Participation of Electric Vehicle Aggregators in Wholesale Electricity Markets: Recent Works and Future Directions

Electric Vehicles are key to reducing carbon emissions while bringing a revolution to the transportation sector. With the massive increase of EVs in road networks and the growing demand for charging services, the electric power grid faces enormous system reliability and operation stability challenges. Demand and supply disparities create inconsistency in the smooth delivery of electrical power. As a potential solution, EVs and their charging infrastructure can be aggregated to prevent the unwanted effects on power systems and also facilitate ancillary services to the power grid. When not need for transportation purposes, EVs can leverage their batteries for power grid services by participating in the electricity market via mechanisms coordinated by system operators. Hence, the market participation of EV infrastructure can help alleviate the power grid stress during peak periods. However, further research is needed to demonstrate the multiple benefits to both EV owners and power grid operators. This paper briefly overviews the existing literature on market participation of EV aggregators, discuss associated challenges and needs, and propose research directions for future research

Recarga de vehículos eléctricos mediante una optimización entera mixta con participación de respuesta de la demanda

The micro networks of commercial buildings will play an important role for an intelligent city, since having electric vehicle charging (EV) activities can cause performance degradation and overloads in the distribution system.  It is proposed to minimize the costs in the consumption of electric energy of a commercial type building when the recharging of electric vehicles is carried out, it will be carried out by means of installation of photovoltaic panels for which in the study the opening hours of the building will be taken fulfilling the need of the demand, for the optimization process it will be done through a dispatch through allocation of resources.  An integral result obtained from the simulation tests showed that the proposed strategy has satisfactory results and high efficiency.Las micro redes de edificios comerciales jugarán un papel importante para una ciudad inteligente, al tener actividades de carga de vehículos eléctricos (EV) puede causar degradaciones del rendimiento y sobrecargas en el sistema de distribución. Se propone minimizar los costos en el consumo de energía eléctrica de un edificio tipo comercial cuando se realiza la recarga de vehículos eléctricos, se lo realizará mediante instalación de paneles fotovoltaicos para lo cual en el estudio se tomará el horario de atención del edificio cumpliendo la necesidad de la demanda, para el proceso de optimización se hará por medio de un despacho mediante asignación de recursos. Un resultado integral obtenido de las pruebas de simulación se demostró que la estrategia propuesta tiene resultados satisfactorios y alta eficiencia

Respuesta de demanda de energía por introducción de vehículos eléctricos: estado del arte

The replacement of vehicles based on fossil fuels with EV - Electric Vehicles is a global necessity, although it is a great contribution to environmental sustainability and the well-being of humanity carries with it great challenges at all levels, such as the study of the impact on the demand of electrical energy associated with the consumption of these electric vehicles. This document presents a bibliographic review associated with the different topics that this problem addresses such as the global data of electric car penetration and the current state of development of its key element: the batteries, along with the loading and unloading curves of the batteries. The study is carried out through a bibliographic review of the IEEE Xplore, Science Direct and related academic production data bases to identify several key aspects of electric vehicles such as existing data, future estimations, percentage of investment in infrastructure by countries and policies, among others. It also establishes several criteria associated with the impact of the characteristics of the battery in the future of EV's worldwide.El reemplazo de vehículos basados en combustible fósil por vehículos eléctricos - VE es una necesidad mundial, si bien resulta un gran aporte a la sostenibilidad ambiental y el bienestar de la humanidad lleva consigo grandes retos a todo nivel, entre ellos el estudio del impacto en la demanda de energía eléctrica asociada al consumo de estos vehículos eléctricos. Este documento presenta una revisión bibliográfica asociada con los diferentes temas que aborda esta problemática como son las cifras mundiales de penetración de automóviles eléctricos y el estado de desarrollo actual del elemento clave que son las baterías, sus curvas de carga y descarga. El estudio se realiza a través de una revisión bibliográfica de las bases IEEE Xplore, Science Direct y producción académica relacionada, llegando a identificar varios aspectos claves en la actualidad de los vehículos eléctricos como son las cifras existentes, estimaciones futuras, inversión en infraestructura por países, políticas, entre otros. Se establece también varios criterios asociados al impacto de las características de la batería en el futuro de los VE’s a nivel mundial

Initial location selection of electric vehicles charging infrastructure in urban city through clustering algorithm

Transportation is one of the critical sectors worldwide, mainly based on fossil fuels, especially internal combustion engines. In a developing country, heightened dependence on fossil fuels affected energy sustainability issues, greenhouse gas emissions, and increasing state budget allocation towards fuel subsidies. Moreover, shifting to electric vehicles (EVs) with alternative energy, primely renewable energy sources, is considered a promising alternative to decreasing dependence on fossil fuel consumption. The availability of a sufficient EV charging station infrastructure is determined as an appropriate strategy and rudimentary requirement to optimize the growth of EV users, especially in urban cities. This study aims to utilize the k-mean algorithm’s clustering method to group and select a potential EV charging station location in Jakarta an urban city in Indonesia. This study proposed a method for advancing the layout location’s comprehensive suitability. An iterative procedure determines the most suitable value for K as centroids. The K value is evaluated by cluster silhouette coefficient scores to acquire the optimized numeral of clusters. The results show that 95 potential locations are divided into 19 different groups. The suggested initial EV charging station location was selected and validated by silhouette coefficient scores. This research also presents the maps of the initially selected locations and clustering

Management of renewable-based multi-energy microgrids in the presence of electric vehicles

This study proposes a stochastic optimisation programming for scheduling a microgrid (MG) considering multiple energy devices and the uncertain nature of renewable energy resources and parking lot‐based electric vehicles (EVs). Both thermal and electrical features of the multi‐energy system are modelled by considering combined heat and power generation, thermal energy storage, and auxiliary boilers. Also, price‐based and incentive‐based demand response (DR) programs are modelled in the proposed multi‐energy MG to manage a commercial complex including hospital, supermarket, strip mall, hotel and offices. Moreover, a linearised AC power flow is utilised to model the distribution system, including EVs. The feasibility of the proposed model is studied on a system based on real data of a commercial complex, and the integration of DR and EVs with multiple energy devices in an MG is investigated. The numerical studies show the high impact of EVs on the operation of the multi‐energy MGs.©2020 IET. This paper is a postprint of a paper submitted to and accepted for publication in IET Renewable Power Generation 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

Bi-level model for operational scheduling of a distribution company that supplies electric vehicle parking lots

Nowadays, the presence of renewable energy resources (RERs), electric vehicle (EV) penetration, and the implementation of demand response (DR) programs are the main affecting factors in the operational scheduling of a distribution company (DISCO). By the new market participants such as parking lot (PL) owners in the DISCO, a bi-level framework can be created for modeling the distribution network. Therefore, in this paper, a new bi-level model is suggested for DISCO’s operational scheduling that involves technical and environmental terms in the objective function. The maximization of the profit of the DISCO owner and the PL owner are the objective functions in each level. These purposes depend on the customers’ load, the power purchased from the upstream network, the power exchanged with the PL owner (for the upper-level) and the power exchanged with the DISCO owner, as well as the EV owners (for the lower-level). Linearization of the model is carried out by applying the Karush–Kuhn–Tucker (KKT) condition and Fortuny-Amat and McCarl linearization approach. Furthermore, EVs’ and RERs’ uncertainties, as well as DR programs are modeled. Also, three types of risk are described including risk-seeker, risk-neutral, and risk-averse (with conditional value-at-risk (CVaR) index). For evaluation of the proposed model, it is applied to the IEEE 15-bus test system. Results show that by charging/discharging schedule of EVs and critical peak pricing program, the DISCO owner gains more profit. Also, the sensitivity analysis allows determining that the EV penetration, nominal power of RERs and customer involvement in the DR program directly affect the DISCO owner’s profit.© 2019 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

Planificación óptima del intercambio de energía de vehículos eléctricos en estacionamientos considerando incertidumbres

Se espera que los vehículos eléctricos (VE) desempeñen un papel importante en el sistema de transporte debido a los problemas ambientales y las crisis energéticas que hoy en día afectan al planeta. El despliegue de una gran cantidad de vehículos requiere una gestión de demanda adecuada, con el fin de proporcionar menores costos de ampliación e inversión, así como evitar futuras congestiones en la red eléctrica de distribución. Este articulo analiza el intercambio de energía entre los vehículos eléctricos y la red de distribución considerando la capacidad V2G en las estaciones de carga y bajo un esquema de precios según el tiempo de uso (TOU), incentivo para que se carguen y descarguen los VE cuando los precios de la energía eléctrica asociados a la demanda cambien. En este estudio, el agregador de vehículos eléctricos es responsable de proporcionar energía y controlar el patrón de carga de los vehículos eléctricos dentro de los estacionamientos. El modelo propuesto permite determinar los patrones óptimos de carga y descarga del estacionamiento en base a un método que maximiza las ganancias del agregador. Adicionalmente, se aplica el método Monte Carlo para manejar las incertidumbres asociadas al comportamiento de los vehículos durante el día.Electric vehicles (EVs) are expected to play an important role in the transportation system due to environmental problems and energy crises that affect the planet today. The deployment of a large number of vehicles requires adequate demand management, in order to provide lower expansion and investment costs, as well as avoid future congestion in the electrical distribution network. This article analyzes the energy exchange between electric vehicles and the distribution network considering the V2G capacity in the charging stations and under a price scheme according to time of use (TOU), an incentive for EVs to be charged and discharged when electricity prices associated with demand change. In this study, the electric vehicle aggregator is responsible for providing energy and controlling the charging pattern of electric vehicles within parking lots. The proposed model allows determining the optimal parking lot loading and unloading patterns based on a method that maximizes the aggregator's profits. In addition, the Monte Carlo technique is applied to manage the uncertainties associated with the behavior of vehicles during the dayIngeniero EléctricoCuenc