2008) Targets an 80% reduction in greenhouse gas emissions by 2050 (34% by 2020; based on 1990 levels) Process industries account for 20-25% of emissions Reduce industrial energy consumption (and greenhouse gas emissions) by increasing energy efficiency by recovering waste heat 11.4TWh 1 of recoverable waste heat is emitted to environment by UK industry each year (5% of total energy use) 1 Reay & Morrell, Carbon Trust Report,

5 Background: Waste Heat Recovery Why? Rising Cost of Key Utilities: Department of Energy and Climate Change 5

6 Background: Waste Heat Recovery How? Technology Use Selected for software? Heat Exchangers Heat Pump (vapour compression) Organic Rankine Cycle To transfer heat from the waste heat source to matching heat sink To provide a temperature lift in order to heat a sink of greater temperature than the source To convert waste heat to electricity Yes: Various types are included Yes: Including various working fluids Yes: Including various working fluids Absorption Heat Pump To provide coolth No: Problems with low COP District heating networks Export waste heat to sink No: Not considered in UK 6

7 Background: Waste Heat Recovery Barriers? Industrial engineers often do not have the time or knowledge to explore all waste heat recovery methods Novel methods of recovery are often ignored Industrial engineers often unsure or uninformed * of the benefits of WHR Expensive consultancy required from start of potential projects *Sinclair (2002) 7

8 Background: Motivation To address the barriers to WHR! Encourage the uptake of WHR projects by: Providing a free consultancy tool in the initial stages of WHR projects Educating industrial engineers about the benefits of novel technologies (such as HP, ORCs) To drive industry towards 100% recovery of waste heat 8

9 Background: Motivation Potential economic/environmental benefits of WHR in UK: Assumptions Cost Savings CO2 Savings Heat Exchanger Replacing Gas Heating Duty of 80% efficiency 570M/year 2.62MtCO2eq/year Replacing Gas Heating Duty of 80% efficiency Heat Pump Using Electric Motor to drive compressor 228M/year 1.12MtCO2eq/year COP = 4 Organic Rankine Cycle Replacing the use of grid electricity Thermal Efficiency = M/year 0.900MtCO2eq/year 9

10 Potential Cost Savings ( M/year) Potential CO2 Emissions Reductions (MtCO2/year) Background: Motivation Potential economic/environmental benefits of WHR: Potential Cost Savings Potential Emissions Reductions 10

11 Methods: Software Overview 11

12 Methods: Data Input Easy to access data: Heat Source/Sink: Nature, P, T, m, μ, ρ, % solids Plant data: hours of operation per year, cost of utilities Simple Questions: Current method of heating the sink? Tolerance to cross-contamination? Tolerance to harmful properties of working fluids? (for HP/ORC) 12

13 Methods: Technology Selection This is done on two levels 13

14 Methods: Technology Selection Level 1: According to plant requirements 14

15 Methods: Technology Selection Level 1: 15

16 Methods: Technology Selection Level 2: According to technology limitations Different heat exchangers have different selection constraints Temperature, Pressure, Fouling limitations Heat Pump/ORC working fluids are selected according to plant limitations Many fluids are flammable and/or toxic - plant must tolerate this 16

17 Methods: Technology Selection Example decision tree leading to selection of heat exchangers for a liquid-liquid duty: 17

18 Methods: Technology Selection 18

19 Methods: Technology Design Heat Exchangers using well established methods such as LMTD method & data from manufacturers Heat Pump more complex Various iteration and optimisation loops required Organic Rankine Cycle more complex Various iteration and optimisation loops required 19

20 Methods: Technology Design Example of a decision tree 20

21 Methods: Technology Design Note: Around 5% of design code for ORC 21

22 Methods: Report First design of equipment: Size, Efficiency/COP, Working Fluid* Economic Results: Estimate Cost, Potential Cost Savings, PB Time Environmental Results: Potential GHG reductions due to WHR For every available option 22

23 Methods: Programming Java is used to build the system knowledgebase and user-interface This allows simple and free dissemination into the industrial domain Java is compatible with all common operating systems Java runtime environment is available free to all users

24 Results: Case Study System is tested using various case studies Including, UK food industry case study leading to the selection of an organic Rankine cycle for WHR Note: Host plant was not previously aware of ORC technology for low-grade WHR 24

25 Results: Case Study WHR in a Crisp Frying Process Exhaust Gas: T = 164 o C 25

26 Results: Case Study Initial User Questions: 1. Check that user has identified a low-grade heat source 2. Ask whether a suitable heat sink has been identified 3. In this case, no heat sink has been identified. Therefore: conversion to electricity is only option 26

27 Results: Case Study Data Input: V. Basic Source Data Input: T = 164 o C Cp = 1.3 kj/kgk m = kg/s T target = 65 o C Cooling water available at 5 o C Some basic plant data (cost of electricity & plant hours of operation) The plant cannot tolerate highly flammable fluids, but can tolerate toxicity 27

28 Results summary Results: Case Study Duty of waste heat recovered: 1350kW Cycle Working Fluid: R245fa (nonflammable) Net Power Output: 170kW Thermal Efficiency: ~13% Units of Electricity generated per year: 1.43M kwh Cost saving: ~ 150K/year GHG reductions: ~750 tco2eq/year Cost estimate: 340K PB time (exc. Maintenance) = 2.25 years 28

29 Results summary Results: Case Study Cycle Diagram is shown Temperatures and pressures at various points in the cycle are shown This should help with any physical designs of the system 29

30 Conclusions Knowledge-based system created for the selection/design of low-grade WHR technology System uses easy to access data System is intuitive and easy to use for an engineer with no previous WHR knowledge Case studies show that the system can provide economical and environmental solutions to WHR 30

31 Further Work Iterative improvements of system Possible inclusion of more options for WHR Testing: Via case studies Third Party Testing: Public V1 will be available very soon I was hoping to hand out copies today but this was not possible Volunteers to test the system/give feedback are sought 31

32 Thank You I d like to acknowledge: Supervisors: Prof. A. Harvey & Prof. D. Reay Industrial collaborators EPSRC richard.law1@ncl.ac.uk 32