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Integration of phasing on multi-objective optimization of building stock energy retrofit
Highlights Optimal retrofit plans for building stocks are generated using genetic algorithm. The phasing of retrofit actions is integrated in the optimisation search space. Results show that proposed optimal strategies are different when phasing is integrated.
Abstract Decision making for the energy retrofit of building stock is key to improve the energy efficiency and comfort in buildings. This article present a methodology developed in order to help the building stock or real estate manager to improve the efficiency of his buildings. The methodology is based on the multi-objective optimization of the retrofit, and specifically of the walls and windows of the buildings. The paper presents the integration of a temporal dimension with the phasing of the construction work in the retrofit strategies on multiple buildings in order to get closer to real world practice in the construction sites. The case study is carried out on a small building stock with the NSGA-II genetic algorithm. The search space of the optimization are vertical and horizontal walls and windows of each building; objective functions are heating demand, price of the proposed retrofit and an overheating indicator based on adaptive comfort. Overheating and heating demand are evaluated using EnergyPlus simulations. Phasing is implemented directly into the optimization formalisation with a separated chromosome describing temporality. As a result, different retrofit strategies were obtained by integrating phasing than with a standard optimisation with no temporal planning of operations. The main difference lies into the which building is selected to be retrofitted first, and in the improved performance of each retrofit material proposed: it led to an increase of performance of 10% in the overheating while thermal performance decreased for 2% in the retrofit strategies possible in reality when including the phasing. These results highlight the importance of formulating the optimization problem as close as possible to the real world constraints in construction in order to have accurate retrofit strategies.
Integration of phasing on multi-objective optimization of building stock energy retrofit
Highlights Optimal retrofit plans for building stocks are generated using genetic algorithm. The phasing of retrofit actions is integrated in the optimisation search space. Results show that proposed optimal strategies are different when phasing is integrated.
Abstract Decision making for the energy retrofit of building stock is key to improve the energy efficiency and comfort in buildings. This article present a methodology developed in order to help the building stock or real estate manager to improve the efficiency of his buildings. The methodology is based on the multi-objective optimization of the retrofit, and specifically of the walls and windows of the buildings. The paper presents the integration of a temporal dimension with the phasing of the construction work in the retrofit strategies on multiple buildings in order to get closer to real world practice in the construction sites. The case study is carried out on a small building stock with the NSGA-II genetic algorithm. The search space of the optimization are vertical and horizontal walls and windows of each building; objective functions are heating demand, price of the proposed retrofit and an overheating indicator based on adaptive comfort. Overheating and heating demand are evaluated using EnergyPlus simulations. Phasing is implemented directly into the optimization formalisation with a separated chromosome describing temporality. As a result, different retrofit strategies were obtained by integrating phasing than with a standard optimisation with no temporal planning of operations. The main difference lies into the which building is selected to be retrofitted first, and in the improved performance of each retrofit material proposed: it led to an increase of performance of 10% in the overheating while thermal performance decreased for 2% in the retrofit strategies possible in reality when including the phasing. These results highlight the importance of formulating the optimization problem as close as possible to the real world constraints in construction in order to have accurate retrofit strategies.
Integration of phasing on multi-objective optimization of building stock energy retrofit
Merlet, Yannis (author) / Rouchier, Simon (author) / Jay, Arnaud (author) / Cellier, Nicolas (author) / Woloszyn, Monika (author)
Energy and Buildings ; 257
2021-12-08
Article (Journal)
Electronic Resource
English
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