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Modeling zero energy buildings : technical and economical optimization

Maria Ferrara

Modeling zero energy buildings : technical and economical optimization.

Rel. Marco Filippi, Enrico Fabrizio, Francesco Causone, Joseph Virgone. Politecnico di Torino, Corso di laurea magistrale in Architettura Costruzione Città, 2013


This thesis was born in the context of new challenges imposed by the recast of Energy Performance of Buildings Directive, concerning nearly Zero Energy Buildings and cost optimal level research. The aim of the work is to provide useful method and tools that could support technical and cost optimal level research, providing an easy and fast way to explore various place-based building configuration with a huge number of simulations, as requested by European Standard and guidelines. The work has been supported by the Région Rhône Alpes COOPERA-2012 project “Modélisation des bâtiments zéro-énergie : optimisation technico-économique”, whose partners are the university laboratory CETHIL-Centre Thermique de Lyon, the Energy Department of Politecnico di Torino, the enterprise “Maison et residence CORBIOLI" of Rhone-Alpes Region, the competent office “Echo Energies Solutions” of Lyon. The main part of the working activity has been carried out at the CETHIL laboratory, in Lyon.

The first part of the work consists in a deep study of the regulatory framework composed by Directives, Standards and guidelines at the European level, and regulations and labels at the French national level. Then the attention moved to computer tools, the use of which is able to help designers and researchers to deal with the new challenges. In particular, among the building simulation software, the use of TRNSYS -Transient System Simulation Tool- has been explored. With regard to the optimization theme, the genetic algorithms methodologies for optimization have been studied within the software GenOpt - Generic Optimization program. Then, possibilities for coupling of the software have been researched through a bibliographic study on previous works and experiences described in some scientific papers and through a personal research activity.

The second part of the thesis concentrates on a case-study. The so-called “Corbioli House” is a high-performance single-family house situated in the Rhone Alpes region of France. The house was built as an exhibition pavilion of nZEB and was monitored with several temperature sensors and a weather station. In teamwork with other French students, the building and its complex energy system (composed by a reversible air/air heat pump, a mechanical ventilation system and a geothermal pre-heating system) have been modelled using TRNSYS. Then theresults of the model, in terms of indoor temperatures and energy consumptions, have been compared to the real data obtained from the monitoring system, so that the model has been calibrated and validated.

The so-adjusted model was then used to carry out the main part of the work, concerning optimization. With regard to technical optimization, some elements of the building envelope have been chosen and set as parameters, such as the insulation thickness, the window type and dimension, the solar protection dimension, the inertial mass. Using GenOpt a parametric study has been performed, in order to evaluate the impact of variation of each parameter on heating, cooling and total energy needs of the house (without taking into account the energy system efficiency), starting from four different initial performance scenarios. The same parametric study has been done on two other building prototypes, similar to the first one except for the envelope. Finally the obtained results (concerning the massive internal insulated envelope, the massive external insulated envelope and the light wooden envelope) have been compared.

As a further step, a cost function based on French market prices has been created for each parameter of each envelope system. Besides the heat pump, three energy systems (a gas condensation boiler, a wood boiler and an all-electrical radiator system) have been created in TRNSYS, together with its cost function. Finally, the three envelope systems with related parameters have been combined with the four energy systems and, with the help of GenOpt optimization algorithm, twelve cost-optimal curves (based on the Global Cost Method) have been obtained and compared, evaluating strength and weaknesses of each building configuration.

Relators: Marco Filippi, Enrico Fabrizio, Francesco Causone, Joseph Virgone
Publication type: Printed
Subjects: A Architettura > AD Green architecture
Corso di laurea: Corso di laurea magistrale in Architettura Costruzione Città
Classe di laurea: UNSPECIFIED
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/3436


Abstract (English)



