Abstract
This chapter presents implementations of simulation-based optimization by giving two examples for finding optimum values of design/decision parameters in the building envelope, building heating/cooling systems, and energy systems. In addition, the features of the multi-objective building performance optimization program (MOBO®) are presented. MOBO is a new generic freeware able to handle single- and multi-objective optimization problems including continuous and/or discrete variables. It can be coupled to many simulation programs and has a library of different types of algorithms (evolutionary, deterministic, hybrid, exhaustive, and random).
It is concluded that simulation-based optimization is an efficient method for finding optimum values of design/decision variables in the building envelope, heating/cooling systems, and energy generation systems. While an exhaustive search method will need a huge number of simulations to find optimal solutions, the optimization algorithm will need reasonable time and number of simulations to find comparable solutions. It can be used in finding optimal solutions for the fulfillment of zero, net- or nearly-zero energy/emission buildings, where minimization of energy emissions and cost and maximization of indoor air quality are the targets.
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Acknowledgements are due to the Academy of Finland for funding this work.
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© 2015 Springer International Publishing Switzerland
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Hasan, A., Palonen, M., Hamdy, M. (2015). Simulation-Based Optimization for Energy and Buildings. In: Sayigh, A. (eds) Renewable Energy in the Service of Mankind Vol I. Springer, Cham. https://doi.org/10.1007/978-3-319-17777-9_45
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DOI: https://doi.org/10.1007/978-3-319-17777-9_45
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