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Xtreme : Application to the optimization of a residential house

RESIDENTIAL HOUSE COST AND ENERGY OPTIMIZATION USING MULTI OBJECTIVES PARETO FRONT METHOD

Summary

This article presents the multi-objective optimization of a residential house. The goal is to find the optimal Pareto front which minimizes both the heating energy needs and the construction cost. A real residential house to be constructed has been used as a use case. 2 simulations software have been used to compute the energy demands of the house: the PHPP and the TRNSYS software. In this paper, the results obtained with the PHPP software are presented. The cost evaluation function was developed in this project and the optimization was performed using XTREME, a commercial optimization software.

SYMBOLS

PHPP                Passive House Planning Package (http://passive.de)

TRNSYS            Transient System Simulation Tool (http://www.trnsys.com)

XTREME             Numerical Optimization Software (http://www.optimalcomputing.be)

U                       Thermal conductance (W/m2K)

g or SHGC          Solar Heat Gain Coefficient (%)


 INTRODUCTION

Reducing the C02 production around the world and in all sectors is now recognized as a mandatory objectives in the near future. Among the biggest consumer sector is the householders sector, which in Europe represents around 24.8% of the energy use [1].

Therefore, since several years the construction of low energy or even passive building attracts a lot of interest from many stakeholders: private person to construct their personal house, public authorities, European commission

Energy consumption targets have been set for the passive house but the extra cost required to reach this passive standard is often a barrier for individual persons. It is difficult to evaluate precisely the return on investment period for such a passive building.

This paper has 3 objectives:

1.     Demonstrate how numerical optimization techniques in general and Pareto Front optimization in particular can be used to find the set of best solutions for typical houses depending on their energetic performance.

2.     Deduce from this Pareto front, the return on investment time of a standard residual house in terms of energy demands and construction cost.

3.     Deduce important best practices depending on the target heat consumption (standard house, low energy house, passive house, )

The outcome of this study will be to demonstrate that the return on investment time for several energy targets can be evaluate using Pareto front optimization techniques.

This paper first presents the house used has a base line in this study. Then, the next 2 sections present the software used to simulate the energy performance and the cost function developed to calculate the construction cost. The fourth section present the optimization software used as well as how it was coupled to the simulation software. Finally, the optimization results are presented and analysed.

Pareto Front in the space Energy Demand - Cost difference

Final Residential House

Download the full paper here