Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Utilizing Highway Rest Areas for Electric Vehicle Charging: Economics and Impacts on Renewable Energy Penetration in California

California policy is incentivizing rapid adoption of zero emission electric vehicles for light-duty and freight applications. This project explored how locating charging facilities at California’s highway rest stops might impact electricity demand, grid operation, and integration of renewables like solar and wind into California’s energy mix. Assuming a growing population of electric vehicles to meet state goals, state-wide growth of electricity demand was estimated, and the most attractive rest stop locations for siting chargers identified. Using a California-specific electricity dispatch model developed at UC Davis, the project estimated how charging vehicles at these stations would impact renewable energy curtailment in California. It estimated the impacts of charging infrastructures on California’s electricity system and how they can be utilized to decrease the duck curve effect resulting from a large amount of solar energy penetration by 2050.View the NCST Project Webpag

Unique Opportunities of Island States to Transition to a Low-Carbon Mobility System

Small islands developing states (SIDS) contribute minuscule proportions to global greenhouse gas (GHG) emissions and energy consumption, but are highly exposed to climate change impacts, in particular to extreme weather events and sea-level rise. However, there is little research on potential decarbonization trajectories unique to SIDS. Here, we argue that insular topology, scale, and economy are distinctive characteristics of SIDS that facilitate overcoming carbon lock-in. We investigate these dimensions for the three islands of Barbados, Fiji, and Mauritius. We find that insular topologies and small scale offer an opportunity for both public transit corridors and rapid electrification of car fleets. The tourism sector enables local decision-makers and investors to experiment with shared mobility and to induce spillover effects by educating tourists about new mobility options. Limited network effects, and the particular economy thus enables to overcome carbon lock-in. We call for targeted investments into SIDS to transition insular mobility systems towards zero carbon in 2040. The decarbonization of SIDS is not only needed as a mitigation effort, but also as a strong signal to the global community underlining that a zero-carbon future is possible.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Quantitive analysis of electric vehicle flexibility : a data-driven approach

The electric vehicle (EV) flexibility, indicates to what extent the charging load can be coordinated (i.e., to flatten the load curve or to utilize renewable energy resources). However, such flexibility is neither well analyzed nor effectively quantified in literature. In this paper we fill this gap and offer an extensive analysis of the flexibility characteristics of 390k EV charging sessions and propose measures to quantize their flexibility exploitation. Our contributions include: (1) characterization of the EV charging behavior by clustering the arrival and departure time combinations that leads to the identification of type of EV charging behavior, (2) in-depth analysis of the characteristics of the charging sessions in each behavioral cluster and investigation of the influence of weekdays and seasonal changes on those characteristics including arrival, sojourn and idle times, and (3) proposing measures and an algorithm to quantitatively analyze how much flexibility (in terms of duration and amount) is used at various times of a day, for two representative scenarios. Understanding the characteristics of that flexibility (e.g., amount, time and duration of availability) and when it is used (in terms of both duration and amount) helps to develop more realistic price and incentive schemes in DR algorithms to efficiently exploit the offered flexibility or to estimate when to stimulate additional flexibility. (C) 2017 Elsevier Ltd. All rights reserved

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

Online Coordinated Charging of Plug-In Electric Vehicles in Smart Grid to Minimize Cost of Generating Energy and Improve Voltage Profile

This Ph.D. research highlights the negative impacts of random vehicle charging on power grid and proposes four practical PEV coordinated charging strategies that reduce network and generation costs by integrating renewable energy resources and real-time pricing while considering utility constraints and consumer concerns

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Optimal planning of a virtual power plant hosting an EV parking lot

With the increasing penetration of electric vehicles (EV) in the future, VPPs can take some actions for meeting their demand. This way, VPPs can increase their income by selling electric power to EVs and utilizing the battery of EVs as energy storage to facilitate the deployment of renewable energy resources. However, investing too much in charging stations may not have an acceptable return on investment. In this paper, we study the optimal operation and planning of a VPP which is located to certain part of the network and is composed of wind turbines, PV units, as well as unidirectional and bidirectional EV charging stations. In our proposed approach, optimal planning is done considering that the system will be operated optimally. According to the simulation results, EV owners' behavior could have a significant impact on the optimal planning decision of the VPP. In addition, optimal number of the unidirectional and bidirectional EV charging stations depend on the share of the PV and wind generation and the capacity of the line between the VPP and upstream grid.©2022 IET. This paper is a postprint of a paper submitted to and accepted for publication in CIRED Porto Workshop 2022: E-mobility and power distribution systems and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.fi=vertaisarvioitu|en=peerReviewed