Efficient energy management for the internet of things in smart cities

The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities

Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans. So the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to re-charge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being re-charged. Based on these new perspectives, we formulate the Electric Vehicle Charging Station Placement Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.Comment: Submitted to IEEE Transactions on Smart Grid, revise

The Critical Role of Public Charging Infrastructure

Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

A Framework for Integrating Transportation Into Smart Cities

In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

Efficient heuristic algorithms for location of charging stations in electric vehicle routing problems

Indexación: Scopus.This work has been partially supported by CONICYT FONDECYT by grant 11150370, FONDEF IT17M10012 and the “Grupo de Logística y Transporte” at the Universidad del Bío-Bío.. This support is gratefully acknowledged.Eco-responsible transportation contributes at making a difference for companies devoted to product delivery operations. Two specific problems related to operations are the location of charging stations and the routing of electric vehicles. The first one involves locating new facilities on potential sites to minimise an objective function related to fixed and operational opening costs. The other one, electric vehicle routing problem, involves the consolidation of an electric-type fleet in order to meet a particular demand and some guidelines to optimise costs. It is determined by the distance travelled, considering the limited autonomy of the fleet, and can be restored by recharging its battery. The literature provides several solutions for locating and routing problems and contemplates restrictions that are closer to reality. However, there is an evident lack of techniques that addresses both issues simultaneously. The present article offers four solution strategies for the location of charging stations and a heuristic solution for fleet routing. The best results were obtained by applying the location strategy at the site of the client (relaxation of the VRP) to address the routing problem, but it must be considered that there are no displacements towards the recharges. Of all the other three proposals, K-means showed the best performance when locating the charging stations at the centroid of the cluster. © 2012-2018. National Institute for R and D in Informatics.https://sic.ici.ro/wp-content/uploads/2018/03/Art.-8-Issue-1-2018-SIC.pd

A roadmap for China to peak carbon dioxide emissions and achieve a 20% share of non-fossil fuels in primary energy by 2030

As part of its Paris Agreement commitment, China pledged to peak carbon dioxide (CO2) emissions around 2030, striving to peak earlier, and to increase the non-fossil share of primary energy to 20% by 2030. Yet by the end of 2017, China emitted 28% of the world's energy-related CO2 emissions, 76% of which were from coal use. How China can reinvent its energy economy cost-effectively while still achieving its commitments was the focus of a three-year joint research project completed in September 2016. Overall, this analysis found that if China follows a pathway in which it aggressively adopts all cost-effective energy efficiency and CO2 emission reduction technologies while also aggressively moving away from fossil fuels to renewable and other non-fossil resources, it is possible to not only meet its Paris Agreement Nationally Determined Contribution (NDC) commitments, but also to reduce its 2050 CO2 emissions to a level that is 42% below the country's 2010 CO2 emissions. While numerous barriers exist that will need to be addressed through effective policies and programs in order to realize these potential energy use and emissions reductions, there are also significant local environmental (e.g., air quality), national and global environmental (e.g., mitigation of climate change), human health, and other unquantified benefits that will be realized if this pathway is pursued in China

Smart Cities for Real People

Accelerating urbanization of the population and the emergence of new smart sensors (the Internet of Things) are combining in the phenomenon of the smart city. This movement is leading to improved quality of life and public safety, helping cities to enjoy economies that help remedy some budget overruns, better health care, and is resulting in increased productivity. The following report summarizes evolving digital technology trends, including smart phone applications, mapping software, big data and sensor miniaturization and broadband networking, that combine to create a technology toolkit available to smart city developers, managers and citizens. As noted above, the benefits of the smart city are already evident in some key areas as the technology sees actual implementation, 30 years after the creation of the broadband cable modem. The challenges of urbanization require urgent action and intelligent strategies. The applications and tools that truly benefit the people who live in cities will depend not on just the tools, but their intelligent application given current systemic obstacles, some of which are highlighted in the article. Of course, all the emerging technologies mentioned are dependent on ubiquitous, economical, reliable, safe and secure networks (wired and wireless) and network service providers

Ready To Roll: Southeastern Pennsylvania's Regional Electric Vehicle Action Plan

On-road internal combustion engine (ICE) vehicles are responsible for nearly one-third of energy use and one-quarter of greenhouse gas (GHG) emissions in southeastern Pennsylvania.1 Electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs) and all-electric vehicles (AEVs), present an opportunity to serve a significant portion of the region's mobility needs while simultaneously reducing energy use, petroleum dependence, fueling costs, and GHG emissions. As a national leader in EV readiness, the region can serve as an example for other efforts around the country."Ready to Roll! Southeastern Pennsylvania's Regional EV Action Plan (Ready to Roll!)" is a comprehensive, regionally coordinated approach to introducing EVs and electric vehicle supply equipment (EVSE) into the five counties of southeastern Pennsylvania (Bucks, Chester, Delaware, Montgomery, and Philadelphia). This plan is the product of a partnership between the Delaware Valley Regional Planning Commission (DVRPC), the City of Philadelphia, PECO Energy Company (PECO; the region's electricity provider), and Greater Philadelphia Clean Cities (GPCC). Additionally, ICF International provided assistance to DVRPC with the preparation of this plan. The plan incorporates feedback from key regional stakeholders, national best practices, and research to assess the southeastern Pennsylvania EV market, identify current market barriers, and develop strategies to facilitate vehicle and infrastructure deployment