Evolutionary tuning of building models to monthly electrical consumption

ASHRAE Transactions

Volumn 119, Issue PART 2, 2013, Pages 89-99

  Garrett, Aaron ^a   New, Joshua ^b   Chandler, Theodore ^a  

^a JACKSONVILLE STATE UNIVERSITY   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; ELECTRIC POWER UTILIZATION; ENERGY UTILIZATION; FINANCIAL MARKETS;

AUTOMATIC CALIBRATION; BUILDING ENERGY MODEL; COMMODITY HARDWARE; ELECTRICAL CONSUMPTION; ENERGY SIMULATION; EVOLUTIONARY TUNING; NOVEL METHODOLOGY; SUM OF ABSOLUTE ERRORS;

AUTOMATION;

EID: 84893363854     PISSN: 00012505     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (35)

1. ASHRAE. 2002. ASHRAE Guideline 14, Measurement of Energy and Demand Savings. Atlanta: ASHRAE.
2. ASHRAE. 2013. ASHRAE Handbook - Fundamentals, Chapter 26, "Heat, Air, and Moisture Control in Building Assemblies - Material Properties." Atlanta: ASHRAE.
3. Back, T., F. Hoffmeister, and H.-R Schwefel. 1991. A survey of evolution strategies. In R. K. Belew and L. B. Booker, editors, Proceedings of the 4th International Conference on Genetic Algorithms, pp. 2-9.
4. Back, T., U. Hammel, and H.-P. Schwefel. 1997. Evolutionary computation: Comments on the history and current state. IEEE Transactions on Evolutionary Computation 1(1):3-17. (Pubitemid 127771014)
5. Biswas, K., A. Gehl, R. Jackson, P. Boudreaux, and J. Christian. 2012. Comparison of Two High-Performance Energy Efficient Homes: Annual Performance Report, December 1, 2010-November 30, 2011. Oak Ridge National Laboratory report ORNL/TM-2011/539. http://info.ornl.gov/sites/publications/files.Pub34163.pdf
6. Briggs, R.S., R.G. Lucas, and Z.T. Taylor. 2003. Climate classification for building energy codes and standards: Part 1 - Development process and Part 2 - Zone definitions, maps, and comparisons. ASHRAE Transactions 109(1):109-30.
7. DeJong, K.A., and W. Spears. 1993. On the state of evolutionary computation. In Stephanie Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, San Mateo, CA, pp. 618-623.
8. DeJong, K. A. 2006. Evolutionary Computation: A Unified Approach. Cambridge, MA: MIT Press.
9. Deru, M., K. Field, D. Studer, K. Benne, B. Griffith, P. Torcellini, B. Liu, M. Halverson, D. Winiarski, and M. Rosenberg. 2011. U.S. Department of Energy commercial reference building models of the national building stock. Technical Report NREL/TP-5500-46861, National Renewable Energy Laboratory, U.S. Department of Energy, Washington, D.C.
10. DOE. 2008. Energy efficiency trends in residential and commercial buildings, Figure 18, U.S. Department of Energy, Washington, D.C. http://appsl.eere.energy.gov/buildings/publications/pdfs/corporate/ bt-stateindustry.pdf.
11. DOE. 2011. Buildings Energy Data Book. U.S. Department of Energy, Washington, D.C. http://buildingsdata-book.eren.doe.gov.
12. DOE. 2012a. Buildings Energy Data Book. Average annual energy expenditures per household, by year ($2010). U.S. Department of Energy, Washington, D.C. http://buildingsdatabook.eren.doe.gov/docs/xls-pdf/2.3.9.pdf.
13. DOE. 2012b. Buildings Energy Data Book. Residential sector energy consumption, Table 2.1.5. U.S. Department of Energy, Washington, D.C. http://buildingsdatabook.eren.doe.gov/TableView.aspx?table=2.1.5.
