Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov Decision Process

Journal of Cleaner Production

Volumn 65, Issue , 2014, Pages 184-193

  Sun, Zeyi ^a   Li, Lin ^a  

^a 1120 Science and Engineering Offices   (United States)

Author keywords

Electricity demand response; Markov Decision Process; Real time; Sustainable manufacturing systems

Indexed keywords

AUTOMOTIVE ASSEMBLY LINES; ELECTRICITY DEMAND RESPONSE; ELECTRICITY-CONSUMPTION; INDUSTRIAL MANUFACTURING; MANUFACTURING ENTERPRISE; MARKOV DECISION PROCESSES; REAL TIME; SUSTAINABLE MANUFACTURING;

DECISION MAKING; ELECTRICITY; GREENHOUSE GASES; MANUFACTURE; MARKOV PROCESSES; OFFICE BUILDINGS;

INDUSTRIAL ECONOMICS;

EID: 84893817036     PISSN: 09596526     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclepro.2013.08.033     Document Type: Article

References (87)

1. E. Abele, T. Sielaff, A. Schiffler, and S. Rothenbucher Analyzing energy consumption of machine tool spindle units and identification of potential for improvements of efficiency, Glocalized Solutions for Sustainability in Manufacturing Proceedings of the 18th CIRP International Conference of Life Cycle Engineering, May 2-4, 2011 2011 Technische University Braunschweig Braunschweig, Germany
2. S. Aguado, R. Alvarez, and R. Domingo Model of efficient and sustainable improvements in a lean production system through processes of environmental innovation J. Clean. Prod. 47 2012 141 148
3. S. Ambani, L. Li, and J. Ni Condition-based maintenance decision-making for multiple machine systems J. Manuf. Sci. E-T. ASME 131 3 2009 031009-1
4. S.E. Anderberg, S. Kara, and T. Beno Impact of energy efficiency on computer numerically controlled machining Proc. IMechE., Part B: J. Eng. Manufacture 224 2010 531 541
5. S. Ashok Peak-load management in steel plants Appl. Energ. 83 5 2006 413 424
6. S. Ashok, and R. Banerjee An optimization mode for industrial load management IEEE T. Power Syst. 16 4 2001 879 884
7. J.S. Baldwin, P.M. Allen, B. Winder, and K. Ridgway Modeling manufacturing evolution: thoughts on sustainable industrial development J. Clean. Prod. 13 2005 887 902
8. A. Battaglini, J. Lilliestam, A. Haas, and A. Patt Development of SuperSmart Grids for a more efficient utilisation of electricity from renewable sources J. Clean. Prod. 17 2009 911 918
9. A. Bego, L. Li, and Z. Sun Identification of reservation capacity in critical peak pricing electricity demand response program for sustainable manufacturing systems Int. J. Energ. Res. 2013 10.1002/er.3077
10. R. Bellman Dynamic Programming 1957 Princeton University Press Princeton, U.S
11. R.K. Bhushan Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites J. Clean. Prod. 39 2013 242 254
12. J.E. Braun Reducing energy costs and peak electrical demand through optimal control of building thermal storage ASHRAE Trans. 96 2 1990 839 848
13. J.E. Braun, and N. Chaturvedi An inverse Grey-Box model for transient building load prediction Int. J. HVAC&R Res. 8 1 2002 73 100
14. K. Bunse, M. Vodicka, P. Schönsleben, M. Brülhart, and F.O. Ernst Integrating energy efficiency performance in production management - gap analysis between industrial needs and scientific literature J. Clean. Prod. 19 2011 667 679
15. H.S. Chang, P.J. Fard, S.I. Marcus, and M. Shayman Multi-time scale Markov decision processes IEEE T. Automat. Contr. 48 6 2003 976 987
16. Q. Chang, J. Ni, P. Bandyopadhyay, S. Biller, and G. Xiao Maintenance opportunity planning system J. Manuf. Sci. E-T. ASME 129 3 2007 661 668
17. X. Chao, and F.Y. Chen An optimal production and shutdown strategy when a supplier offers an incentive program Manufacturing Serv. Operations Manage. 7 2 2005 130 143
18. X. Chao, and P.H. Zipkin Optimal policy for a periodic-review inventory system under a supply capacity contract Oper. Res. 56 1 2008 59 68
19. K. Chatterjee, and L. Doyen Energy and mean-payoff parity Markov Decision Processes Proceedings of the 36th International Symposium on Mathematical Foundations of Computer Science (MFCS'11), August 2011 2011 206 218 Warsaw, Poland
20. Z. Chen, L. Wu, and Y. Fu Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization IEEE T. Smart Grid 3 4 2012 1822 1831
21. F. Corno, and F. Razzak Intelligent energy optimization for user intelligible goals in smart home environments IEEE T. Smart Grid 3 4 2012 2128 2135
22. J. Dahmus, and T. Gutowski An environmental analysis of machining Proceedings of IMECE04 2004 ASME International Mechanical Engineering Congress and Exposition, November 13-20, 2004 2004 643 652 Anaheim, California, U.S
23. Y. Dallery On modeling failure and repair times in stochastic models of manufacturing systems using generalized exponential distributions Queueing Syst. 15 1994 199 209
24. D. DeGroff Green environment: decision-making and power utility optimization towards smart-grid options Smart Grid Renew. Energy 1 2010 32 39
25. M. Despeisse, P.D. Ball, S. Evans, and A. Levers Industrial ecology at factory level - a conceptual model J. Clean. Prod. 31 2012 30 39
26. M. Despeisse, M.R. Oates, and P.D. Ball Sustainable manufacturing tactics and cross-functional factory modeling J. Clean. Prod. 42 2013 31 41
27. A. Dietmair, and A. Verl A generic energy consumption model for decision making and energy efficiency optimization in manufacturing Int. J. Sust. E. 2 2 2009 123 133
28. A. Dietmair, and A. Verl Energy consumption forecasting and optimization for tool machines Mod. Machinery Sci. J. 2 2 2009 62 67
29. M. Doostizadeh, and H. Ghasemi A day-ahead electricity pricing model based on smart metering and demand-side management Energy 46 2012 221 230
30. F. Draganescu, M. Gheorghe, and C.V. Doicin Models of machine tool efficiency and specific consumed energy J. Mater. Process. Tech. 141 1 2003 9 15
31. J.R. Duflou, J.W. Sutherland, D. Dornfeld, C. Herrmann, J. Jeswiet, S. Kara, M. Hauschild, and K. Kellens Towards energy and resource efficient manufacturing: a processes and systems approach CIRP Ann.-Manuf. Techn. 61 2012 587 609
32. Edison Electric Institute Rising Electricity Costs: a Challenge for Consumers, Regulators, and Utilities 2006 Washington D.C., U.S http://www.eei.org/whatwedo/PublicPolicyAdvocacy/StateRegulation/Documents/ rising-electricity-costs.pdf (06.04.2013)
33. EIA (Energy Information Administration) Annual Energy Outlook 2006 2006 Washington D.C., U.S http://www.scag.ca.gov/rcp/pdf/publications/1- 2006AnnualEnergyOutlook.pdf (06.04.2013)
34. EIA (Energy Information Administration) Electric Power Annual 2010 2011 Washington D.C., U.S http://www.eia.gov/electricity/annual/pdf/epa.pdf (07.04.2013)
35. Electric Power Research Institute Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the U.S. (2010-2030) 2009 Palo Alto, CA, U.S http://www.edisonfoundation.net/IEE/Documents/EPRI- SummaryAssessmentAchievableEEPotential0109.pdf (06.04.2013)
36. P. Faria, and Z. Vale Demand response in electrical energy supply: an optimal real time pricing approach Energy 36 8 2011 5374 5384
37. P. Faria, Z. Vale, J. Soares, and J. Ferreira Demand response management in power systems using a particle swarm optimization approach IEEE Intell. Syst. 2011 10.1109/MIS.2011.35
38. FERC (Federal Energy Regulatory Commission) Assessment of Demand Response and Advanced Metering 2008 Washington D.C., U.S http://www.ferc.gov/legal/ staff-reports/12-08-demand-response.pdf (06.04.2013)
39. FERC (Federal Energy Regulatory Commission) A National Assessment of Demand Response Potential 2009 Washington D.C., U.S http://www.ferc.gov/legal/ staff-reports/06-09-demand-response.pdf (06.04.2013)
40. M. Fernandez, L. Li, and Z. Sun Just-For-Peak buffer inventory for peak electricity demand reduction of manufacturing systems Int. J. Prod. Econ. 2013 http://dx.doi.org/10.1016/j.ijpe.2013.06.020
41. K. Friedrich, M. Eldridge, D. York, P. Witte, and M. Kushler Saving Energy Cost-effectively: a National Review of the Cost of Energy Saved through Utility-sector Energy Efficiency Programs, American Council for an Energy-efficient Economy 2009 Washington D.C., U.S http://dandelion-patch.mit. edu/afs/athena.mit.edu/dept/cron/project/urban-sustainability/ Energy%20Efficiency-Brendan%20McEwen/LG%20EE%20Policy%20Sectors/Costs/ Friedrich%20et%20al%202009%20-%20EE%20Costs.pdf (06.04.2013)
42. G. Ghatikar, A. McKane, S. Goli, P. Therkelsen, and D. Olsen Assessing the Control Systems Capacity for Demand Response in California Industries 2012 Lawrence Berkeley National Laboratory Berkeley, CA, U.S http://drrc.lbl.gov/ sites/drrc.lbl.gov/files/LBNL-5319E.pdf (06.04.2013)
