Abstract
There is a growing demand for alternative forms of energy that could firstly replace fossil fuels, with the environmental advantages resulting therefrom, but that could be as well economically more beneficial by allowing companies to obtain competitive advantages from the aforementioned alternative forms of energy. In this sense, the use of waste to produce thermal energy is presented as an alternative worthy of study. In this paper, an analysis is made of the use of waste from the textile industry, more precisely cotton waste, which is used as a renewable resource for the production of thermal energy. After the characterization of the waste, the energetic potential is determined comparatively to other fuels such as woodchips and wood pellets. A comparative economic assessment with other fuels is carried out. The obtained results show that the cotton briquettes have a heating value of 16.80 MJ/kg and a cost of 0.006 (sic)/kWh when used as fuel. This predicts an annual reduction in fuel cost of 80, 75 and 70% when compared with fuel-oil, wood pellets and wood chips, respectively. Thus, the use of cotton waste could be a viable alternative, economically and environmentally, to produce thermal energy.

Abstract
This paper analyses the impact of the penetration of electric vehicles (EVs) charging loads on thermal ageing of a distribution transformer of a private industrial client that allows EVs to charge while their owners are at work and at three different working shifts during a day. Furthermore, the system is part of an isolated electric grid in a Portuguese Island. In this paper, a transformer thermal model is used to estimate the hotspot temperature given the load ratio. Real data were used for the main inputs of the model, i.e. private industrial client load, transformer parameters, the characteristics of the factory and electric vehicle parameters.

Abstract
The aim of this paper is to present the development of an innovative experimental reflective pulse oximetry solution targeting wearable health system for daily monitoring purposes. The measurement of two common human physiological indicators is performed, which are the pulse rate and the blood oxygenation level (SpO(2)). The design options are detailed, covering photoplethysmographic (PPG) signals sensing architecture and post- processing digital filter operations. The high resolution of the physiological measures is achieved using sigma delta conversion technique. Conclusions are duly drawn.

Abstract
This paper deals with the radial distribution system reconfiguration problem in a multi-objective scope, aiming to determine the optimal configuration by means of minimization of active power losses and several reliability indices. A novel way to calculate these indices under a mixed-integer linear programming (MILP) approach is provided. Afterwards, an efficient implementation of the e-constraint method using lexicographic optimization is employed to solve the multi-objective optimization problem, which is formulated as a MILP problem. After the Pareto Efficient solution set is generated, a multi-attribute decision making procedure is used, namely the technique for order preference by similarity to ideal solution (TOPSIS) method, so that a decision maker (DM) can express preferences over the solutions and facilitate the final selection.

Abstract
Introducing Combined Heat and Power (CHP) units into Active Distribution Network (ADN) can significantly affect the problem of optimal generation scheduling. A new method for solving the problem of Optimal Scheduling of Combined Heat and Power (OSCHP) units of an ADN with Electric Storage Systems (ESSs) and Thermal Storage Systems (TSSs) considering Industrial Customers (ICs) Inter-Zonal Power Exchanges (IZPEs) is presented. The ADN operator may use CHP units to supply its ICs and based on smart grid conceptual model, it can transact electricity with upstream network. However, the electricity transactions between the ADN and its ICs in normal and contingency scenarios may highly complicate this problem. In this paper, linearization techniques are adopted to linearize equations and a two-stage stochastic mixed integer linear programming (SMILP) model is utilized to solve the problem to determine the optimal generation scheduling units. The first stage models the behaviour of operation parameters, minimizes the operation costs, and checks the feasibility of the ICs' requested firm and non firm IZPEs, while the second stage considers system's stochastic contingency scenarios. The competitiveness of ADN in the deregulated market can be improved by adjusting the proposed decision variables in the two-stage optimization procedure. The proposed method is applied to 18- and 123-bus IEEE test systems to thoroughly demonstrate the benefits of implementing inter-zonal power exchanges.

Abstract
Penetration of distributed generation systems in conventional power systems leads to power quality (PQ) disturbances. This paper provides an improved PQ disturbances classification, which is associated with load changes and environmental factors. Various forms of PQ disturbances, including sag, swell, notch, and harmonics, are taken into account. Several features are obtained through hyperbolic S-transform, out of which the optimal features are selected using a genetic algorithm. These optimal features are used for PQ disturbances classification by employing support vector machines (SVMs) and decision tree (DT) classifiers. The study is supported by three different case studies, considering the experimental setup prototypes for wind energy and photovoltaic systems, as well as the modified Nordic 32-bus test system. The robustness and precision of DT and SWM are performed with noise and harmonics in the disturbance signals, thus providing comprehensive results.