14. DOE. 2012c. Buildings Energy Data Book. 2010 residential energy end-use expenditure splits by fuel type ($2010 billion), Table 2.3.5. U.S. Department of Energy, Washington, D.C. http://buildingsdatabook.eren.doe.gov/ TableView.aspx?table=2.3.5.
15. DOE. 2012d. Building energy software tools directory. Department of energy tools 2012. U.S. Department of Energy, Washington, D.C. http://appsl.eere.energy.gov/buildings/tools-directory/subjects-sub.cfm.
16. DOE. 2012e. Getting started with EnergyPlus: Basic concepts manual. U.S. Department of Energy, Washington, D.C. http://energyplus.gov.
17. DOE. 2012f. OpenStudio: Commercial buildings research and software development. National Renewable Energy Laboratory, U.S. Department of Energy, Washington, D.C. http://openstudio.nrel.gov.
18. Earth Advantage Institute. 2009. Energy performance score 2008 pilot: Findings and recommendations report. Report prepared for EnergyTrust of Oregon. Earth Advantage Institute, Portland, OR and Conservation Services Group, Westborough, MA.
19. FIA. 2012. Frequently asked questions, http://www.eia.gov/tools/faqs/faq. cfm?id=97&t=3. U.S. Energy Information Administration, Washington, D.C.
20. Eiben, A.E. and J.E. Smith. 2007. Introduction to Evolutionary Computing. New York: Springer.
21. Fogel, D.B. 1994. An introduction to simulated evolutionary optimization. IEEE Transactions on Neural Networks 5(1):3-14.
22. Fogel, D.B. 2000. What is evolutionary computation? IEEE Spectrum 37(2):26-32.
23. Fogel, L.J., A.J. Owens, and M.J. Walsh. 1966. Artificial Intelligence through Simulated Evolution. New York: Wiley.
24. Forrest, S. 1993. Genetic algorithms: Principles of natural selection applied to computation. Science 60:872-78. (Pubitemid 23275801)
25. Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley.
26. Holland, J.H. 1975. Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press.
27. ICC/ASHRAE. 2009. 2009 International Energy Conservation Code and ANSI/ASHRAE/IESNA Standard 90.1-2007 Energy Standard for Buildings Except Low-Rise Residential Buildings. Washington, D.C: International Code Council and Atlanta: ASHRAE.
28. Michalewicz, Z., and D.B. Fogel. 2004. How to Solve It: Modern Heuristics. New York: Springer.
29. New, J.R., J. Sanyal, M. Bhandari, and S. Shrestha. 2012. Autotune E+ building energy models. Proceedings of the 5th National SimBuild of IBPSA-USA, Aug. 1-3. http://www.ibpsa.us/simbuild2012/Papers/SB12-TS05a-1-New.pdf.
30. Reddy, T.A., I. Maor, S. Jian, and C. Panjapomporn. 2006. Procedures for reconciling computer-calculated results with measured energy data. ASHRAE Research Project RP-1051, ASHRAE, Atlanta, GA.
31. Roberts, D., N. Merket, B. Polly, M. Heahey, S. Casey, and J. Robertson. 2012. Assessment of the U.S. Department of Energy Scoring Tool. National Renewable Energy Laboratory, Washington, D.C.
32. Russell, S., and P. Norvig. 2002. Artificial Intelligence: A Modern Approach. Prentice Hall, 2nd edition.
33. Spears, W.M., K.A. DeJong, T. Bäck. D.B. Fogel, and H. deGaris. 1993. An overview of evolutionary computation. In Proceedings of the 1993 European Conference on Machine Learning.
34. Vose, M.D. 1999. The Simple Genetic Algorithm: Foundations and Theory. Cambridge, MA: MIT Press.
35. ZEBRAlliance. 2012. An alliance maximizing cost-effective energy efficiency in buildings. ZEBRAlliance, Oak Ridge, TN. http://www.zebralliance. org.