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Degradation based optimization models
Introduction Literature review Framework Application & results Conclusion
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![28
References:
[1] Parhizkar, T., & Roshandel, R. (2017). Long term performance degradation analysis and
optimization of anode supported solid oxide fuel cell stacks. Energy Conversion and
Management, 133, 20-30.
[2] Roshandel, R., & Parhizkar, T. (2016). Degradation based optimization framework for long term
applications of energy systems, case study: Solid oxide fuel cell stacks. Energy, 107, 172-181.
[3] Parhizkar, T., Mosleh, A., & Roshandel, R. (2017). Aging based optimal scheduling framework
for power plants using equivalent operating hour approach. Applied Energy, 205, 1345-1363.
[4] Roshandel, R., & Parhizgar, T. (2013). A new approach to optimize the operating conditions of a
polymer electrolyte membrane fuel cell based on degradation mechanisms. Energy Systems, 4(3),
219-237.
Chicago
[5] Sotoodeh, A. F., Parhizkar, T., Mehrgoo, M., Ghazi, M., & Amidpour, M. (2019). Aging based
design and operation optimization of organic rankine cycle systems. Energy Conversion and
Management, 199, 111892.
Chicago](https://image.slidesharecdn.com/literaturereviewondegradationbasedoptimizationmethod-201226015414/85/Literature-Review-on-Degradation-Based-Framework-for-Long-Term-Analysis-and-Optimization-of-Energy-Conversion-Systems-28-320.jpg)
Literature Review on Degradation Based Framework for Long-Term Analysis and Optimization of Energy Conversion Systems
- 1. Degradation Based Framework for Long-Term Analysis and Optimization of Energy Conversion Systems By: Tarannom Parhizkar 1 December 2020
- 3. 3 Performance Time Degradation mechanisms Introduction Literature review Framework Application & results Conclusion Diagnosing degradation mechanisms, helps to define energy conversion system performance more accurately. Degradation effects
- 4. Type of degradation Typical causes Recoverable deg Clogging, scaling and build up of deposits on the working surface Non-recoverable deg Tear, loss of working surface, corrosion/oxidation, erosion. A gradual and irreversible accumulation of damage that occurs during a system’s life cycle. This process is known as degradation 4Degradation definition Introduction Literature review Framework Application & results Conclusion
- 5. 5 Investment cost Operation cost Maintenance cost Income Income timet1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 timet1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 Cost Introduction Literature review Framework Application & results Conclusion Degradation long term economic effects
- 6. 6 Operating conditions have effect on energy conversion components degradation rate.Performance Time Introduction Literature review Framework Application & results Conclusion Research necessity Different environ and operational co
- 7. 7Research objective Life time cost DAMAGE Life time income $ $ Introduction Literature review Framework Application & results Conclusion Developing the framework of “degradation based optimization (DBO)” model by optimizing system operating conditions
- 9. Literature review classification • Degradation based process model Literature review Process Model System output (Power, Heat,…) System input ( Fuel,…) 9 Introduction Literature review Framework Application & results Conclusion
- 10. Literature review classification • Degradation based process model Literature review Process Model System output (Power, Heat,…) System input ( Fuel,…) 10 Introduction Literature review Framework Application & results Conclusion Degradation mechanisms
- 11. Degradation based process models R. Zhou1 et al., 2011. Degradation modeling attempts to characterize the evolution of degradation signals. A gradual and irreversible accumulation of damage that occurs during a system’s life cycle is known as degradation. The observed condition-based signals from Condition Monitoring process are known as degradation signals. 1. 2. 3. 11 Introduction Literature review Framework Application & results Conclusion Degradation definition
- 12. S. Bae et al., 2008. Data-driven model Principle based model Degradation models 12Degradation based process models Introduction Literature review Framework Application & results Conclusion Degradation model classification
- 13. 13 Authors System Purpose Methodology Gebraeel et al 2005 Framework development Residual lifetime prediction Principle based model Y. Zhao 2005 Gas turbine power plant Performance deterioration Data-driven model Haschka et al 2006 SOFC Voltage degradation Data-driven model Bae et al 2010 Degradation rate functions development Degradation rate functions Data-driven model Ryana et al 2012 SOFC Sulfur impurity effect on the performance Data-driven model Kappis 2013 Compressor Degradation effect on performance in different ambient temperatures Principle based model Degradation based process models Introduction Literature review Framework Application & results Conclusion
