Abstract
There is a large consensus on the importance of human behaviour on the energy performance of buildings. Energy policy orientations consistently take into account the importance of the building stock in the overall energy use by societies. Existing buildings are specially challenging, as reliable diagnoses are required to take appropriate action towards comfort and energy efficiency. Managers also play a determinant role in building performance, either on investment decisions in technology or on the building operation. Middle-out agents may determine effective energy use options and positively influence behaviours at both levels, top management and occupants. Interdisciplinary cooperation amongst members of research teams is required for energy-efficient building design, coping simultaneously with technological and behavioural issues and their interrelations, privileging occupant-centred approaches.

Abstract
Several technological, social and organizational factors influence energy management in school buildings, resulting in a complex situation away from the usual engineering approach. The selection of evaluation criteria to assess the energy performance of school buildings remains one of the most challenging aspects since these should accommodate the perspectives of the potential key stakeholders. This paper presents a comprehensive problem structuring approach combining Soft Systems Methodology and Value Focused Thinking to elicit and organize the multiple aspects that influence energy efficiency of school buildings. The main aim of this work is structuring the fundamental objectives to develop a criteria tree to be considered in a multi-criteria classification model to be used by management entities for rating overall energy performance of school buildings. This methodological framework helped grasping the main issues at stake for a thorough energy performance assessment of school buildings and the need to define adequate policies for improvement.

Abstract
As the access to consumption data available in household smart meters is now very common in several developed countries, this kind of information is assuming a providential role for different players in the energy sector. The proposed study was applied to data available from the Smart Meter Energy Consumption Data in the London Households dataset, provided by UK Power Networks, containing half-hourly readings from an original sample of 5567 households (71 households were hereby carefully selected after a justified filtering process). The main aim is to forecast the day-ahead load profile, based only on previous load values and some auxiliary variables. During this research different forecasting models are applied, tested and compared to allow comprehensive analyses integrating forecasting accuracy, processing times and the interpretation of the most influential features in each case. The selected models are based on Multivariate Adaptive Regression Splines, Random Forests and Artificial Neural Networks, and the accuracies resulted from each model are compared and confronted with a baseline (Naive model). The different forecasting approaches being evaluated have been revealed to be effective, ensuring a mean reduction of 15% in Mean Absolute Error when compared to the baseline. Artificial Neural Networks proved to be the most accurate model for a major part of the residential consumers.

Abstract
During the next decades the refurbishment of old buildings will be an essential way to contribute to the global improvement of buildings energy performance indicators. Within this context, the present paper is focused on the use of electrochromic (EC) windows, an emerging technology alternative to shading devices, to control solar gains in buildings located in Mediterranean climates. The optical properties adjustments of the EC glasses are discussed based on the incident solar radiation. The ESP-r building energy simulation software was used to study the energy savings resulting from the application of electrochromic windows, considering the comparison of several windows solutions (single, double-glazing and EC windows) and windows orientations (East, South and West). In addition, different transition ranges for the optical properties of the EC glasses are assessed through the analysis of the energy needs for space heating and cooling. The main conclusion is that EC technology is an effective option in cooling dominated buildings. The impact of EC windows is highly dependent on facade orientation, being a valid option particularly in the cases of the East and West facades. For these facades, the control set point found to be effective corresponds to an incident solar radiation on the glass of 150 W/m(2) to impose a total coloured state. For the South facade the results show no significant advantage of using EC windows.

Abstract
This work presents a multi-criteria classification system considering multiple, conflicting and incommensurate evaluation aspects influencing energy efficiency in school buildings. The multi-criteria ELECTRE TRI method is used to classify energy performance of school buildings into categories of merit using the IRIS software. The alternatives under evaluation are assigned to predefined ordered categories according to their absolute performance and not in comparison with the performance of other alternatives. Each alternative is assessed using reference profiles defming the boundaries of the categories in which the alternatives should be sorted. The model was applied using a set of performance indicators obtained in the framework of a research and development project aimed at assessing the energy performance of a sample of Portuguese school buildings. IRIS allowed inferring robust conclusions by indicating the range of categories for each alternative, considering the decision maker's preferences, captured by the parameters of ELECTRE TRI. (C) 2017 The Authors. Published by Elsevier Ltd.

Abstract
The main goal of this paper is to present a set of well-defined and structured procedures to establish guidelines for the application of an integrated assessment of energy performance and indoor climate in schools. Increasing the knowledge about how energy is consumed in schools is a way to enhance the awareness of school managers (board of directors) about the importance of improving energy efficiency and reducing energy costs. The proposed methodology helps to identify major energy consuming equipment in school buildings and potential energy conservation measures. The assessment of indoor climate identifies potential corrective measures to problems related to indoor air quality and thermal comfort, also supporting the study of further energy conservation measures associated with ensuring environmental quality. Results of a case study showed that the expected energy consumption reduction is about 11.2% due to a better usage of daylighting and 4.5% due to the reduction of fresh air flow rates, while extending the ventilation operation time. In addition, there is a considerable non-calculated potential for energy savings and improvement of indoor environmental conditions in school buildings, promoting students and teachers productivity and wellbeing.