List of figures

1 Introduction: COOPERA Project

1.1 Context

1.2 Objectives and actors

2 Regulatory framework

2.1 ZEB and Cost Optimality in European Directives

2.1.1 EPBD

2.1.2 EPBD recast

2.1.3 Cost optimal methodology

2.2 French regulation towards nZEB

2.2.1 French RT 2012

2.2.2 Evolution of labels

2.2.3 Experiences and future developements in France

3 Simulation and optimization tools

3.1 Building simulation software

3.1.1 The used tool: TRNSYS

3.2 Optimization software

3.2.1 The used tool: GenOpt

3.2.2 Setting a complex optimization problem

3.3 Using TRNSYS with GenOpt

3.3.1 Template files

3.3.2 Project files

4 The Maison Corbioli as a case study: description

4.1 Elements for a bioclimatic conception

4.1.1 The shape

4.1.2 Insulation

4.1.3 Passive energy gains

4.1.4 Inertia wall

4.1.5 Airtighness

4.2 Energy systems

4.2.1 T-ZEN system

4.2.2 Puits canadien

4.2.3 Photovoltaic panels

5 The Corbioli House as a case study: monitoring and model

5.1 Monitoring

5.1.1 Instrumentation

5.1.2 Occupancy simulation

5.1.3 Results

5.2 TRNSYS model

5.2.1 Boundary conditions model

5.2.2 Building model

5.2.3 Energy system model

5.2.4 Canadian well model

5.3 Comparison between results from monitoring and simulation

6 Technical evaluation and optimization

6.1 Corbioli House 1.0: massive structure with internal insulation

6.1.1 Parameters

6.1.2 Results of parametric study

6.1.3 Corbioli House 1.0.1, 1.0.2, 1.0.3: modifying the initial configuration ..

6.1.4 Optimal configuration of Corbioli House 1.0

6.2 Corbioli House 2.0: massive structure with external insulation

6.2.1 Parameters

6.2.2 Optimal configuration of Corbioli House 2.0

6.3 Corbioli House 3.0: light wooden structure

6.3.1 Parameters

6.3.2 Optimal configuration of Corbioli House 3.0

6.4 Evaluation and comparison of envelope systems

7 Financial optimization

7.1 Building construction cost functions

7.1.1 Opaque envelope of Corbioli House 1

7.1.2 Opaque envelope of Corbioli House 2

7.1.3 Opaque envelope of Corbioli House 3

7.1.4 Transparent envelope: window types

7.1.5 Other building elements related to set parameters

7.2 Energy systems models and costs

7.2.1 Energy system 1: reversible heat pump and mechanical ventilation

7.2.2 Energy system 2: traditional all-electrical system

7.2.3 Energy system 3: condensing boiler and air-conditioning fans

7.2.4 Energy system 4: wood-pellet boiler and air-conditioning fans

7.3 Results of economical optimizations

7.3.1 Corbioli Houses 1.1, 2.1, 3.1

7.3.2 Corbioli Houses 1.2, 2.2, 3.2

7.3.3 Optimization of envelope with energy system 2

7.3.4 Corbioli Houses 1.3, 2.3, 3.3

7.3.5 Optimization of envelope system with energy system 3

7.3.6 Corbioli Houses 1.4, 2.4, 3.4 201

7.3.7 Optimization of envelope system with energy system 4

7.3.8 General optimization of envelope 1 201

7.3.9 General optimization of envelope 2 201

7.3.10 General optimization of envelope 3 201

8 Conclusions and future developments 209



ClimaMED paper


[ 1] Ehsan Asadi, Manuel Gameiro da Silva, Carlos Henggeler Antunes, and Luis Dias. Multi¬objective optimization model for building retrofit strategies. CLIMA Conference, 2013.

[2] Bodgan Atanasiu and Ilektra Koulompi. Implementing the cost-optimal methodology in eu countries. REHVA Journal, pages 16-28, May 2013.

[3] Cristina Becchio, Enrico Fabrizio, Valentina Monetti, and Marco Filippi. Cost optimal levels of energy requirements for nearly-zeb: application to an italian reference building for existing offices. CLIMA conference, 2013.

[4] Buildings Performance Institute of Europe BPIE. Cost optimality, discussing methodology and challenges within the recast of energy performance of building directive. 2010.

[5] Buildings Performance Institute of Europe BPIE. Principles for nearly zero energy building - paving the way for effective implementation of policy requirements. 2011.

[6] Scott Bucking, Andreas Athienitis, and Radu Zmeureanu. An optimization methodology to evaluate the effect size of incentives on energy-cost optimal curve. Building Simulation Conference, 2013.