- 14. 14 Authors System Purpose Methodology Rujian Fu 2015 Lithium ion polymer batteries Battery capacity fade cause Principle based model M. Chandesris 2015 PEM water electrolyzer Influence of temperature and current density Data-driven model Minggao Ouyang 2016 Li-ion battery Capacity prediction Data-driven model ( ) (0) (1 )LT t LT f= ´ - ( , , ,...)f a b g Degradation based process models Introduction Literature review Framework Application & results Conclusion
- 15. Literature review classification 15 • Degradation based optimization model Literature review • Degradation based process model Introduction Literature review Framework Application & results Conclusion
- 16. 16Degradation based optimization models S. K. Agrawal et al., 1999. Dynamic optimization involves optimization over time and state variables depend on time. E. Bryson et al., 1999. P. Whittle et al., 1982. Introduction Literature review Framework Application & results Conclusion Dynamic optimization definition
- 17. 17 Authors System Purpose Methodology Gallestey et al 2002 Gas turbine Minimizing system total cost Data-driven model Antoine et al 2002 Gas turbine Minimizing system total cost Data-driven model Trecae et al 2005 Steam and gas turbine Minimizing system total cost Data-driven model ABB Co 2006 Power plant equipment Different targets regarding degradation Principle based and Data-driven model Degradation based optimization models Introduction Literature review Framework Application & results Conclusion
- 18. 18 Authors System Purpose Methodology Rasmekomen et al 2013 Framework development Optimizing maintenance interval regarding degradation(cost) Data-driven model Kima et al 2013 PEM Optimizing system temperature Data-driven model Ziyou Song 2014 battery/supercapa citor energy storage system Optimal sizing Data-driven model Nur I. Zulkafli 2016 Framework development Planning of production Principle based and Data-driven model Degradation based optimization models Introduction Literature review Framework Application & results Conclusion
- 19. 19 Introduction Literature review Framework Application & results Conclusion Degradation based optimization models Overall concept ABB company., 2002.
- 20. 20 Model Predictive Control (MPC) and Mixed Logical Dynamic (MLD) approach are used to derive the optimal conditions. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion
- 21. 21 E. Gallestey et al., 2002. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion ( ) ( )[ ] t T t T standard aging t t J u c q d c c q dt t + + = - = + -ò ò 1 m aging i i i c Value c = = ´å , 1,2,...,i i dLT c i m dt = = ( ) ( ) (0) icric i i icric i a a t LT t a a - = - Considering aging cost
- 22. 22 Model Predictive Control (MPC) and Mixed Logical Dynamic (MLD) approach are used to derive the optimal conditions. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion
- 23. 23 ABB company,2005. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion ( ) ( 1)LTC AV k AV k= - - Considering aging cost
- 24. 24 Model Predictive Control (MPC) and Mixed Logical Dynamic (MLD) approach are used to derive the optimal conditions. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion
- 25. 25Degradation based optimization models Introduction Literature review Framework Application & results Conclusion C. Bordin et al., 2017. ( )min t t G B t C C+å B t C Pg dg= ´å Power generation (kWh) Degradation cost ($/kWh) Considering aging effect
- 26. 26 OptiMax, ABB company, 2006. Degradation based optimization models Introduction Literature review Framework Application & results Conclusion Software in this field
- 27. 27Strengths and weaknesses Introduction Literature review Framework Application & results Conclusion • Considering aging cost in the objective function • Considering aging effects in the optimization procedure Summary of main strengths and weaknesses of other research Weaknesses Strength • Framework • Any energy conversion system • Operating strategy and objective function • Data-driven and model-based degradation model • The effect of considering degradation in optimization procedure with different objective functions
- 28. 28 References: [1] Parhizkar, T., & Roshandel, R. (2017). Long term performance degradation analysis and optimization of anode supported solid oxide fuel cell stacks. Energy Conversion and Management, 133, 20-30. [2] Roshandel, R., & Parhizkar, T. (2016). Degradation based optimization framework for long term applications of energy systems, case study: Solid oxide fuel cell stacks. Energy, 107, 172-181. [3] Parhizkar, T., Mosleh, A., & Roshandel, R. (2017). Aging based optimal scheduling framework for power plants using equivalent operating hour approach. Applied Energy, 205, 1345-1363. [4] Roshandel, R., & Parhizgar, T. (2013). A new approach to optimize the operating conditions of a polymer electrolyte membrane fuel cell based on degradation mechanisms. Energy Systems, 4(3), 219-237. Chicago [5] Sotoodeh, A. F., Parhizkar, T., Mehrgoo, M., Ghazi, M., & Amidpour, M. (2019). Aging based design and operation optimization of organic rankine cycle systems. Energy Conversion and Management, 199, 111892. Chicago
- 29. 29 The key is not to prioritize what's on your schedule, but to schedule your priorities. Stephen Covey