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The aim of study is to talk about a generic model of Smart City with a multi-agents system and the aspects correlated to Internet. Smart cities are made by a high level of Information and Communication Technology (ICT) structures able to transmit energy, information flows multidirectional and connect a different sector that include mobility, energy, social, economy. These components are very important to offer intelligence in a city, as basic infrastructure for a definition of a model repeatable and exportable, as well as supported by the European Community, that is allocating considerable funds (Horizon 2020) for the creation of Smart City.

The current economic crisis, combined with growing citizen expectations, is placing increasing pressure on European cities to provide better and more efficient infrastructures and services, often for less cost. This trend has contributed to the growing popularity and use of the term 'Smart City' [1]. The Smart City, represent a new way of thinking about urban space by shaping a model that integrates Green Energy Sources and Systems (GESSs), energy efficiency, sustainable mobility, protection of the environment and economic sustainability, that represent the goals for future developments. Smart cities are made by a high level of Information and Communication Technology-ICT-structures able to transmit energy, information flows multidirectional and connect a different sector that include mobility, energy, social, economy. Into Smart Cities transport systems are sustainable, smart grids are enhanced to ensure greater integration capabilities of production plants from renewable sources, public lighting is efficient, the buildings are equipped with sensors and devices aimed at rationalizing consumption energy and create greater awareness on the part of citizens, with the aim of improving the quality of life of people through a new governance of public administration capable of managing this innovation and cultural change. However, while wishing the transformation of cities in smart systems, have not defined models infrastructure, that allow different subsets to communicate and interact, in order to make the concrete realization of a smart city. The objective of this paper is to discuss a model of Smart City with a multi-agent systems and Internet of things, that provides intelligence to a city, as basic infrastructure for a definition of a model repeatable and exportable, so as advocated by the European Community, that is allocating considerable funds (Horizon 2020) for the creation of Smart City.

Many different types of electric vehicle (EV) charging technologies are described in literature and implemented in practical applications. This paper presents an overview of the existing and proposed EV charging technologies in terms of converter topologies, power levels, power flow directions and charging control strategies. An overview of the main charging methods is presented as well, particularly the goal is to highlight an effective and fast charging technique for lithium ions batteries concerning prolonging cell cycle life and retaining high charging efficiency. Once presented the main important aspects of charging technologies and strategies, in the last part of this paper, through the use of genetic algorithm, the optimal size of the charging systems is estimated and, on the base of a sensitive analysis, the possible future trends in this field are finally valued.

The advent of alternative vehicle technologies such as Electrical Vehicles (EVs) is an efficient effort to reduce the emission of carbon oxides and nitrogen oxides. Ironically, EVs poses concerns related to vehicle recharging and management. Due to the significance of charging station infrastructure, electric vehicles' charging stations deployment is investigated in this work. Its aim is to consider several limitations such as the power of charging station, the average time needed for each recharge, and traveling distance per day. Initially, a mathematical formulation of the problem is framed. Then, this problem is optimized by application of Genetic Algorithm (GA), with the objective to calculate the necessary number of charging stations then finding the best positions to locate them to satisfy the clients demand.

The strong growth of the solar power generation industry requires an increasing need to predict the profile of solar power production over a day and develop highly efficient and optimized stand-alone and grid-connected photovoltaic systems. Moreover, the opportunities offered by Battery Energy Storage Systems (BESSs) coupled with PV systems require an ability to forecast the load power to optimize the size of the entire system composed of PV panels and storage devices. This paper presents a sizing and control strategy of BESSs for dispatching a photovoltaic generation farm in the 1-hour ahead and day-ahead markets. The forecasting of the solar irradiation and load power consumption is performed by developing a predictive model based on a feedforward neural network trained with the Levenberg-Marquardt back-propagation learning algorithm

The incorporation of renewable energy and the transportation system can be significantly beneficial for the economy and environment of Bangladesh. The main energy source for vehicles in Bangladesh are the country’s natural gas and fuel. However, due to the rapid depletion of the gas reserve, soaring gas prices and global warming, alongside the environmental pollution caused by burning fuel, this raises concerns about these energy sources. Renewable energy offers a plausible solution to these problems. This paper’s objective is to focus on the maximum usages of a solar photovoltaic (PV) system in electrical vehicles and to minimize the environmental impact in terms of CO2 emission. This system may be partially used to power up the electric vehicle with a charging facility and contribute excess power to the national grid. The modeling, with its optimal analysis of the green transportation system, is simulated using the Hybrid Optimization of Multiple Energy Renewables (HOMER) software. The energy produced by the PV system can provide up to 13,792 kWh/year. Approximately 21% of the total production can be used in the charging station for charging the electrical vehicles and the rest of the energy can contribute to the national grid. Moreover, using the proposed concept of green transport will ultimately reduce greenhouse gas emissions by 52,944 kg/year.