43. B. Givan, and R. Parr An Introduction to Markov Decision Processes 2013 http://www.cs.rice.edu/∼vardi/dag01/givan1.pdf (06.04.2013)
44. C. Goldman, M. Reid, R. Levy, and A. Silverstein National Action Plan for Energy Efficiency, Coordination of Energy Efficiency and Demand Response 2010 United States Environmental Protection Agency Washington D.C., U.S http://www.epa.gov/cleanenergy/documents/suca/ee-and-dr.pdf (06.04.2013)
45. L.A. Greening Demand response resources: who is responsible for implementation in a deregulated market? Energy 35 4 2010 1518 1525
46. T. Gutowski, J. Dahmus, and A. Thiriez Electrical energy requirements for manufacturing processes Proceedings of 13th CIRP International Conference of Life Cycle Engineering, May 31-June 2, 2006 2006 Leuven, Belgium
47. P. Heikkurinen, and K.J. Bonnedahl Corporate responsibility for sustainable development: a review and conceptual comparison of market-and stakeholder-oriented strategies J. Clean. Prod. 43 2013 191 198
48. G.P. Henze, C. Felsmann, and G. Knabe Evaluation of optimal control for active and passive building thermal storage Int. J. Therm. Sci. 43 2004 173 183
49. S. Hu, F. Liu, Y. He, and T. Hu An on-line approach for energy efficiency monitoring of machine tools J. Clean. Prod. 27 2012 133 140
50. A.B. Karami, L. Jeanpierre, and A.I. Mouaddib Partially observable Markov Decision Process for managing robot collaboration with human Proceedings of 21st International Conference on Tools with Artificial Intelligence, November 2-4, 2009 2009 518 521 Newark, NJ, U.S
51. V.K. Konstantinos, and E.E. Sascha Markov Decision Processes with delays and asynchronous cost collection IEEE T. Automat. Contr. 48 4 2003 568 574
52. P. Laroche, F. Charpillet, and R. Schott Mobile robotics planning using abstract Markov decision processes Proceedings of 11th IEEE International Conference on Tools with Artificial Intelligence, November 9-11, 1999 1999 299 306 Chicago, IL
53. R.E. Lave A Markov Decision Process for economic quality control IEEE T. Syst. Sci. Cyb. 2 1 1966 45 54
54. G. Lewis Strategies to Increase California Food Processing Industry Demand Response Participation: a Scoping Study 2007 Lawrence Berkeley National Laboratory Berkeley, CA, U.S. http://drrc.lbl.gov/system/files/lbnl-63668.pdf (06.04.2013)
55. G. Lewis, I. Rhyne, and B. Atkinson California Food Processing Industry, Wastewater Demonstration Project: Phase I Final Report 2009 Lawrence Berkeley National Laboratory Berkeley, CA, U.S http://drrc.lbl.gov/sites/drrc.lbl.gov/ files/lbnl-2585e.pdf (06.04.2013)
56. J. Li, and S.M. Meerkov Production Systems Engineering 2008 Springer New York, U.S
57. L. Li, Q. Chang, and J. Ni Data driven bottleneck detection of manufacturing systems Int. J. Prod. Res. 47 18 2009 5019 5036
58. L. Li, and Z. Sun Dynamic energy control for energy efficiency improvement of sustainable manufacturing systems using Markov Decision Process IEEE T. Syst. Man Cy. A 2013 10.1109/TSMC.2013.2256856 (in press)
59. L. Li, Z. Sun, H. Yang, and F. Gu Simulation-based energy efficiency improvement for sustainable manufacturing systems Proceedings of the 2012 ASME International Manufacturing Science and Engineering Conference (MSEC), Paper Number MESC 2012-7242, June 4-8, 2012 2012 1033 1039 Notre Dame, IN, U.S
60. L. Li, J. Yan, and Z. Xing Energy requirements evaluation of milling machines based on thermal equilibrium and empirical modeling J. Clean. Prod. 52 2013 113 121
61. W. Li, and S. Kara An empirical model for predicting energy consumption of manufacturing processes: a case of turning process Proc. IMechE, Part B: J. Eng. Manufacture 225 2010 1636 1646
62. W. Li, A. Zein, S. Kara, and C. Hermann An investigation into fixed energy consumption of machine tools, glocalized solutions for sustainability in Manufacturing 2011 Technische University Braunschweig Braunschweig, Germany
63. Y. Li, B.L. Ng, M. Trayer, and J. Liu Automated residential demand response: algorithmic implications of pricing models IEEE T. Smart Grid 3 4 2012 1712 1721
64. Y. Liang, D. Levine, and Z. Shen Thermostats for the smart grid: models, benchmarks, and insights Energy J. 33 4 2012 61 96
