Francesca Cappelletti

Multi-objective optimization for existing buildings retrofitting under government subsidization

The refurbishment of existing buildings allows remarkable improvements in energy performance, even by mature and off‐the‐shelf technologies. However, the pursuit of nearly zero energy buildings in renovation can lead to non-optimal solutions in terms of comfort. Besides, the initial cost can limit the owner in refurbishing buildings or drive the choice toward energy-efficiency measures with minimum initial cost at the expense of energy and non-energy performances. In this regard, financial incentives can be a key driver to stimulate renovation, mobilizing private investments and overcoming the high upfront costs and relatively long pay-back time of the retrofit. In the literature, the real effectiveness of incentives to improve both the comfort and the energy performance of the cost-optimal solutions has not been assessed in depth. This work investigates to which extent the incentives on different typologies of energy-efficiency measures can improve the performance of the optimal retrofits solutions. The analysis has been carried out on a set of different residential building modules, representative of different building typologies and Italian construction periods, located in two different climatic contexts representative of Italy, mixed-humid (Milano) and warm-marine (Messina) (ASHRAE 2007), optimizing the energy, costs, and indoor thermal comfort aspects.

Comfort and energy performance analysis of different glazing systems coupled with three shading control strategies

Shading control strategies are often required to optimize the balance between solar gains, daylight availability, glare protection, and view to the outside. Automated shading operation, when properly designed, may avoid performance losses due to manual operation while maintaining indoor environmental comfort. In this work, the integrated performance of different glazing systems coupled with three control approaches for roller shades is presented for a typical office space. The first control is a standard open–closed operation based on a workplane illuminance range, while the other two are able to set intermediate shade positions according to the solar position to maximize daylighting. The third control addresses excessive daylight on the workplane by imposing a workplane illuminance threshold to reduce the risk of daylight discomfort glare. Daysim, based on Radiance and the daylight coefficient method, was used to calculate the annual illuminance profile over the workplane, and Evalglare was used to calculate glare indexes. EnergyPlus was used for thermal comfort and energy analysis. The results were processed through a MATLAB code for transferring required information from one tool to another. Moreover, to assess the global performance of the shading controls and fenestration configurations studied, visual and thermal comfort were evaluated through a set of metrics able to express both the availability (the fraction of time with acceptable comfort conditions at specific positions) and the spatial usability (the fraction of space simultaneously within comfort range at specific moments). The energy performance was also quantified in terms of primary energy demand for heating, cooling, and lighting. The results showed that it is possible to balance daylighting, thermal and visual comfort, and energy use. This can be achieved by simultaneously selecting shading controls that allow adequate daylight without causing glare, and glazing properties with good thermal performance that allow adequate daylight (high visible transmittance) but limit solar gains (lower solar transmittance or solar heat gain coefficient [SHGC]) for moderate and cooling-dominated climates.

Challenges in the application of a WRF/Urban-TRNSYS model chain for estimating the cooling demand of buildings: A case study in Bolzano (Italy)

In the present study, a WRF/Urban-TRNSYS model chain is proposed to evaluate the cooling demand of buildings located in an urban area. A case study is proposed to show the applicability of the method for a hypothetical residential building located in the city of Bolzano (Italy) on a clear-sky hot day in summer. WRF/Urban results were first validated against measurements from permanent weather stations located both in the urban area and in the surrounding countryside. Then, several TRNSYS simulations were performed, in order to assess the impact of the gridded input from WRF/Urban against both measurements from a weather station located close to the sample building and to standard data from the Test Reference Year (TRY). Compared with estimates using input data from the weather station, the daily cooling demand of the sample building estimated by WRF/Urban-TRNSYS differed by only 6% to 8%, while differences of 60% were found when using standard TRY data. Moreover, results show that energy estimates obtained by means of WRF/Urban-TRNSYS model chain satisfy the standard requirement suggested by Ashrae Guidelines 14–2002, suggesting that this model chain is a useful tool for the estimation of real buildings energy consumption.

Development of algorithms for building retrofit

Abstract Designing buildings retrofit is not an easy task because a wide selection of energy-efficiency measures are technically available on the market, each of which can be applied to a different extent. In a range of different levels, from policy makers to energy service companies, owners, or conductors, there is a need to find the way to plan interventions, depending on the economic resources available and on some additional performance requisites, such as comfort levels, environmental impact, and so on. This means that some guidance is necessary to decide which would be the most effective combination of retrofit solutions among different packages. In other words, the final goal of a retrofit design is typically the optimization of a set of different aspects, not only the minimization of energy needs, with the consequent reduction of CO 2 emissions, but also the maximization of the economic efficiency, dealing with either subsidies or proper investments, depending on the specific perspective, the preservation or improvement of the indoor environmental quality, and ultimately the long term sustainability of the intervention. On the one hand, most of these goals have a competing nature and optimizing just one of them could compromise the achievement of the others. On the other hand, the analysis of all the possible alternatives of interventions requires the application of techniques able to investigate the entire size of the problem, without excluding some of the possibilities, and to find a trade-off among the objectives, at the same time. The research of the attainment of multiple objectives by means of the exploration of all the possible solutions can be solved applying some mathematical techniques known as multicriteria or multiobjective optimization analysis. In this chapter an overview of different methodologies to deal with multiobjective projects and methods to assist and to define the retrofit interventions is described. The techniques are there, but only research institutions really have demonstrated the capability to implement them. Theres not a lack of algorithms for building retrofit or management, but there is still a lack of dedicated software tools, specifically developed for guiding retrofit decisions and using the most promising algorithms, user-friendly enough to support the designer and decision-maker in defining the best alternatives to be considered. For larger applications, on the other hand, practitioners and energy service companies can find useful support in new entrepreneurship initiatives and start-ups focused on providing calculation and optimization services, with an in-depth knowledge of building physics, economics and finance, and fiscal aspects. High initial investments and entering barriers, both cultural and technical, are overcome thanks to an externalization strategy that can justify the settlement of new companies.