Identification of reservation capacity in critical peak pricing electricity demand response program for sustainable manufacturing systems

International Journal of Energy Research

Volumn 38, Issue 6, 2014, Pages 728-736

  Bego, Andres ^a   Li, Lin ^a   Sun, Zeyi ^a  

^a 1120 Science and Engineering Offices   (United States)

Author keywords

Critical Peak Pricing; Electricity demand response; Sustainable manufacturing systems

Indexed keywords

COSTS; ELECTRICITY; INDUSTRIAL ECONOMICS; MANUFACTURE; MATHEMATICAL MODELS; NONLINEAR PROGRAMMING; NUMERICAL METHODS; PRODUCTION CONTROL; PRODUCTION ENGINEERING;

CRITICAL PEAK PRICING; CRITICAL PEAK PRICING (CPP); DEMAND RESPONSE PROGRAMS; ELECTRICITY DEMAND RESPONSE; MANUFACTURING ENTERPRISE; MIXED-INTEGER NONLINEAR PROGRAMMING; NEAR-OPTIMAL SOLUTIONS; SUSTAINABLE MANUFACTURING;

APPLICATION PROGRAMS;

EID: 84897473695     PISSN: 0363907X     EISSN: 1099114X     Source Type: Journal    
DOI: 10.1002/er.3077     Document Type: Article

References (39)