65. A. McKane, I. Rhyne, A. Lekov, L. Thompson, and M.A. Piette Automating Demand Response: the Missing Link in the Electricity Value Chain 2008 Lawrence Berkeley National Laboratory Berkeley, CA, U.S http://drrc.lbl.gov/sites/drrc. lbl.gov/files/lbnl-2736e.pdf (06.04.2013)
66. W.Q. Meeker, and L.A. Escobar Statistical Methods for Reliability Data 1998 John Wiley & Sons New York, U.S
67. L.J. Mirman, O.F. Morand, and K.L. Reffett A qualitative approach to Markovian equilibrium in infinite horizon economies with capital J. Econ. Theory 139 1 2008 75 98
68. N. Motegi, M.A. Piette, D.S. Watson, S. Kiliccote, and P. Xu Introduction to Commercial Building Control Strategies and Techniques for Demand Response, Environmental Energy Technologies Division 2007 Lawrence Berkeley National Laboratory Berkeley, CA, U.S. http://gaia.lbl.gov/btech/papers/59975.pdf (06.04.2013)
69. G. Mouzon, and M.B. Yildirim A framework to minimize total energy consumption and total tardiness on a single machine Int. J. Sust. E. 1 2 2008 105 116
70. New York ISO Emergency Demand Response Program Manual NY, U.S 2010 http://www.nyiso.com/public/webdocs/products/demand-response/ emergency-demand-response/edrp-mnl.pdf (06.04.2013)
71. W.B. Powell Approximate Dynamic Programming: Solving the Curses of Dimensionality second ed. 2011 John Wiley & Sons Hoboken, U.S
72. ProModel, Inc. http://www.promodel.com/ (06.04.2013).
73. M. Schipper Energy-related Carbon Dioxide Emissions in U.S. Manufacturing 2006 U.S. Energy Information Administration Washington D.C., U.S DOE/EIA-0573(2005) http://www.eia.doe.gov/oiaf/1605/ggrpt/pdf/industry-mecs.pdf (07.04.2013)
74. G.M. Shafiullah, M.T.O. Amanullah, A.B.M. Shawkat Ali, and P. Wolfs Smart grid for a sustainable future Smart Grid Renew. Energy 4 2013 23 34
75. O. Siddiqui The Green Grid - Energy Savings and Carbon Emissions Reductions Enabled by a Smart Grid 2008 Electric Power Research Institute Palo Alto, CA, U.S http://www.smartgridnews.com/artman/uploads/1/SGNR-2009-EPRI- Green-Grid-June-2008.pdf (06.04.2013)
76. Z. Sun, S. Biller, F. Gu, and L. Li Energy consumption reduction for sustainable manufacturing systems considering machines with multiple-power states Proceedings of the 2011 ASME International Manufacturing Science and Engineering Conference (MSEC), Paper Number MSEC 2011-50069, June 13-17, 2011 2011 99 103 Corvallis, OR, U.S
77. Z. Sun, and L. Li Opportunity estimation for real time energy control of sustainable manufacturing systems IEEE T. Autom. Sci. Eng. 10 1 2013 38 44
78. A. Trianni, E. Cagno, P. Thollander, and S. Backlund Barriers to industrial energy efficiency in foundries: a European comparison J. Clean. Prod. 40 2013 161 176
79. I. Vassileva, F. Wallin, and E. Dahlquist Understanding energy consumption behavior for future demand response strategy development Energy 46 2012 94 100
80. C. Walsh, and P. Thornley Barriers to improving energy efficiency within the process industries with a focus on low grade heat utilization J. Clean. Prod. 23 2012 138 146
81. L. Wang, Z. Wang, and R. Yang Intelligent multiagent control system for energy and comfort management in smart and sustainable buildings IEEE T. Smart Grid 3 2 2012 605 617
82. Unpublished results Y. Wang, and L. Li Time-of-Use Based Production Scheduling towards Energy-efficient, Demand-responsive, and Cost-effective Manufacturing 2013 submitted to Energy, revision
83. Y. Wang, I.R. Pordanjani, and W. Xu An event-driven demand response scheme for power system security enhancement IEEE T. Smart Grid 2 1 2011 23 29
84. Y. Ye The simplex and policy-iteration methods are strongly polynomial for the Markov decision problem with fixed discount rate Math. Oper. Res. 36 4 2011 593 603
85. P. Yi, X. Dong, A. Iwayemi, C. Zhou, and S. Li Real-time opportunistic scheduling for residential demand response IEEE T. Smart Grid 4 1 2013 227 234
86. S. Yousefi, M.P. Moghaddam, and V.J. Majd Optimal real time pricing in an agent-based retail market using a comprehensive demand response model Energy 36 9 2011 5716 5727
87. R. Yu, W. Yang, and S. Rahardja A statistical demand-price model with its application in optimal real-time price IEEE T. Smart Grid 3 4 2012 1734 1742