Guest Editorial Special Section on Advances in Automation and Optimization for Sustainable Transportation and Energy Systems

This special section of the IEEE Transactions on Automation Science and Engineering (T-ASE) focuses on new models, methods, and technologies for energy efficiency and sustainability in transportation and energy systems. In this section, the focus is thus on articles considering sustainable transportation, such as electric vehicles (EVs), integrated with the smart grid requirements. As guest editors, we are very pleased to present the selected 12 papers, whose topics are specifically related to optimal planning of charging stations (CSs), sustainable transportation and mobility, EVs integration in smart grids, reliability, reduction of consumption, demand response and smart grid modeling, optimal scheduling, routing and charging of fleets of EVs, as well as smart parkin

Methods and tools to evaluate the availability of renewable energy sources

The recent statements of both the European Union and the US Presidency pushed in the direction of using renewable forms of energy, in order to act against climate changes induced by the growing concentration of carbon dioxide in the atmosphere. In this paper, a survey regarding methods and tools presently available to determine potential and exploitable energy in the most important renewable sectors (i.e., solar, wind, wave, biomass and geothermal energy) is presented. Moreover, challenges for each renewable resource are highlighted as well as the available tools that can help in evaluating the use of a mix of different sources

A Bi-level Approach for the Stochastic Optimal Operation of Interconnected Microgrids

Smart grid planning and control is becoming a theme of high interest in the last years. This is due to the presence of distributed generation, power from renewable resources and storage systems, to the different actors present over the territory, and to the difficulty of defining appropriate models for decision support. A bilevel optimal control scheme is proposed for grids characterized by renewable and traditional power production, bidirectional power flows, dynamic storage systems, and stochastic modeling issues. In this scheme, the upper level decision maker (UDM) views the lower level decision makers (LDMs) or microgrids as single nodes. In the statement of the UDM problem, the LDM control strategies are structurally and parametrically constrained inside a nonlinear optimization problem that includes load flow equations. Then, the LDMs can follow references from the UDM and use available information at the local level to solve a stochastic optimization problem. The proposed control architecture has been applied to a specific case study (Savona, Italy