Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study

Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG(Lab)(2)) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications

Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications

[EN] The need for effective freight and human transportation systems has consistently increased during the last decades, mainly due to factors such as globalization, e-commerce activities, and mobility requirements. Traditionally, transportation systems have been designed with the main goal of reducing their monetary cost while offering a specified quality of service. During the last decade, however, sustainability concepts are also being considered as a critical component of transportation systems, i.e., the environmental and social impact of transportation activities have to be taken into account when managers and policy makers design and operate modern transportation systems, whether these refer to long-distance carriers or to metropolitan areas. This paper reviews the existing work on different scientific methodologies that are being used to promote Sustainable Transportation Systems (STS), including simulation, optimization, machine learning, and fuzzy sets. This paper discusses how each of these methodologies have been employed to design and efficiently operate STS. In addition, the paper also provides a classification of common challenges, best practices, future trends, and open research lines that might be useful for both researchers and practitioners.This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033, RED2018-102642-T) and the SEPIE Erasmus+ Program (2019-I-ES01-KA103-062602), and the IoF2020-H2020 (731884) project.Torre-Martínez, MRDL.; Corlu, CG.; Faulin, J.; Onggo, BS.; Juan-Pérez, ÁA. (2021). Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications. Sustainability. 13(3):1-21. https://doi.org/10.3390/su1303155112113

Smart Energy and Intelligent Transportation Systems

With the Internet of Things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city. This facilitates a more efficient use of physical infrastructure and encourages citizen participation. Smart energy and smart mobility are among the key aspects of the smart city, in which the electric vehicle (EV) is believed to take a key role. EVs are powered by various energy sources or the electricity grid. With proper scheduling, a large fleet of EVs can be charged from charging stations and parking infrastructures. Although the battery capacity of a single EV is small, an aggregation of EVs can perform as a significant power source or load, constituting a vehicle-to-grid (V2G) system. Besides acquiring energy from the grid, in V2G, EVs can also support the grid by providing various demand response and auxiliary services. Thanks to this, we can reduce our reliance on fossil fuels and utilize the renewable energy more effectively. This Special Issue “Smart Energy and Intelligent Transportation Systems” addresses existing knowledge gaps and advances smart energy and mobility. It consists of five peer-reviewed papers that cover a range of subjects and applications related to smart energy and transportation

Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit

Intelligent Mobility in Smart Cities

Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the problem, the integration of systems for efficiency gains may compromise the resilience of an urban system. This all needs to be taken into consideration when thinking about Smart Cities. The transportation field must also apply the principles and concepts mentioned above. This cannot be understood without considering its links and effects on the other components of an urban system. New technologies allow for new means of travel to be built, and new business models allow for existing ones to be utilized. This Special Issue puts together papers with different focuses, but all of them tackle the topic of smart mobility

Framework de Tomada de Decisão para Last-Mile Sustentável

The e-commerce growth, propelled by factors like globalization, urbanization, or the COVID-19 pandemic, has been raising the demand for logistic activities. This affects the entire supply chain, especially the last-mile, as it is considered the most ineffective part of the supply chain and a source of negative externalities. Although various solutions promise to alleviate these problems, understanding them and selecting the best has proven to be difficult due to conflicting criteria, multiple perspectives, and trade-offs. The vicissitudes of complex and sensitive urban contexts like historic centers also contribute to this difficulty. This work contributes an integrated framework that may assist the involved stakeholders in decision-making. To this end, this work is based on a three-part methodology. The extensive systematic literature review developed provided an integrated overview of this fragmented research area. This review confirmed the multidisciplinary nature of the topic, as there is an increasing number of studies conducted under very different perspectives. Furthermore, it was found that the economic dimension is the most considered; the most polluting countries contributed little to the research; and the solutions involve trade-offs. The literature review supported the definition of the hierarchical model that structures last-mile operations in historic centers. This model was evaluated by interviewing a group of experts. After integrating the experts’ feedback, the model was quantified by the same experts according to an AHP-TOPSIS approach. This quantification had as a case study the historic center of Porto, Portugal. The experts considered the three sustainability dimensions identically important. Air pollution was the most valued sub-criterion whereas Visual pollution was the least. All last-mile solutions considered in the model achieved similar results, therefore suggesting a combined distribution strategy. Nevertheless, the use of parcel lockers is the most favorable solution and seems adequate in Porto’s historic center.O crescimento do e-commerce, impulsionado por fatores como a globalização, a urbanização ou a pandemia de COVID-19, tem aumentado a procura por atividades logísticas. Isto afeta toda a cadeia de abastecimento, principalmente a última-milha, por ser considerada a parte mais ineficaz da cadeia de abastecimento e uma fonte de externalidades negativas. Embora existam várias soluções que prometem aliviar estes problemas, entendêlas e selecionar a melhor tem se provado difícil devido a critérios conflituosos, múltiplas perspetivas e trade-offs. As vicissitudes de contextos urbanos complexos e sensíveis como os centros históricos também contribuem para essa dificuldade. Este trabalho contribui um framework integrado que pode auxiliar os stakeholders envolvidos na tomada de decisão. Para este fim, este trabalho é baseado numa metodologia composta por três partes. A extensa revisão sistemática da literatura desenvolvida forneceu uma visão integrada desta área de investigação fragmentada. Esta revisão confirmou o caráter multidisciplinar do tema, pois há um número crescente de estudos conduzidos sob perspetivas muito diferentes. Além disso, verificou-se que a dimensão económica é a mais considerada; os países mais poluentes contribuíram pouco para a pesquisa; e as soluções envolvem trade-offs. A revisão da literatura suportou a definição do modelo hierárquico que estrutura as operações de última-milha em centros históricos. Este modelo foi avaliado entrevistando um grupo de experts. Após a integração do feedback dos experts, o modelo foi quantificado pelos mesmos de acordo com uma abordagem AHP-TOPSIS. Esta quantificação teve como caso de estudo o centro histórico do Porto, Portugal. Os experts consideraram as três dimensões da sustentabilidade identicamente importantes. O subcritério relativo à poluição atmosférica foi o mais valorizado, enquanto o menos foi o relativo à poluição visual. Todas as soluções de últimamilha consideradas no modelo alcançaram resultados semelhantes, sugerindo uma estratégia de distribuição combinada. No entanto, o uso de parcel lockers é a solução mais favorável e é aparentemente adequada para o centro histórico do Porto

Future Transportation

Greenhouse gas (GHG) emissions associated with transportation activities account for approximately 20 percent of all carbon dioxide (co2) emissions globally, making the transportation sector a major contributor to the current global warming. This book focuses on the latest advances in technologies aiming at the sustainable future transportation of people and goods. A reduction in burning fossil fuel and technological transitions are the main approaches toward sustainable future transportation. Particular attention is given to automobile technological transitions, bike sharing systems, supply chain digitalization, and transport performance monitoring and optimization, among others

PV Charging and Storage for Electric Vehicles

Electric vehicles are only ‘green’ as long as the source of electricity is ‘green’ as well. At the same time, renewable power production suffers from diurnal and seasonal variations, creating the need for energy storage technology. Moreover, overloading and voltage problems are expected in the distributed network due to the high penetration of distributed generation and increased power demand from the charging of electric vehicles. The energy and mobility transition hence calls for novel technological innovations in the field of sustainable electric mobility powered from renewable energy. This Special Issue focuses on recent advances in technology for PV charging and storage for electric vehicles

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy