Autonomous Mobility and Energy Service Management in Future Smart Cities: An Overview

With the rise of transportation electrification, autonomous driving and shared mobility in urban mobility systems, and increasing penetrations of distributed energy resources and autonomous demand-side management techniques in energy systems, tremendous opportunities, as well as challenges, are emerging in the forging of a sustainable and converged urban mobility and energy future. This paper is motivated by these disruptive transformations and gives an overview of managing autonomous mobility and energy services in future smart cities. First, we propose a three-layer architecture for the convergence of future mobility and energy systems. For each layer, we give a brief overview of the disruptive transformations that directly contribute to the rise of autonomous mobility-on-demand (AMoD) systems. Second, we propose the concept of autonomous flexibility-on-demand (AFoD), as an energy service platform built directly on existing infrastructures of AMoD systems. In the vision of AFoD, autonomous electric vehicles provide charging flexibilities as a service on demand in energy systems. Third, we analyze and compare AMoD and AFoD, and we identify four key decisions that, if appropriately coordinated, will create a synergy between AMoD and AFoD. Finally, we discuss key challenges towards the success of AMoD and AFoD in future smart cities and present some key research directions regarding the system-wide coordination between AMoD and AFoD.Comment: 19 pages, 4 figure

Decentralized EV charging and discharging scheduling algorithm based on Type-II fuzzy-logic controllers

Electric vehicles suppose a new paradigm in mobility and a challenge for today electric grids because its number increases day by day. Therefore, it is of paramount importance to keep the electric grid stable to allow an efficient charging of electric vehicles, besides keeping the traditional energy services for every other electric devices in industry, cities and homes. To achieve that, the process of charging and discharging of electric vehicles should be taken under consideration to allow an efficient use of the available energy in the grid and batteries. In the present work, we propose a type-II fuzzy cascade controller that will be run in every electric vehicle following a decentralized approach when it is plugged. In the first level of the controller the need and urgency of charging/discharging are evaluated based on grid voltage that the EV charging station measures. The electricity prices are also considered in this first phase. In the second level, the amount of charging/discharging energy is finally decided based on the battery state and the time remaining for departure specified by the user. The implemented type-II fuzzy controller presents an significant advantage compares to type-I systems because of its better suitability for systems where measures have high levels of uncertainty like those existing in the electric grid or batteries. The controller has been tested on a branch type distribution network, where load demand and energy cost vary dynamically over a three days simulation period.Funding for open access charge: Universidad de Málaga / CBU

A survey on enhancing grid flexibility through bidirectional interactive electric vehicle operations

Smart grids (SG) constitute a revolutionary concept within the energy sector, enabling the establishment of a bidirectional communication infrastructure. This infrastructure significantly improves control, efficiency, and overall service quality in power systems. The study provides an in-depth survey on the classification of EVs, including both plug-in and non-plug-in EVs, and the integration process of V2G, including bidirectional power flow analysis. Moreover, various control strategies for EV integration are explored, ranging from centralized and decentralized to hierarchical control structures. Further, the research thoroughly examines the potential benefits of EV integration and addresses associated challenges, such as battery degradation, infrastructure requirements, cybersecurity and communication issues, grid congestion, and consumer behavior. The study goes beyond theoretical exploration and offers a comprehensive simulation analysis. This analysis leverages the storage capabilities of EVs to provide grid support services. A real-time dynamic dispatch strategy is formulated to integrate EVs into the automatic generation control of multi-energy systems. The findings demonstrate that EVs can effectively mitigate forecasting errors in a power network heavily reliant on wind energy sources. Consequently, the storage capabilities of EVs contribute to enhancing grid flexibility in managing the intermittency of renewable energy resources

An Efficient and Secure Energy Trading Approach with Machine Learning Technique and Consortium Blockchain

In this paper, a secure energy trading mechanism based on blockchain technology is proposed. The proposed model deals with energy trading problems such as insecure energy trading and inefficient charging mechanisms for electric vehicles (EVs) in a vehicular energy network (VEN). EVs face two major problems: finding an optimal charging station and calculating the exact amount of energy required to reach the selected charging station. Moreover, in traditional trading approaches, centralized parties are involved in energy trading, which leads to various issues such as increased computational cost, increased computational delay, data tempering and a single point of failure. Furthermore, EVs face various energy challenges, such as imbalanced load supply and fluctuations in voltage level. Therefore, a demand-response (DR) pricing strategy enables EV users to flatten load curves and efficiently adjust electricity usage. In this work, communication between EVs and aggregators is efficiently performed through blockchain. Moreover, a branching concept is involved in the proposed system, which divides EV data into two different branches: a Fraud Chain (F-chain) and an Integrity Chain (I-chain). The proposed branching mechanism helps solve the storage problem and reduces computational time. Moreover, an attacker model is designed to check the robustness of the proposed system against double-spending and replay attacks. Security analysis of the proposed smart contract is also given in this paper. Simulation results show that the proposed work efficiently reduces the charging cost and time in a VEN.publishedVersio

