Computational analysis of energy and cost efficient retrofitting measures for the French house
Introduction
The Energy Performance of Buildings Directive (EPBD) recast in 2010 [1] and amendment in 2018 [2] demands that new buildings should be nearly zero-energy (NZEB) buildings by the end of 2020. The EPBD recast [1,2] also calls for the application of cost-efficient measures for both building envelope and technical systems (including heating systems). The NZEB definition was explained in that document as a very low amount of energy that should be covered to a very significant extent by energy from renewable sources. Example studies [[3], [4], [5], [6], [7]] discussed these terms at time it was introduced, investigated methods and presented computational analyses. For most if not all member states of the EU, the ambitious energy-efficiency target cannot be met through only measures for new buildings. The EPBD recast‒Article 2a [2] demands member states to establish long-term renovation strategy and stimulate cost-effective deep renovation to support the renovation of the national stock of buildings into a highly efficient and decarbonised building stock by 2050. The concept of ‘deep renovation’ was defined earlier as a percentage of reduction in current energy consumption by 60–90% [8] or precisely as 75% [9]. Member states started from the beginning to pass regulations in mandatory local standards (e.g. Refs. [[10], [11], [12]]), whilst other states further reinforced the Directive through additional schemes (e.g. Ref. [13]), policies and incentives (e.g. Ref. [14]) and most recently by issuing laws to commit to 2050 net-zero emissions [15]. In practice, such ambitious energy-efficiency and emissions reduction plans are nationally in the hands of main key stakeholders with different interests in the building sector. These include governmental organisations, financing entities, construction firms, systems and materials manufacturers, utility providers, and end-consumers or householders for domestic buildings. Pombo et al. [16] investigated energy and cost efficiency of domestic buildings renovation for 3 different scenarios over a case study of a Spanish multi-family block of flats. The scenarios included 3 simulation variants of typical Spanish renovations applied for existing building, Spanish regulations for new buildings, and the Passive house standard [17]. Similarly, Ekström et al. [18] investigated same 3 scenarios for reference Swedish houses to show cost-effective measures. Multi-objective optimization tools were introduced to find optimum renovation measures (energy and cost optimal) accounting for future weather [19], and dealing with historic buildings [20].
In France, the building sector consumes 43% of the country's whole sectorial energy consumption. The housing stock, consists of 36.3 million houses, and is responsible for 67% of the consumption of the building sector [21]. The French building stock increases annually by less than 1% [22], which makes the need for retrofitting existing buildings even more critical if this energy-efficiency target is to be achieved.
A few studies on the thermal performance of the French housing have been conducted to address the EPBD targets for building energy-efficiency, or performance of retrofit measures in general [[23], [24], [25], [26]]; and account for cost optimality [[27], [28], [29], [30]]. For example, Romani et al. [29] searched for optimal solutions using economic and environmental databases. Brangeon et al. [30] developed automated method using statistical and manufacturer databases to search for refurbishment solution of a collective housing building. However, market available retrofit solutions for single-family-houses were not investigated. Further, there is no investigation against financing options for householders to support the initial investment. This would have been useful to investigate possible energy and cost-efficiency solutions to help decision-making by householders.
This study aims to support decision-making for an archetype of a French single-family house, by conducting optimization focusing on applying: 1) popular marketed building fabric/system retrofit measures and 2) realistic mortgage financial calculations. The study assumes a financing scenario that householders are offered a loan to fully pay for recommended retrofit measures specific for their house. The basis for recommended retrofit measures is that the loan need to be paid off through energy bills' savings brought by these measures. These were the basis of the so-called Green Deal UK retrofit scheme [13], that sounded attractive when was introduced to the UK public. For this work, a parametric simulation tool has been developed to run the dynamic thermal modelling (DTM) software ‘EnergyPlus 7.20’ based on a 2D matrix of retrofit parameters. These simulations included 1536 variants of retrofits with 5 post-processing to account for the heating system's efficiency for each of the 4 climatic regions (a total of 30,720 variants). The post-processing of results, carried out within the simulation routine at each run, included calculations of the associated retrofit costs.
Section snippets
Simulation-based optimization
Simulation-based optimization is a technique used to assist decision-making in many different fields, by setting clearly the optimization problem; addressing the objectives and constraints; and then carrying out simulations to search for optimum solutions. In this study, an exhaustive-search with constraint-based filtering technique was used to find out the optimum combinations of retrofit measures from a set that is introduced for the French market by local and international trades. These
Parametric analysis
The parametric simulations (6140 simulations with 5 post-processing for the heating system's efficiency) were completed over 6 days on a personal laptop computer. Part of the simulations was repeated to analyse the results' sensitivity to the building orientation. This was done separately as the orientation was not considered as a retrofit measure. The FE + output report was then used to analyse the results. Fig. 4, Fig. 5, Fig. 6 show example parametric analysis of the results, while Table 4
Discussion
Building energy optimization studies usually include a large size and wide ranges of parameters (typically ranges of continuous variables) that do not mind standardised elements provided by the construction trades. This, therefore, results in a mix of solutions which may assist tradesmen for designing and offering energy-efficient measures. However, the un-standardised elements cannot directly (or via practitioners) allow householders to confidently decide on the proper set of measures for
Conclusions
This study presented a simple and practical optimization approach (exhaustive search with a filtering technique) that is focused on most popular retrofit measures (standardised) introduced for the French market. This included objectives of energy and cost efficiency subject to minimum limit of energy-saving, payback, and overheating risk constraints. The study aimed at supporting the decision-making process in selecting retrofit measures for the French housing stock, built before the year 1974.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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