Ultracapacitors for port crane applications: Sizing and techno-economic analysis

The use of energy storage with high power density and fast response time at container terminals (CTs) with a power demand of tens of megawatts is one of the most critical factors for peak reduction and economic benefits. Peak shaving can balance the load demand and facilitate the participation of small power units in generation based on renewable energies. Therefore, in this paper, the economic efficiency of peak demand reduction in ship to shore (STS) cranes based on the ultracapacitor (UC) energy storage sizing has been investigated. The results show the UC energy storage significantly reduce the peak demand, increasing the load factor, load leveling, and most importantly, an outstanding reduction in power and energy cost. In fact, the suggested approach is the start point to improve reliability and reduce peak demand energy consumption

Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial

DEVELOPING A SMART AND SUSTAINABLE PUBLIC TRANSPORTATION SYSTEM: A CASE STUDY IN CAMDEN, NEW JERSEY

The transportation sector is a major contributor to air pollution and Greenhouse Gas (GHG) emissions. As a significant source of emissions, public transportation presents an opportunity for mitigation through electrification. However, transitioning to an electric bus fleet necessitates substantial investments in bus procurement and charging infrastructure. To address the associated costs, this study introduces a mixed-integer linear mathematical model developed to optimize the location of on-route fast charging stations within bus networks. The central objective of this optimization formulation is to minimize the overall cost of establishing the charging infrastructure. The study employs a real-world case study focusing on a Camden, NJ, USA bus network. Key considerations include optimizing charging station locations considering time constraints at bus stops to avoid schedule delays and inconvenience for passengers during the charging process. Furthermore, the study investigates the sensitivity of the optimization model in response to variations in parameters. Notably, battery capacity, charger power, average energy consumption, dwell time, and minimum and maximum state of charge significantly affect the optimal locations and required number of chargers. The insights generated from this study are anticipated to offer valuable guidance to policymakers, practitioners, and researchers involved in planning the transition of bus fleets towards zero-emission vehicles

Robust energy system planning for decarbonization under technological uncertainty: From transport electrification to power system investments

This work develops energy system modeling tools that identify features of a robust energy policy: a policy that performs well relative to alternatives. The tools are based on the Open Souce Modeling System (OSeMOSYS), are named the Multipurpose OSeMOSYS-based Framework (MOMF), and are applied to Costa Rica´s energy transition through the lens of its National Decarbonization Plan (NDP). The MOMF can support energy decarbonization planning exercises, and it is suitable to address the uncertainty involved in a decades-long process. It compares possible NDP futures -quantitative combinations of uncertainties and sectoral policy objectives- to a business-as-usual (BAU) scenario without decarbonization. The MOMF also evaluates actors within a country, including the fiscal impacts of decarbonization, following the best practices of applied energy modeling for policy support. This work finds that the NDP has high economic benefits (avoided costs relative to the BAU) in the long term, equivalent to 5.5% of GDP yearly in the 2041-2050 decade. In 2031-2040, the benefits are 0.8% of GDP yearly; in 2022-30, the NDP faces net costs (more costs than the BAU) of 0.9% of GDP yearly. These results are averages across futures and can be higher or lower. The government will have lower direct tax revenue of about 0.87% of GDP yearly in 2041-2050 and will need to redistribute benefits to compensate for this. It can use vehicle-kilometer taxes (VKT), property taxes, or energy taxes for the redistribution, mainly taxing private transport owners -who have the highest benefits-. However, to facilitate the decarbonization of freight firms in 2022-2030 and 2031-2040, the government could subsidize their zero-emission vehicles (ZEV) adoption. High benefits, low emissions complying with net-zero targets, and low electricity and public transport prices are desirable policy outcomes. Low costs for ZEVs and energy infrastructure -including renewables and storage- are crucial uncertain conditions for desirable outcomes. The robust levers the government can adopt to achieve desirable outcomes must decouple economic growth from transport activity. The specific levers include public transport investments, digitalization, non-motorized transport, ride-sharing, logistics hubs, and city densification. Moreover, low electricity prices need a low cost of capital to finance investments in the power sector.UCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Ingeniería::Maestría Académica en Ingeniería Eléctric

A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed