Nonconvex model predictive control for commercial refrigeration

International Journal of Control

Volumn 86, Issue 8, 2013, Pages 1349-1366

  Hovgaard, Tobias Gybel ^a,b   Boyd, Stephen ^c   Larsen, Lars F S ^a   Jørgensen, John Bagterp ^b  

^a Vestas Technology R and D   (Denmark)

^b TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^c Stanford University   (United States)

Author keywords

energy management; nonlinear control systems; optimisation methods; predictive control; smart grids

Indexed keywords

CONVEX QUADRATIC PROGRAMMING; EVAPORATION TEMPERATURE; OPTIMISATION METHOD; PREDICTIVE CONTROL; RENEWABLE ENERGY SOURCE; SMART GRID; TEMPERATURE DEPENDENCE; THERMODYNAMIC EFFICIENCY;

COMPUTER SIMULATION; COSTS; ELECTRICITY; ENERGY MANAGEMENT; MODEL PREDICTIVE CONTROL; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; RENEWABLE ENERGY RESOURCES; SMART POWER GRIDS;

PREDICTIVE CONTROL SYSTEMS;

EID: 84882448539     PISSN: 00207179     EISSN: 13665820     Source Type: Journal    
DOI: 10.1080/00207179.2012.742207     Document Type: Article

References (58)

1. Andersson, SL, Elofsson, AK, Galus, MD, Göransson, L, Karlsson, S, Johnsson, F, and, Andersson, G. 2010. Plug-in Hybrid Electric Vehicles as Regulating Power Providers: Case Studies of Sweden and Germany. Energy Policy, 38: 2751-2762. doi: 10.1016/j.enpol.2010.01.006
2. Angeli, D, Amrit, R, and, Rawlings, J. 2012. On Average Performance and Stability of Economic Model Predictive Control. IEEE Transactions on Automatic Control, 57 (7): 1615-1626. doi: 10.1109/TAC.2011.2179349
3. Arteconi, A, Hewitt, NJ, and, Polonara, F. 2012. State of the Art of Thermal Storage for Demand-side Management. Applied Energy, 93: 371-389. doi: 10.1016/j.apenergy.2011.12.045
4. Biegler, L. 2009. " Efficient Nonlinear Programming Algorithms for Chemical Process Control and Operations ". In System Modeling and Optimization, IFIP Advances in Information and Communication Technology, Edited by: Korytowski, A, Malanowski, K, Mitkowski, W and Szymkat, M. Vol. 312, 21-35. Boston: Springer.
5. Blarke, MB, and, Dotzauer, E. 2011. Intermittency-friendly and High-efficiency Cogeneration: Operational Optimisation of Cogeneration with Compression Heat Pump, Flue Gas Heat Recovery, and Intermediate Cold Storage. Energy, 36: 6867-6878. doi: 10.1016/j.energy.2011.10.008
6. Boggs, PT, and, Tolle, JW. 1995. Sequential Quadratic Programming. Acta Numerica, 4: 1-51. doi: 10.1017/S0962492900002518
7. Boyd, S, and, Vandenberghe, L. 2004. Convex Optimization, Cambridge University Press, New York.
8. Bush, R, and, Wolf, G. 2009. Utilities Load Shift with Thermal Storage. Transmission & Distribution World, 12
9. Camacho, EF, Samad, T, Garcia-Sanz, M, and, Hiskens, I. 2011. " Control for Renewable Energy and Smart Grids ". In The Impact of Control Technology, Control Systems Society, Edited by: Samad, T and Annaswamy, AM. 69-88. IEEE Control Systems Society.
10. Diehl, M, Amrit, R, and, Rawlings, JB. 2011. A Lyapunov Function for Economic Optimizing Model Predictive Control. IEEE Transactions on Automatic Control, 56: 703-707. doi: 10.1109/TAC.2010.2101291
11. Diehl, M, Bock, HG, Schlo, JP, Findeisen, R, Nagy, Z, and, Allgöwer, F. 2002. Real-time Optimisation and Nonlinear Model Predictive Control of Processes Governed by Differential Algebraic Equations. Journal of Process Control, 12: 577-585. doi: 10.1016/S0959-1524(01)00023-3
12. Diehl, M, Ferreau, H, and, Haverbeke, N. 2009. " Efficient Numerical Methods for Nonlinear MPC and Moving Horizon Estimation ". In Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, Edited by: Magni, L, Raimondo, D and Allgöwer, F. Vol. 384, 391-417. Berlin/Heidelberg: Springer.
13. Dinh, QT, Savorgnan, C, and, Diehl, M. 2011. Real-time Sequential Convex Programming for Nonlinear Model Predictive Control and Application to a Hydro-power Plant. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). 2011. pp. 5905-5910.
14. Edlund, K, Bendtsen, JD, and, Jørgensen, JB. 2011. Hierarchical Model-based Predictive Control of a Power Plant Portfolio. Control Engineering Practice, 19: 1126-1136. doi: 10.1016/j.conengprac.2011.06.002
15. Elliott, MS, and, Rasmussen, BP. 2008. Model-based Predictive Control of a Multi-evaporator Vapor Compression Cooling Cycle. Proceedings of the American Control Conference. 2008. pp. 1463-1468.
16. Energinet.dk, (2011), Potential and Opportunities for Flexible Electricity Consumption with Special Focus on Individual Heat Pumps (in Danish), Technical Report, Energinet.dk, The Danish TSO owned by the Danish Climate and Energy Ministry, Denmark
17. Finn, P, Fitzpatrick, C, Connolly, D, Leahy, M, and, Relihan, L. 2011. Facilitation of Renewable Electricity using Price Based Appliance Control in Irelands Electricity Market. Energy, 36: 2952-2960. doi: 10.1016/j.energy.2011. 02.038
18. Galanis, G, and, Anadranistakis, M. 2002. A One-dimensional Kalman Filter for the Correction of Near Surface Temperature Forecasts. Meteorological Applications, 9: 437-441. doi: 10.1017/S1350482702004061
19. Grancharova, A, Johansen, T, and, Tøndel, P. 2007. " Computational Aspects of Approximate Explicit Nonlinear Model Predictive Control ". In Asssessmsnt and Future Directions of Nonlinear Model Predictive Control, Lecture Notes in Control and Information Sciences, Edited by: Findeisen, R, Allgöwer, F and Biegler, L. Vol. 358, 181-192. Berlin/Heidelberg: Springer.
20. Halvgaard, R, Poulsen, NK, Madsen, H, and, Jørgensen, JB. 2012. " Economic Model Predictive Control for Building Climate Control in a Smart Grid ". In in 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) 1-6.
21. Han, S, Han, S, and, Sezaki, K. 2010. Development of an Optimal Vehicle-to-grid Aggregator for Frequency Regulation. IEEE Transactions on Smart Grid, 1: 65-72. doi: 10.1109/TSG.2010.2045163
22. Hindi, H, Greene, D, and, Laventall, C. 2012. " Coordinating Regulation and Demand Response in Electric Power Grids: Direct and Price-based Tracking using Multirate Economic Model Predictive Control ". In Control and Optimization Methods for Electric Smart Grids, Power Electronics and Power Systems, Edited by: Chakrabortty, A and Ilic, MD. Vol. 3, 111-131. US: Springer New York.
23. Houska, B, Ferreau, H, and, Diehl, M. 2010. ACADO Toolkit-An Open Source Framework for Automatic Control and Dynamic Optimization. Optimal Control Applications and Methods, 32 (3): 298-312. doi: 10.1002/oca.939
24. Hovgaard, TG, Edlund, K, and, Jørgensen, JB. 2010. The Potential of Economic MPC for Power Management. Proceedings of the 49th IEEE Conference on Decision and Control, 2010. 2010. pp. 7533-7538.
25. Hovgaard, TG, Larsen, LFS, Edlund, K, and, Jørgensen, JB. 2012a. Model Predictive Control Technologies for Efficient and Flexible Power Consumption in Refrigeration Systems. Energy, 44: 105-116. doi: 10.1016/j.energy.2011.12.007
26. Hovgaard, TG, Larsen, LFS, and, Jørgensen, JB. 2011a. Flexible and Cost Efficient Power Consumption using Economic MPC-A Supermarket Refrigeration Benchmark. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference. pp. 848-854.
27. Hovgaard, TG, Larsen, LFS, and, Jørgensen, JB. 2011b. Robust Economic MPC for a Power Management Scenario with Uncertainties. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference. 2011b. pp. 1515-1520.
28. Hovgaard, TG, Larsen, LFS, Skovrup, MJ, and, Jørgensen, JB. 2012b. Analyzing Control Challenges for Thermal Energy Storage in Foodstuffs. Proceedings of the IEEE International Conference on Control Applications (CCA) part of the IEEE Multi-Conference on Systems and Control (MSC). pp. 956-961.
29. Hovgaard, TG, Larsen, LFS, Skovrup, MJ, and, Jørgensen, JB. 2012c. Optimal Energy Consumption in Refrigeration Systems-Modelling and Non-convex Optimisation. The Canadian Journal of Chemical Engineering, 90 (6): 1426-1433. doi: 10.1002/cjce.21672
30. Jerez, JL, Constantinides, GA, Kerrigan, EC, and, Ling, KV. 2011. Parallel MPC for Real-time FPGA-based Implementation. in Proceedings of the 18th IFAC World Congress,: 1338-1343.
31. Jørgensen, JB. 2005. " Moving Horizon Estimation and Control ". In Ph.D. thesis, Department of Chemical Engineering, Technical University of Denmark.
32. Jørgensen, JB, Rawlings, JB, and, Jørgensen, SB. 2004. Numerical Methods for Large-scale Moving Horizon Estimation and Control. in Proceedings of the International Symposium on Dynamics and Control Process Systems (DYCOPS),: 895-900.
33. Kirschen, DS. 2003. Demand-side View of Electricity Markets. IEEE Transactions on Power Systems, 18: 520-527. doi: 10.1109/TPWRS.2003.810692
34. Kraning, M, Wang, Y, Akuiyibo, E, and, Boyd, S. 2011. Operation and Configuration of a Storage Portfolio via Convex Optimization. in Proceedings of the 18th IFAC World Congress,: 10487-10492.
35. Larsen, LFS, Thybo, C, and, Rasmussen, H. 2007. Potential Energy Savings Optimizing the Daily Operation of Refrigeration Systems. Proceedings of the European Control Conference. pp. 4759-4764. Kos, Greece
36. Leducq, D, Guilpart, J, and, Trystram, G. 2006. Nonlinear Predictive Control of a Vapour Compression Cycle. International Journal of Refrigeration, 29: 761-772.
37. Leephakpreeda, T. 2012. Implementation of Adaptive Indoor Comfort Temperature Control via Embedded System for Air-conditioning Unit. Journal of Mechanical Science and Technology, 26: 259-268. doi: 10.1007/s12206-011-0920-z
38. Ma, J, Qin, J, Salsbury, T, and, Xu, P. 2012. Demand Reduction in Building Energy Systems Based on Economic Model Predictive Control. Chemical Engineering Science, 67: 92-100. doi: 10.1016/j.ces.2011.07.052
