A multi-layer market for vehicle-to-grid energy trading in the smart grid

In this paper, we propose a novel multi-layer market for analyzing the energy exchange process between electric vehicles and the smart grid. The proposed market consists essentially of two layers: a macro layer and a micro layer. At the macro layer, we propose a double auction mechanism using which the aggregators, acting as sellers, and the smart grid elements, acting as buyers, interact so as to trade energy. We show that this double auction mechanism is strategy-proof and converges asymptotically. At the micro layer, the aggregators, which are the sellers in the macro layer, are given monetary incentives so as to sell the energy of associated plug-in hybrid electric vehicles (PHEVs) and to maximize their revenues. We analyze the interaction between the macro and micro layers and study some representative cases. Depending on the elasticity of the supply and demand, the utility functions are analyzed under different scenarios. Simulation results show that the proposed approach can significantly increase the utility of PHEVs, compared to a classical greedy approach.postprin

Assessment of the Use of Renewable Energy Sources for the Charging Infrastructure of Electric Vehicles

Application of renewable energy sources is a relevant area of energy supply for urban infrastructure. In 2019, the share of energy produced by such sources reached 11% (for solar energy) and 22% (for wind energy) of the total energy produced during the year. However, these systems require an improvement in their efficiency that can be achieved by introducing electric vehicles. They can accumulate, store and transfer surplus energy to the city’s power grid. A solution to this problem is a smart charging infrastructure. The existing studies in the field of charging infrastructure organization for electric vehicles consider only models locating charging stations in the city or the calculation of their required number. These calculations are based on socio-economic factors and images of a potential owner of an electric vehicle. Therefore, the aim of this study is to develop a methodology for determining the location of charging stations and their required number. The calculation will include the operating features of the existing charging infrastructure, which has not been done before. Thus, the purpose of this article is to research the operation of the existing charging infrastructure. This will provide an opportunity to develop approaches to the energy supply of charging infrastructure and city’s power grid from renewable energy sources. The article presents an analysis of data on the number of charging sessions during the year, month and day. This data enable us to construct curves of the charging session number and suggest ways to conduct the next stages of this study. Doi: 10.28991/esj-2020-01251 Full Text: PD

Optimal V2G scheduling of electric vehicles and unit commitment using chemical reaction optimization

An electric vehicle (EV) may be used as energy storage which allows the bi-directional electricity flow between the vehicle's battery and the electric power grid. In order to flatten the load profile of the electricity system, EV scheduling has become a hot research topic in recent years. In this paper, we propose a new formulation of the joint scheduling of EV and Unit Commitment (UC), called EVUC. Our formulation considers the characteristics of EVs while optimizing the system total running cost. We employ Chemical Reaction Optimization (CRO), a general-purpose optimization algorithm to solve this problem and the simulation results on a widely used set of instances indicate that CRO can effectively optimize this problem. © 2013 IEEE.published_or_final_versio

Capacity Estimation for Vehicle-to-Grid Frequency Regulation Services with Smart Charging Mechanism

Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Frequency regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide frequency regulation services. However, V2G is a dynamic system where the participating EVs come and go independently. Thus it is not easy to estimate the regulation capacities for V2G. In a preliminary study, we modeled an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation-up and regulation-down, separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitating a new business model for V2G. In this paper, we extend our previous development by designing a smart charging mechanism which can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model.Comment: 11 pages, Accepted for publication in IEEE Transactions on Smart Gri

Vehicular Energy Network

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Opportunistic Routing for Vehicular Energy Network

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Electric vehicle as a service (EVaaS):applications, challenges and enablers

Under the vehicle-to-grid (V2G) concept, electric vehicles (EVs) can be deployed as loads to absorb excess production or as distributed energy resources to supply part of their stored energy back to the grid. This paper overviews the technologies, technical components and system requirements needed for EV deployment. Electric vehicle as a service (EVaaS) exploits V2G technology to develop a system where suitable EVs within the distribution network are chosen individually or in aggregate to exchange energy with the grid, individual customers or both. The EVaaS framework is introduced, and interactions among EVaaS subsystems such as EV batteries, charging stations, loads and advanced metering infrastructure are studied. The communication infrastructure and processing facilities that enable data and information exchange between EVs and the grid are reviewed. Different strategies for EV charging/discharging and their impact on the distribution grid are reviewed. Several market designs that incentivize energy trading in V2G environments are discussed. The benefits of V2G are studied from the perspectives of ancillary services, supporting of renewables and the environment. The challenges to V2G are studied with respect to battery degradation, energy conversion losses and effects on distribution system

Dynamic Programming based approach for Energy Trading

Bi-directional Energy Trading is going to play an essential role in facilitating the increased usage of distributed renewable energy sources. The smooth transition towards these clean sources of energy would require opening up of the energy markets to allow for a two-way electricity trade. The study proposes a dynamic programming based energy trading framework (called Dynamic Battery Charging (DBC) Algorithm) from the end-user perspective. Using the proposed energy transfer model the framework finds out the optimal battery charge state at the consumer end. To further improve the performance of the framework, the original DBC algorithm is clubbed together with a capacity fading based battery cost model. For testing and validation purpose, a case study of three different load profiles (different in scale) in three energy markets is done. The simulation results show the profitability of the proposed strategy in all the tested scenarios