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The Spanish residential building stock built between 1940 and 1980 period presents a high energy saving potential as it represents a significant percentage of the total housing stock and it was built without any regulation regarding energy efficiency. Accordingly, the first aim of this paper was to quantify the energy saving potential and the related reduction in CO 2 emissions of the housing stock in those years. The work focuses on the Mediterranean climate of the Comunitat Valenciana Region, therefore the energy efficiency strategies proposed are passive and deal with the envelope of buildings. On the basis of the results obtained, several scenarios with intervention periods of 10, 20 and 30 years were calculated. The conclusion was that with the current rate of annual building renovation, it will be nearly impossible to reach the goals established by the EPBD. Only a deep transformation of the building fabric within this sector could help in achieving them. Finally, it should be noted that the proposed methodology can be applied to other areas with different climates, particularly in Spain. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a regression analysis of energy consumption in the banking sector. In our case study, the target area is the Spanish banking sector, for which we divide the available data into a prediction and a validation subset. Power models were developed using test data from 55 banks. From the analysis, three models were obtained; where the first proposed model can be used to predict the energy consumption of the whole banking sector, while the rest of the models estimate the energy consumption for branches with low winter climate severity (Model 2) and high winter climate severity (Model 3). Models 2 and 3 differ from the first model in that they need independent variables measured in situ. As a result, the uncertainty of the response variable in the function of the independent variables is reduced by 56.8% for the first model and by 65.2% and 68.5% for the second and third proposed models, respectively. The validation of the first model, which is the model with the lowest determination coefficient, shows that this model is appropriate for predicting the energy consumption of bank branches with good energy consumption performance and detecting inefficiencies in bank branches with poor energy consumption performance. [Copyright &y& Elsevier]

Abstract: Trigeneration systems, also known as Combined Heat, Cooling and Power (CHCP) systems, are interesting alternatives to supply different energy services in urban districts and in large buildings, particularly in warm areas such as Mediterranean countries. These systems can provide substantial benefits from economic, energetic, and environmental viewpoints, since the cogenerated heat can be used for heating in winter as well as cooling in summer with an absorption refrigerator. This paper develops an optimization model using Mixed Integer Linear Programming (MILP) to determine the type, number and capacity of equipment in CHCP systems installed in the tertiary sector as well as to establish the optimal operation mode for the different plant components on an hour-by-hour basis throughout the year. The objective function to be minimized is the annual total cost. The optimization model considers the legal constraints imposed to feed the surplus autogenerated electricity into the grid at a regulated feed-in tariff. The optimization model is applied to design a system providing energy services for a hospital located in the city of Zaragoza (Spain). The effects of the financial market conditions and energy prices in the optimal structure of the system are analyzed. [Copyright &y& Elsevier]