Integrating Vehicle-to-Grid Technologies in Autonomous Electric Vehicle Systems

Electrochemical Vehicle-to-Grid (V2G) technologies in autonomous electric vehicles (EVs) offer immense potential to revolutionize energy management and optimize the utilization of EVs. By enabling bidirectional energy flow between EVs and the electric grid, V2G allows EVs not only to consume electricity but also to contribute power back to the grid when necessary. When combined with autonomous capabilities, V2G can provide even greater benefits and flexibility. This research abstract highlights key points concerning V2G technologies in autonomous EVs. Firstly, autonomous EVs equipped with V2G technology can function as mobile energy storage units, aiding in grid stabilization and balancing high electricity demand. Secondly, V2G-enabled autonomous EVs can participate in demand response programs, optimizing charging schedules to off-peak hours and reducing strain on the grid during peak demand. Moreover, V2G facilitates the integration of renewable energy sources by allowing autonomous EVs to store and inject excess renewable energy into the grid when needed. Furthermore, V2G-enabled autonomous EVs act as backup power sources during emergencies or power outages, ensuring uninterrupted electricity supply to critical infrastructure. By participating in V2G programs, autonomous EV owners can generate revenue by selling stored energy to the grid and providing grid services, offsetting EV ownership costs. Additionally, autonomous EVs with V2G technology can intelligently manage their charging and discharging based on factors like electricity prices, grid demand, and user preferences, thereby optimizing energy usage and reducing charging costs. While the widespread adoption of V2G technologies in autonomous EVs hinges on infrastructure development, standardization, regulatory frameworks, and user acceptance, their integration is poised to play a significant role in future sustainable energy and transportation systems. As autonomous and electric vehicle technologies continue to evolve, V2G capabilities hold tremendous promise in transforming energy management, promoting grid reliability, and maximizing the benefits of EVs for both consumers and the grid

Control and Optimization of Energy Storage in AC and DC Power Grids

Energy storage attracts attention nowadays due to the critical role it will play in the power generation and transportation sectors. Electric vehicles, as moving energy storage, are going to play a key role in the terrestrial transportation sector and help reduce greenhouse emissions. Bulk hybrid energy storage will play another critical role for feeding the new types of pulsed loads on ship power systems. However, to ensure the successful adoption of energy storage, there is a need to control and optimize the charging/discharging process, taking into consideration the customer preferences and the technical aspects. In this dissertation, novel control and optimization algorithms are developed and presented to address the various challenges that arise with the adoption of energy storage in the electricity and transportation sectors. Different decentralized control algorithms are proposed to manage the charging of a mass number of electric vehicles connected to different points of charging in the power distribution system. The different algorithms successfully satisfy the preferences of the customers without negatively impacting the technical constraints of the power grid. The developed algorithms were experimentally verified at the Energy Systems Research Laboratory at FIU. In addition to the charge control of electric vehicles, the optimal allocation and sizing of commercial parking lots are considered. A bi-layer Pareto multi-objective optimization problem is formulated to optimally allocate and size a commercial parking lot. The optimization formulation tries to maximize the profits of the parking lot investor, as well as minimize the losses and voltage deviations for the distribution system operator. Sensitivity analysis to show the effect of the different objectives on the selection of the optimal size and location is also performed. Furthermore, in this dissertation, energy management strategies of the onboard hybrid energy storage for a medium voltage direct current (MVDC) ship power system are developed. The objectives of the management strategies were to maintain the voltage of the MVDC bus, ensure proper power sharing, and ensure proper use of resources, where supercapacitors are used during the transient periods and batteries are used during the steady state periods. The management strategies were successfully validated through hardware in the loop simulation

EV charging stations and RES-based DG: A centralized approach for smart integration in active distribution grids

Renewable Energy Sources based (RES-based) Dispersed Generation (DG) and Electrical Vehicles (EVs) charging systems diffusion is in progress in many Countries around the word. They have huge effects on the distribution grids planning and operation, particularly on MV and LV distribution grids. Many studies on their impact on the power systems are ongoing, proposing different approaches of managing. The present work deals with a real application case of integration of EVs charging stations with ES-based DG. The final task of the integration is to be able to assure the maximum utilization of the distribution grid to which both are connected, without any upgrading action, and in accordance with Distribution System Operators (DSOs) needs. The application of the proposed approach is related to an existent distribution system, owned by edistribuzione, the leading DSO in Italy. Diverse types of EVs supplying stations, with diverse diffusion scenarios, have been assumed for the case study; various Optimal Power Flow (OPF) models, based on diverse objective functions, reflecting DSO necessities, have been applied and tried. The obtained results demonstrate that a centralized management approach by the DSO, could assure the respect of operation limits of the system in the actual asset, delaying or avoiding upgrading engagements and charges

Control Strategies for Smart Charging and Discharging of Plug- In Electric Vehicles

This chapter aims to provide an overview of the plug-in electric vehicle (PEV) charging and discharging strategies in the electric power system and the smart cities, as well as an application benefiting both consumers and power utility. The electric vehicle technology will be introduced. Then, the main impacts, benefits and challenges related to this technology will be discussed. Following, the role of the vehicles in smart cities will be presented. Next, the major methods and strategies for charging and discharging of plug-in electric vehicles available in the literature will be described. Finally, a new strategy for the intelligent charging and discharging of electric vehicles will be presented, which aims to benefit the consumer and the power utility