Karol Bot Gonçalves

Abstract
The building façade has a crucial role in acting as the interface between the environment and the indoor ambient, and from an engineering and architecture perspective, in the last years, there has been a growing focus on the strategic development of building façades. In this sense, this work aims to present a literature review for the Building Integrated Solar Energy Systems (BI-SES) for façades, subdivided into three categories: thermal, photovoltaic and hybrid (both thermal and photovoltaic). The methodology used corresponds to a systematic review method. A sample of 75 works was reviewed (16 works on thermal BI-SES, 37 works on photovoltaic BI-SES, 22 works on hybrid BI-SES). This article summarises the works and later classifies them according to the type of study (numerical or experimental), simulation tool, parametric analysis and performance when applied.

Abstract
Power systems are going through a transition period. Consumers want more active participation in electric system management, namely assuming the role of producers-consumers, prosumers in short. The prosumers' energy production is heavily based on renewable energy sources, which, besides recognized environmental benefits, entails energy management challenges. For instance, energy consumption of appliances in a home can lead to misleading patterns. Another challenge is related to energy costs since inefficient systems or unbalanced energy control may represent economic loss to the prosumer. The so-called home energy management systems (HEMS) emerge as a solution. When well-designed HEMS allow prosumers to reach higher levels of energy management, this ensures optimal management of assets and appliances. This paper aims to present a comprehensive systematic review of the literature on optimization techniques recently used in the development of HEMS, also taking into account the key factors that can influence the development of HEMS at a technical and computational level. The systematic review covers the period 2018-2021. As a result of the review, the major developments in the field of HEMS in recent years are presented in an integrated manner. In addition, the techniques are divided into four broad categories: traditional techniques, model predictive control, heuristics and metaheuristics, and other techniques.

Abstract
Wildfires threaten and kill people, destroy urban and rural property, degrade air quality, ravage forest ecosystems, and contribute to global warming. Wildfire management decision support models are thus important for avoiding or mitigating the effects of these events. In this context, this paper aims at providing a review of recent applications of machine learning methods for wildfire management decision support. The emphasis is on providing a summary of these applications with a classification according to the case study type, machine learning method, case study location, and performance metrics. The review considers documents published in the last four years, using a sample of 135 documents (review articles and research articles). It is concluded that the adoption of machine learning methods may contribute to enhancing support in different fire management phases.

Abstract

Abstract
The increasing levels of energy consumption worldwide is raising issues with respect to surpassing supply limits, causing severe effects on the environment, and the exhaustion of energy resources. Buildings are one of the most relevant sectors in terms of energy consumption; as such, efficient Home or Building Management Systems are an important topic of research. This study discusses the use of ensemble techniques in order to improve the performance of artificial neural networks models used for energy forecasting in residential houses. The case study is a residential house, located in Portugal, that is equipped with PV generation and battery storage and controlled by a Home Energy Management System (HEMS). It has been shown that the ensemble forecasting results are superior to single selected models, which were already excellent. A simple procedure was proposed for selecting the models to be used in the ensemble, together with a heuristic to determine the number of models.