[7] Briefing CIBSE. The recast energy performance of building directive. 2011.

[8] European Commission and Energy Directorate General. Guidelines accompanying commission delegated regulation (eu) no 244/2012 of 16 january 2012 supplementing directive 2010/31/eu of the european parliament and of the council on the energy performance of buildings by establishing a comparative methodology framework for calculating cost optimal levels of minimum energy performance requirements for buildings and building elements. 2012.

[9] EU Concerted Actions. Implementing the energy performance of building directive epbd 2010. Featuring country report 2010.

[10] Eloise Couvert and lerome Savoyat. Notice d’utilization du logiciel trnsys. 2011.

[11] Drury B. Crawley, Jon W. Hand, Michael Kummert, and Brent T. Griffith. Contrasting the capabilities of building energy performance simulation programs. 2005.

[12] Dossier de presse. Publication rapport 2011 - bbc (2012), 2013.

[13] Ministère de l’ecologie de l’energie du développement durable et de la mer. Arrete du 26 octobre 2010 relatif aux caractéristiques thermiques et aux exigences de performance energetique des bâtiments nouveaux et des parties nouvelles de bâtiments, (RT 2012).

[14] Ecofys. Sectoral emission reduction potentials and economic costs for climate change (serpec-cc) summary report. 2009.

[15] Enrico Fabrizio. Modelling of multi-energy systems in buildings. PhD thesis, Politecnico di Torino - INSA Lyon, 2008.

[16] Enrico Fabrizio and Marco Filippi. Introduzione alia simulazione energetica dinamica degli edifici. Ed. Delfino, 2011.

[17] Maria Ferrara, Joseph Virgone, Enrico Fabrizio, Kuznik Frederik, and Marco Filippi. Mod¬elling zero energy building: technical and economcal optimization. ClimaMED Conference, 2013.

[18] European Committee for Standardization. Standard en 15459:2007 - economic evaluation procedure for energy systems in buildings.

[19] Conference invitee de Gerard Krauss. La maison du futur. In Salon ECOBAT, 17 - 20 Mars 2007, Paris.

[20] Fraunhofer ISI and partners. Study on the energy savings potentials in eu member states, candidate countries and eea countries, final report for the european commission directorate-general energy and transport. 2009.

[21] J. Kennedy and R. C. Eberhart. A discrete binary version of the particle warm algorithm. Procedures of Systems, Man, and Cybernetics, 5:4104-4018,1997.

[22] S. Klein. TRNSYS. A transient system program. Engineering Experiment Station, Report 38- 13. Solar Energy Laboratory, University of Wisconsin - Madison Solar Energy LAboratory, Madison, 2000.

[23] G. Krauss, B. Lips, J. Virgone, and E. Blanco. Modélisation sous trnsys d’une maison a energie positive. Congres IBPSA France, La Reunion, 2-3 novembre 2006.

[24] Michael Kümmert. Using genopt with trnsys 16 and type 56. 2007.

[25] J. Kurnitski. How to calculate cost optimal nzeb energy performance ? REHVA Journal, pages 36-41, October 2011.

[26] Tomas Persson, Frank Fiedler, and Svante Nordländer. Methodology for identifying parameters for the trnsys model type 210 - wood pellet stoves and boilers. 2012.

[27] EPBD recast. Directive 2010/31/eu of the european parliament and of council of 19 may 2010 on the energy performance of buildings. Official Journal of the European Union, 2010.

[28] Jeremy Rifkin. The Third Industrial Revolution. How Lateral Power is Transforming Energy, the Economy, and the World. 2011.

[29] Brian Simmons, Matthias H. Y. Tan, C. F. Jeff Wu, Youngdong Yu, and Godfried Augen- broe. Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target. Building Simulation conference, 2013.

[30] Solar Energy Laboratory, TRANSSOLAR, Centre Scientifique et Technique du Bâtiment, Thermal Energy System Specialists. TRNSYS 16 documentation, 2007.

[31] Michael Wetter and Simulation Research Group. GenOpt - Generic Optimization Program, User Manual, Version 2.1.0. Lawrence Berkeley National Laboratory, June 2008.

[32] www.mathworks.it Global Optimization Toolbox. How the genetic algorithm works.

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