Sónia Cunha
IN+, Instituto Superior Técnico, Universidade de Lisboa
Sónia Cunha is a researcher at IN+, Center for Innovation, Technology and Policy Research at Instituto superior Técnico (IST), in Lisbon, Portugal. She has a Master in Mechanical Engineering also from IST. Her Master Thesis focused on the study of Building energy simulation modelling under different scenarios of known data. Sónia is currently a PhD candidate of the sustainable energy Systems of the MIT Portugal Programme. She is currently part of the research at IST that is contributing for the EU funded Sharing Cities project. Her current work focuses on building energy simulation, urban models for energy consumption, energy generation, building retrofit potential and natural resources consumption.
Energy consumption and greenhouse gas emissions continue to increase, and so do concerns regarding climate change and energy security. Increasing energy efficiency is viewed as way to counteract these trends, particularly in... [ view full abstract ]
Energy consumption and greenhouse gas emissions continue to increase, and so do concerns regarding climate change and energy security. Increasing energy efficiency is viewed as way to counteract these trends, particularly in buildings which account for around a third of the total final energy consumption in the world and present great savings potential. In the European Union, for example, around two thirds of the buildings have been built before there were any energy performance standards, presenting great opportunities for retrofitting implementation. However, the renovation rate is very low, only around 1%.
Building renovation faces several barriers, one of them being the lack of information regarding what is the most suitable energy efficiency measure and what are the expected energy savings. As goals and regulations are set for new buildings to increase building energy efficiency, the same should be done for building renovation including initiatives to help building owners surpass these challenges.
As the share of population living in urban areas continues to increase, it becomes increasingly more important to understand and study the complexity of the building stock at an urban scale. Considering a larger scale provides a more holistic analysis to building renovation, enabling the identification of the most relevant energy efficiency measures in each urban area. However, this poses a set of new methodological challenges.
The main goal of the work being developed is to evaluate the potential for energy savings in existing buildings at urban scale, proposing the best solution considering energy savings and implementation cost. The work is applied to a case study area in Lisbon with 2 137 residential buildings and a total residential built area of 2 274 355 m2. The energetic performance of buildings is evaluated through the calculation of the baseline energy needs for heating and cooling for each residential building according to the Portuguese regulation. The impact of different retrofit measures were analysed by comparing the baseline with values for retrofitted scenarios.
The results show that the thermal needs of the building stock could decrease 13% if 63% of the buildings were renovated. The average decrease in thermal needs was 15%, being the maximum 57%. Of the total buildings in the area, 18% should improve their walls, 19% should improve the roof and 26% should replace the windows. None of the multi-family buildings constructed after 1990 require any sort of retrofitting intervention. These results are being associated with a cost analysis so that complementarity between retrofit measures may be considered to determine an optimal solution for each building.
This methodology can be used to estimate the savings potential for different retrofit strategies. The results may be combined with socio-economic data to design better renovation policies that are more include and targeted towards vulnerable population. Furthermore, it may also enable building owners to surpass renovation barriers related to lack of information.
• Resilience and planning , • Decision support methods and tools , • Sustainable urban systems
