Abstract

Selecting the most cost-effective retrofit interventions to achieve a significant reduction of energy use and CO2 emissions in the building sectors is challenging, because a large number of possible retrofitting options should be analyzed. To remedy this and simplify the decision-making process, optimization may be adopted. This study developed an iterative optimization process by coupling a dynamic energy simulation software, IDA-ICE, and a generic optimization engine, GenOpt, through the Graphical Script module. This optimization process was applied to an office building located in the Nordic climate. Two scenarios were considered. In the first scenario, the optimal designs were achieved by minimizing the life cycle cost of retrofitting measures over a span of 60 years, while the building energy use for space heating and cooling were the constraints to satisfy the Norwegian passive house standard level. In the second scenario, the delivered energy to the building was minimized and the life cycle cost of retrofitting was limited to a predefined value. Two different space heating systems were used, radiator space heating and all-air systems. The optimization parameters included building envelope elements and heating and cooling set points (in the case of all-air system). The results showed that the specific life cycle cost could be reduced up to 11%, while the energy use for the space heating and space cooling was met according to the Norwegian passive house standards. The delivered energy to the building could be decreased by up to 55% in the second scenario.

Highlights

  • Energy efficiency measures in building stock play a significant role in the reduction of total energy use

  • The results showed that the specific life cycle cost could be reduced up to 11%, while the energy use for the space heating and space cooling was met according to the Norwegian passive house standards

  • In other words, using the Graphical Script (GS) modules, the objective function was minimized at the two aforementioned levels since the cases that did not meet the constraints were multiplied by a large number, while acceptable results remained unchanged during the optimization process

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Summary

Introduction

Energy efficiency measures in building stock play a significant role in the reduction of total energy use. Among all users, existing non-residential buildings account for a large portion of energy use and greenhouse gas (GHG) emissions. In Norway, non-residential buildings form around 62% of the total building stock [1], emphasizing the essential need for improving the energy performance of this building type. The building energy efficiency is even more challenging due to cold climate conditions and high heating needs, which accounts for between 40% and 60% of the total energy use [2]. Building retrofitting is a viable solution in improving the existing building stock’s energy performance and IAQ

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