1. Bloomenergy. White Paper, Understanding California's electricity prices. (Available from: http://c0688662.cdn.cloudfiles.rackspacecloud.com/downloads_pdf_White_Paper_Calif_Elec_Prices.pdf). Accessed on 02/14/2013.
2. Energy Information Administration. Annual energy outlook 2010 with projections to 2035. April 2010. (Available from: http://www.eia.gov/oiaf/aeo/pdf/0383(2010).pdf). Accessed on 02/14/2013.
3. Sorensen B. A sustainable energy future: Construction of demand and renewable energy supply scenarios. International Journal of Energy Research 2008; 32(5):436-470.
4. Dincer I, Rosen MA. A worldwide perspective on energy, environment and sustainable development. International Journal of Energy Research 1998; 22(15):1305-1321.
5. Purcell F, McMullan JT, McCrea A. Sustainable energy development and greenhouse gas emissions in an island power system. International Journal of Energy Research 2000; 24(4):321-348.
6. McEvoy D, Gibbs DC, Longhurst JWS. City-regions and the development of sustainable energy-supply systems. International Journal of Energy Research 2000; 24(3):215-237.
7. Chupka M, Earle R, Fox-Penner P, Hledik R. Transforming America's power industry: the investment challenge 2010-2030. 2008. (Available from: http://www.brattle.com/_documents/uploadlibrary/upload725.pdf). Accessed on 02/14/2013.
8. Federal Energy Regulatory Commission. December 20, 2012. (Available from: http://www.ferc.gov/industries/electric/indus-act/demand-response/dem-res-adv-metering.asp). Accessed on 02/14/2013.
9. Goldman C, Reid M, Levy R, Silverstein A. Coordination of energy efficiency and demand response. Lawrence Berkeley National Laboratory: Berkeley, CA, USA, 2010.
10. Siddiqui O. The green grid - Energy savings and carbon emissions reductions enabled by a smart grid. Electric Power Research Institute: Palo Alto, CA, USA, 2008.
11. Yin R, Xu P, Piette M, Kiliccote S. Study on auto-DR and pre-cooling of commercial buildings with thermal mass in California. Energy and Buildings 2009; 42(7):967-975.
12. Houwing M, Negenborn RR, Schutter BD. Demand response with micro-CHP system. Proceedings of the IEEE 2011; 99(1):200-213.
13. Braun JE. Reducing energy costs and peak electrical demand through optimal control of building thermal storage. ASHRAE Transactions 1990; 96(2):839-848.
14. Corno F, Razzak F. Intelligent energy optimization for user intelligible goals in smart home environments. IEEE Transactions on Smart Grid 2012; 3(4):2128-2135.
15. Liang Y, Levine DI, Shen Z. Thermostats for the smart grid: models, benchmarks, and insights. Energy Journal 2012; 33(4):61-95.
16. Wang L, Zhu W, Yang R. Intelligent multiagent control system for energy and comfort management in smart and sustainable buildings. IEEE Transactions on Smart Grid 2012; 3(2):605-617.
17. Paatero JV, Lund PD. A model for generating household electricity load profiles. International Journal of Energy Research 2006; 30(5):273-290.
18. Zhang H, Zhao F, Sutherland JW. Manufacturing scheduling for reduced energy cost in a smart grid scenario. Proceedings of 20th CIRP International Conference on Life Cycle Engineering, Singapore, 2013.
19. Li L, Sun Z, Tang Z. Real time electricity demand response for sustainable manufacturing systems: challenges and a case study. Proceedings of the Eighth IEEE International Conference on Automation Science and Engineering, Seoul, Korea, 20-24 August 2012; 353-357.
20. Faruqui A, Hledik R, Newell S, Pfeifenberger J. The power of five percent: How dynamic pricing can save $35 billion in electricity costs. The Brattle Group, Inc, 2007. (Available from: http://www.brattle.com/_documents/UploadLibrary/Upload574.pdf). Accessed on 02/14/2013.
21. Alghandoor A, Phelan PE, Villalobos R, Phelan BE. U.S. manufacturing aggregate energy intensity decomposition: The application of multivariate regression analysis. International Journal of Energy Research 2008; 32(2):91-106.
22. Al-Ghandoor A, Phelan PE, Villalobos R, Phelan BE. Modeling and forecasting the U.S. manufacturing aggregate energy intensity. International Journal of Energy Research 2008; 32(6):501-513.
23. Al-Shehri A. A simple forecasting model for industrial electric energy consumption. International Journal of Energy Research 2000; 24(8):719-726.
24. Despeisse M, Ball PD, Evans S, Levers A. Industrial ecology at factory level-a conceptual model. Journal of Cleaner Production 2012; 31:30-39.
25. Aguado S, Alvarez R, Domingo R. Model of efficient and sustainable improvements in a lean production system through processes of environmental innovation. Journal of Cleaner Production 2013; 47:141-148.
26. Chao X, Chen F. Y. An optimal production and shutdown strategy when a supplier offers an incentive program. Manufacturing & Service Operations Management 2005; 7(2):130-143.
27. Chao X, Zipkin PH. Optimal policy for a periodic-review inventory system under a supply capacity contract. Operations Research 2008; 56(1):59-68.
28. Pacific Electric & Gas. 2013. (Available from: http://www.pge.com/mybusiness/energysavingsrebates/demandresponse/obmcppilot/index.shtml). Accessed on 02/14/2013.
29. Motoranddrives.com. (Available from: http://www.motorsanddrives.com/cowern/motorterms10.html). Accessed on 02/14/2013.
30. Fernandez M, Li L, Sun Z. "Just-For-Peak" buffer inventory for peak electricity demand reduction of manufacturing systems. Accepted by International Journal of Production Economics 2013.
31. Ashok S, Banerjee R. An optimization mode for industrial load management. IEEE Transactions on Power Systems 2001; 16(4):879-884.
32. Ashok S. Peak-load management in steel plants. Applied Energy 2006; 83(5):413-424.
33. San Diego Gas and Electric (SDG&E), Critical Peak Pricing (CPP). 2013. (Available from: http://www.sdge.com/save-money/demand-response/cpp). Accessed on 02/14/2013.
34. Energy Insights. Considerations for program design and the role of enabling technologies. (Available from: http://www.aeic.org/load_research/docs/12_Time-of-Use_and_Critical_Peak_Pricing.pdf). Accessed on 02/14/2013.
35. Ghatikar G, Mathieu J, Piette MA, Koch E, Hennage D. Open automated demand response dynamic pricing technologies and demonstration. Lawrence Berkeley National Laboratory: Berkeley, CA, USA, 2010.
36. San Diego Gas and Electric (SDG&E). Schedule EECC-CPP-D. 2013. (Available from: http://regarchive.sdge.com/tm2/pdf/ELEC_ELEC-SCHEDS_EECC-CPP-D.pdf). Accessed on 02/14/2013.
37. Bussieck MR, Pruessner A. Mixed-integer nonlinear programming. SIAG/OPT Newsletter: Views & News, 14, 2003.
38. General Algebraic Modeling System. GAMS. (Available from: http://www.gams.com). Accessed on 02/14/2013.
39. LINDO Global Solver. (Available from: http://www.gams.com/solvers/solvers.htm#LINDOGLOBAL). Accessed on 02/14/2013.