Abstract
Nowadays, Electric Vehicles (EVs) are the new technology to reduce the usage of fossil fuels and to prevent the environmental issues. But, increasing the number of EVs and mismanagement of their energy in distribution networks would cause higher operational costs and lower network security. This paper evaluates the voltage security of distribution networks in the presence of EVs. Accordingly, the maximization of voltage security margin (VSM) and the minimization of operational cost are considered as the main objective functions in the optimization problem of active and reactive power management. The constraints of the proposed optimization problem include power flow equations, system operating limits and EVs constraints. It is supposed that the EVs are equipped with bidirectional chargers to control active and reactive power, simultaneously. The proposed model is implemented on the 33-bus distribution network to evaluate the performance of the proposed optimization scheme for distribution network management in the presence of EVs.

Abstract
In this work is discussed the importance of the renewable production forecast in an island environment. A probabilistic forecast based on kernel density estimators is proposed. The aggregation of these forecasts, allows the determination of thermal generation amount needed to schedule and operating a power grid of an island with high penetration of renewable generation. A case study based on electric system of S. Miguel Island is presented. The results show that the forecast techniques are an imperative tool help the grid management.

Abstract
Biomass as an energy source contributes to a decrease in the dependence on imported fossil fuels, while at the same time, adding value to the countries where biomass fuel sources thrive, in addition to providing a source of renewable energy. Knowledge of the behaviour of fuel is essential in order to design and operate equipment safely and efficiently. In particular, knowledge about mineral content is essential because the ashes play an important role in the dynamics of the generation system. Through knowledge of the chemical composition and physical properties of the ashes, it is possible to predict the tendency to form deposits in the boiler components, as well as their potential to cause corrosion, erosion and abrasion. The behaviour of the ashes in the system is highly dependent on fuel, particularly when it comes from industrial waste or energy crops. These fuels have a higher mineral content, particularly sodium (Na), potassium (K), phosphorous (P) and chloride (Cl). They also have higher ash content with a low melting point and high corrosion potential. This paper focuses on the characteristics of the ashes derived from the combustion of biomass, with particular attention paid to the chemical transformations at high temperatures, as well as its effect on the combustion equipment. Emphasis is placed on the potential problems that occur when biomass-burning technologies are used for energy crops, in order to avoid catastrophic failures. It concludes with recommendations for the management, control and prevention of problems associated with ash.

Abstract
With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

Abstract
In this study the case of the energy consumption profile of the Aristotle University of Thessaloniki, in Greece, is presented and statistically analyzed by clustering methods on the basis of seasonal daily load curves and load shape factors, using data from real-time measurements. The results indicate that the categorization of active power demand in university buildings is an extremely useful tool for understanding and predicting the seasonal, hourly and daily energy consumption changes, which is the first step towards adopting energy efficiency policies in such scale premises as well as performing demand-side actions aiming to achieve a more economical and environmentally sustainable energy usage.

Abstract
In this paper, islanding detection in a hybrid distributed generation (DG) system is analyzed by the use of hyperbolic S-transform (HST), time-time transform, and mathematical morphology methods. The merits of these methods are thoroughly compared against commonly adopted wavelet transform (WT) and S-transform (ST) techniques, as a new contribution to earlier studies. The hybrid DG system consists of photovoltaic and wind energy systems connected to the grid within the IEEE 30-bus system. Negative sequence component of the voltage signal is extracted at the point of common coupling and passed through the above-mentioned techniques. The efficacy of the proposed methods is also compared by an energy-based technique with proper threshold selection to accurately detect the islanding phenomena. Further, to augment the accuracy of the result, the classification is done using support vector machine (SVM) to distinguish islanding from other power quality (PQ) disturbances. The results demonstrate effective performance and feasibility of the proposed techniques for islanding detection under both noise-free and noisy environments, and also in the presence of harmonics.