Simulation-based optimization for energy and buildings

Ala Hasan; Matti Palonen; Mohamed Hamdy

doi:10.1007/978-3-319-17777-9_45

Simulation-based optimization for energy and buildings

Ala Hasan, Matti Palonen, Mohamed Hamdy

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

5 Citations (Scopus)

Abstract

This paper 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 fulfilment 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.

Original language	English
Title of host publication	Renewable Energy in the Service of Mankind
Subtitle of host publication	Selected Topics from the World Renewable Energy Congress WREC 2014
Publisher	Springer
Pages	503-513
Volume	1
ISBN (Print)	978-3-319-17776-2, 978-3-319-17777-9
DOIs	https://doi.org/10.1007/978-3-319-17777-9_45
Publication status	Published - 2015
MoE publication type	A4 Article in a conference publication
Event	World Renewable Energy Congress XIII, WREC 2014 - London, United Kingdom Duration: 3 Aug 2014 → 8 Aug 2014

Conference

Conference	World Renewable Energy Congress XIII, WREC 2014
Abbreviated title	WREC 2014
Country/Territory	United Kingdom
City	London
Period	3/08/14 → 8/08/14

Keywords

building performance simulation
optimization
MOBO software
zero-energy buildings

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-17777-9_45

Cite this

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title = "Simulation-based optimization for energy and buildings",

abstract = "This paper 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{\textregistered} 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 fulfilment 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.",

keywords = "building performance simulation, optimization, MOBO software, zero-energy buildings",

author = "Ala Hasan and Matti Palonen and Mohamed Hamdy",

note = "Project code: 82593; World Renewable Energy Congress XIII, WREC 2014, WREC 2014 ; Conference date: 03-08-2014 Through 08-08-2014",

year = "2015",

doi = "10.1007/978-3-319-17777-9_45",

language = "English",

isbn = "978-3-319-17776-2",

volume = "1",

pages = "503--513",

booktitle = "Renewable Energy in the Service of Mankind",

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}

Simulation-based optimization for energy and buildings. / Hasan, Ala; Palonen, Matti; Hamdy, Mohamed.
Renewable Energy in the Service of Mankind: Selected Topics from the World Renewable Energy Congress WREC 2014. Vol. 1 Springer, 2015. p. 503-513.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Simulation-based optimization for energy and buildings

AU - Hasan, Ala

AU - Palonen, Matti

AU - Hamdy, Mohamed

N1 - Project code: 82593

PY - 2015

Y1 - 2015

N2 - This paper 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 fulfilment 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.

AB - This paper 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 fulfilment 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.

KW - building performance simulation

KW - optimization

KW - MOBO software

KW - zero-energy buildings

U2 - 10.1007/978-3-319-17777-9_45

DO - 10.1007/978-3-319-17777-9_45

M3 - Conference article in proceedings

SN - 978-3-319-17776-2

SN - 978-3-319-17777-9

VL - 1

SP - 503

EP - 513

BT - Renewable Energy in the Service of Mankind

PB - Springer

T2 - World Renewable Energy Congress XIII, WREC 2014

Y2 - 3 August 2014 through 8 August 2014

ER -

Simulation-based optimization for energy and buildings

Abstract

Conference

Keywords

UN SDGs

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Cite this