39. Ma, Y, and, Borrelli, F. 2012. Fast Stochastic Predictive Control for Building Temperature Regulation. Proceedings of the American Control Conference (ACC), 2012. pp. 3075-3080.
40. Ma, Y, Borrelli, F, Hencey, B, Coffey, B, Bengea, S, and, Haves, P. 2012a. Model Predictive Control for the Operation of Building Cooling Systems. IEEE Transactions on Control Systems Technology, 20: 796-803. doi: 10.1109/TCST.2011.2124461
41. Ma, Y, Kelman, A, Daly, A, and, Borrelli, F. 2012b. Predictive Control for Energy Efficient Buildings with Thermal Storage: Modeling, Stimulation, and Experiments. IEEE Control Systems, 32: 44-64. doi: 10.1109/MCS.2011.2172532
42. Mattingley, J, and, Boyd, S. 2012. CVXGEN: A Code Generator for Embedded Convex Optimisation. Optimization and Engineering, 13: 1-27. doi: 10.1007/s11081-011-9176-9
43. Mattingley, J, Wang, Y, and, Boyd, S. 2011. Receding Horizon Control. IEEE Control Systems Magazine, 31: 52-65.
44. Mohsenian-Rad, AH, and, Leon-Garcia, A. 2010. Optimal Residential Load Control with Price Prediction in Real-time Electricity Pricing Environments. IEEE Transactions on Smart Grid, 1: 120-133. doi: 10.1109/TSG.2010.2055903
45. Molina-Garcia, A, Kessler, M, Fuentes, JA, and, Gomez-Lazaro, E. 2011. Probabilistic Characterization of Thermostatically Controlled Loads to Model the Impact of Demand Response Programs. IEEE Transactions on Power Systems, 26: 241-251. doi: 10.1109/TPWRS.2010.2047659
46. O'Donoghue, B, Stathopoulos, G, and, Boyd, S. 2012. A Splitting Method for Optimal Control. http://www.stanford.edu/~boyd/papers/oper-splt-ctrl.html
47. Oldewurtel, F, Parisio, A, Jones, CN, Gyalistras, D, Gwerder, M, Stauch, V, Lehmann, B, and, Morari, M. 2012. Use of Model Predictive Control and Weather Forecasts for Energy Efficient Building Climate Control. Energy and Buildings, 45: 15-27. doi: 10.1016/j.enbuild.2011.09.022
48. Oldewurtel, F, Parisio, A, Jones, C, Morari, M, Gyalistras, D, Gwerder, M, Stauch, V, Lehmann, B, and, Wirth, K. 2010. Energy Efficient Building Climate Control using Stochastic Model Predictive Control and Weather Predictions. Proceedings of the American Control Conference (ACC). pp. 5100-5105.
49. Pina, A, Silva, C, and, Ferrão, P. 2012. The Impact of Demand Side Management Strategies in the Penetration of Renewable Electricity. Energy, 41: 128-137. doi: 10.1016/j.energy.2011.06.013
50. Qin, SJ, and, Badgwell, TA. 2003. A Survey of Industrial Model Predictive Control Technology. Control engineering practice, 11: 733-764. doi: 10.1016/S0967-0661(02)00186-7
51. Rawlings, JB, and, Amrit, R. 2009. Optimizing Process Economic Performance using Model Predictive Control. Nonlinear Model Predictive Control: Towards New Challenging Applications,: 119-138. doi: 10.1007/978-3-642-01094-1
52. Saele, H, and, Grande, OS. 2011. Demand Response from Household Customers: Experiences from a Pilot Study in Norway. IEEE Transactions on Smart Grid, 2: 90-97. doi: 10.1109/TSG.2010.2104165
53. Sarabia, D, Capraro, F, Larsen, LFS, and, de Prada, C. 2008. Hybrid NMPC of Supermarket Display Cases. Control Engineering Practice, 17: 428-441. doi: 10.1016/j.conengprac.2008.09.003
54. Skovrup, MJ. 2000. " Thermodynamic and Thermophysical Properties of Refrigerants-Software Package in Borland Delphi ". In Technical Report, Department of Energy Engineering, Technical University of Denmark Kgs. Lyngby, Denmark
55. Sonntag, C, Devanathan, A, and, Engell, S. 2008. Hybrid NMPC of a Supermarket Refrigeration System using Sequential Optimization. in Proceedings of 17th IFAC World Congress,: pp. 13901-13906.
56. Van Harmelen, GL. 2001. The Virtual Power Station Targeting Residential, Industrial and Commercial Controllable Loads. Proceedings of IFAC Conference on Technology Transfer in Developing Countries-Automation in Infrastructure Creation (DECOM-TT 2000). pp. 45-48.
57. Wang, Y, and, Boyd, S. 2010. Fast Model Predictive Control using Online Optimization. IEEE Transactions on Control Systems Technology, 18: 267-278. doi: 10.1109/TCST.2009.2017934
58. Zeilinger, MN, Jones, CN, and, Morari, M. 2008. Real-time Suboptimal Model Predictive Control using a Combination of Explicit MPC and Online Optimisation. Proceedings of the 47th IEEE Conference on Decision and Control (CDC). pp. 4718-4723.