Applying Genetic Algorithms to Optimize Energy Efficiency in Buildings

Multicriteria Decision Aid and Artificial Intelligence

Volumn , Issue , 2013, Pages 309-333

  Diakaki, Christina ^a   Grigoroudis, Evangelos ^a  

^a TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

Buildings; Decision making; Energy efficiency; Genetic algorithms (GA); Multiobjective optimization

Indexed keywords

EID: 84886666084     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781118522516.ch13     Document Type: Chapter

References (41)

1. Berben JJL, Vis I, Witchen K and Grau K (2004) EPA-ED Formulas: Calculation Scheme. Report no. 040538jo of Energy Performance Assessment Method for Existing Dwellings Project, EC Contract: 4.1030/Z/01-142/2001.
2. Caldas L (2008) Generation of energy-efficient architecture solutions applying GENE_ARCH: An evolution-based generative design system. Advanced Engineering Informatics 22, 59-70.
3. Caldas LG and Norford LK (2002) A design optimization tool based on a genetic algorithm. Automation in Construction 11, 173-184.
4. Caldas LG and Norford LK (2003) Genetic algorithms for optimization of building envelopes and the design and control of HVAC systems. Journal of Solar Energy Engineering 125, 343-351.
5. Chantrelle FP, Lahmidi H, Keilholz W, El Mankibi M and Michel P (2011) Development of a multicriteria tool for optimizing the renovation of buildings. Applied Energy 88, 1386-1394.
6. Chen D and Gao J (2011) A multi-objective genetic algorithm approach for optimization of building energy performance. In Proceedings of the 2011 ASCE International Workshop on Computing in Civil Engineering, dx.doi.org/10.1061/41182(416)7.
7. Collette V and Siarry P (2004) Multiobjective Optimization. Springer, Berlin.
8. COMIS (2003) COMIS Multizone Air Flow Model. http://epb.lbl.gov/comis/users.html [accessed 12/31/2011].
9. Dasgupta D and McGregor DR (1993) sGA: A Structured Genetic Algorithm. Technical Report, IKBS-11-93, Department of Computer Science, University of Strathclyde.
10. Deb K (2000) An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering 186(2-4), 311-338.
11. Deb K (2001) Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Ltd, New York, NY.
12. Deb K (2005) Kanpur Genetic Algorithms Laboratory: NSGA-II Source Code. www.iitk.ac.in/kangal/codes.shtml [accessed 12/31/2011].
13. Deep K, Singh KP, Kansal ML and Mohan C (2009) A real coded genetic algorithm for solving integer and mixed integer optimization problems. Applied Mathematics and Computation 212(2), 505-518.
14. Diakaki C, Grigoroudis E, Kabelis N, Kolokotsa D, Kalaitzakis K and Stavrakakis G (2010) A multi-objective decision model for the improvement of energy efficiency in buildings. Energy 35, 5483-5496.
15. Diakaki C, Grigoroudis E and Kolokotsa D (2008) Towards a multi-objective optimization approach for improving energy efficiency in buildings. Energy and Buildings 40, 1747-1754.
16. Ehrgott M (2005) Multicriteria Optimization. Springer, Berlin.
17. Fonseca CM and Fleming PJ (1995) Multi-objective genetic algorithms made easy: Selection, sharing and mating restriction. Conference in Genetic Algorithms in Engineering Systems: Innovations and Applications. Conference Publication No. 414 IEE, pp. 12-14.
18. Fonseca CM and Fleming PJ (1998) Multiobjective optimization and multiple constraint handling with evolutionary algorithms-Part 1: A unified formulation. IEEE Transactions on Systems, Man and Cybernetics, Part A 28(1), 26-37.
19. Hamdy M, Hasan A and Siren K (2009) Combination of optimization algorithms for a multiobjective building design problem. In Proceedings of the 11th IBPSA (International Building Performance Simulation Association) Conference, Glasgow, UK, July 27-30, pp. 173-179.
20. Hamdy M, Hasan A and Siren K (2011). Applying a multi-objective optimization approach for design of low-emission cost-effective dwellings. Building and Environment 46, 109-123.
21. Integrated Environmental Solutions (2011) Virtual Environment (VE). http://iesve.com [accessed 12/31/2011].
22. International Energy Agency (2008) Worldwide Trends in Energy Use and Efficiency: Key Insights from IEA Indicator Analysis. OECD/IEA, Paris.
23. International Energy Agency (2010) Energy Technology Perspectives 2010: Scenarios & Strategies to 2050, Executive Summary. OECD/IEA, Paris.
24. Kolokotsa D, Diakaki C, Grigoroudis E, Stavrakakis G and Kalaitzakis K (2009) Decision support methodologies on the energy efficiency and energy management in buildings. Advances in Building Energy Research 3, 121-146.
25. Krarti M (2000) Energy Audit of Building Systems. CRC Press, Boca Raton, FL.
26. Kreider JF, Curtiss P and Rabl A (2002) Heating and Cooling for Buildings, Design for Efficiency. McGraw-Hill, New York, NY.
27. Krishnakumar K (1989) Micro-genetic algorithms for stationary and non-stationary function optimization. In Intelligent Control and Adaptive Systems (ed. Rodriguez G). SPIE, Philadelphia, PA, pp. 289-296.
28. Magnier L and Haghighat F (2010) Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network. Building and Environment 45, 739-746.
29. MathWorks (2011) Global Optimization Toolbox User's Guide. The MathWorks Inc., Natick, MA.
30. Pedersen CO, Liesen RJ, Strand RK, Fisher DE, Dong L and Ellis PG (2000) A Toolkit For Building Load Calculations. ASHRAE, Atlanta, GA.
31. Ren MJ and Wright JA (1998) A ventilated slab thermal storage system model. Building and Environment 33, 43-52.
32. Sahlin P, Eriksson L, Grozman P, Johnsson H, Shapovalov A and Vuolle M (2004) Wholebuilding simulation with symbolic DAE equations and general purpose solvers. Building and Environment 39, 949-958.
33. Simulation Research Group (1993) DOE-2 Supplement-Version 2.1E. Lawrence Berkeley National Laboratory, LBL-34946.
34. TRNSYS (2005) Transient Systems Simulation Program. Solar Energy Laboratory, University of Wisconsin, Madison. http://sel.me.wisc.edu/trnsys [accessed 12/31/2011].
35. Verbeeck G and Hens H (2007) Life cycle optimization of extremely low energy dwellings. Journal of Building Physics 31(2), 143-177.
36. Wang W, Zmeureanu R and Rivard H (2005) Applying multi-objective genetic algorithms in green building design optimization. Building and Environment 40, 1512-1525.
37. World Business Council for Sustainable Development (2009) Energy Efficiency in Buildings: Transforming the Markets. WBCSD, Geneva.
38. Wright JA and Farmani R (2001a) Genetic algorithms: a fitness formulation for constrained minimization. In Proceedings of the Genetic Algorithm and Evolutionary Computation Conference (GECCO-01), San Francisco, USA, July, pp. 725-732.
39. Wright JA and Farmani R (2001b) The simultaneous optimization of building fabric construction, HVAC system size, and the plant control strategy. In Proceedings of the 7th IBPSA (International Building Performance Simulation Association) Conference, Rio de Janeiro, Brazil, August 13-15, pp. 865-872.
40. Wright JA, Loosemore HA and Farmani R (2002) Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and Buildings 34, 959-972.
41. Wulfinghoff DR (1999) Energy Efficiency Manual. Energy Institute Press, Wheaton, MD.