Modelado de la demanda de carga lenta y rápida de vehículos eléctricos para el estudio de impacto en la red de distribución

El presente proyecto se ha desarrollado para proponer una metodología de modelización de la demanda de carga lenta y rápida de vehículos eléctricos para el estudio de impacto en la red de distribución. El capítulo 1 es la memoria del análisis del estado del arte de esta temática. En el capítulo 2 se desarrolla el modelo para carga lenta, en el capítulo 3 se añade la carga rápida y en el capítulo 4 se aplica a un caso de estudio. En los últimos años el desarrollo de los vehículos eléctricos se ha acelerado considerablemente hasta la llegada al gran público de modelos con prestaciones parecidas a las actuales en vehículos de combustión interna. La carga de vehículos eléctricos, cuando quieran recuperar la energía, representa un reto para la red eléctrica en todos los niveles, por lo que la carga de los VE debe enmarcarse dentro de un contexto global. Dado que es probable que la movilidad de los próximos años sea en vehículo eléctrico, existe la necesidad de realizar diversos estudios de todos los aspectos a los que afectará para facilitar su implantación. El presente estudio se focaliza en la modelización del consumo eléctrico durante el proceso de carga. La modelización de esta nueva demanda eléctrica es necesaria para evaluar la capacidad que tienen la redes eléctricas de asimilar esta nueva carga. La modelización de la demanda depende de dos factores: las características de los vehículos eléctricos y la movilidad de los usuarios. Las características de los vehículos que afectarán a la red eléctrica son, principalmente, la batería, el consumo energético y el tipo de vehículo. En cuanto a la movilidad, el tipo de usuario, la distancia recorrida y el instante en el que se producen los desplazamientos determinarán la demanda eléctrica. La relación entre estas variables es la que determina las necesidades de carga de los usuarios. Seguidamente se deben considerar variables relativas a la infraestructura que posibilita la carga de los vehículos para así satisfacer la demanda, ya que ésta debe facilitar la energía y potencia para la carga de las baterías. Estos procesos de carga pueden ser denominados carga lenta, que utiliza una infraestructura doméstica, y carga rápida, que requiere una infraestructura más compleja similar a las gasolineras actuales, por lo que no podrá instalarse a nivel doméstico. Una vez modelizada esta nueva demanda, debe asociarse con la demanda eléctrica convencional de la zona de estudio, ya que ambas se solicitarán en la misma red. En esta interactuación podría suceder que, en determinadas condiciones, coincidan ambas puntas de demanda, que podrían impactar en la operación de la red en aspectos de calidad de suministro. De esta manera, se pueden evaluar las consecuencias de la carga de vehículos eléctricos en la red, y así proponer soluciones que reduzcan los posibles impactos

Generación eléctrica en el Chad

Peer Reviewe

The potential role of flexibility during peak hours on greenhouse gas emissions: A life cycle assessment of five targeted national electricity grid mixes

On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.Peer ReviewedPostprint (published version

Probabilistic agent-based model of electric vehicle charging demand to analyse the impact on distribution networks

Electric Vehicles (EVs) have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processes required to reach its destination. This methodology also permits to consider social and economic variables. Furthermore, the model is stochastic, in order to consider the random pattern of some variables. The model is applied to Barcelona’s (Spain) mobility pattern and uses the 37-node IEEE test feeder adapted to common distribution grid characteristics from Barcelona. The corresponding grid impact is analyzed in terms of voltage drop and four charging strategies are compared. The case study indicates that the variability in scenarios without control is relevant, but not in scenarios with control. Moreover, the voltages do not reach the minimum voltage allowed, but the MV/LV substations could exceed their capacities. Finally, it is determined that all EVs can charge during the valley without any negative effect on the distribution grid. In conclusion, it is determined that the methodology presented allows the EV charging demand to be calculated, considering different variables, to obtain better accuracy in the results.Peer ReviewedPostprint (published version

Centralized flexibility services for distribution system operators through distributed flexible resources

Under the context of smart grids within smart cities, increasing distributed generation, consumer empowerment and emerging flexibility services, distribution system operators could benefit by activating flexibility in distribution grids to avoid deploying new infrastructures and grid overloading. The solution offered by this work is an energy management system algorithm capable of activating flexibility behind the prosumer main meter during constrained periods. Therefore, the distribution system operator could compensate grid congestion during high consumption or production periods and increase their renewable generation hosting capacity by using behind-the-meter flexibility during peak production periods.Postprint (published version

Local flexibility market design for aggregators providing multiple flexibility services at distribution network level

This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.Postprint (published version

Methodology for the evaluation of resilience of ICT systems for smart distribution grids

Ensuring resilient operation and control of smart grids is fundamental for empowering their deployment, but challenging at the same time. Accordingly, this study proposes a novel methodology for evaluating resilience of Information and Communication Technology (ICT) systems for smart distribution grids. Analysing how the system behaves under changing operating conditions a power system perspective allows to understand how resilient the smart distribution grid is, but the resilience of the ICT system in charge of its operation affects the overall performance of the system and does, therefore, condition its resilience. With the aim of systematising the evaluation of ICT systems’ resilience, this study proposes to combine a standardized modelling of Smart Grids, the Smart Grid Architecture Model (SGAM), with a data structured diagram, the Entity Relationship Model (ERM). The architecture of smart distribution grids is analysed through SGAM. Then, their technical characteristics and functionalities are defined and represented in a ERM diagram. Finally, the attributes or properties of the system components are used to formulate resilience indicators against different types of disturbances. This methodology is then applied to analyse the resilience of a ICT platform being developed in EMPOWER H2020 project.Postprint (published version

Architecture definition and operation testing of local electricity markets. The EMPOWER project

Peer ReviewedPostprint (author's final draft

Day-ahead micro-market design for distributed energy resources

Postprint (author's final draft

Profitability analysis on demand-side flexibility: A review

Flexibility has emerged as an optimal solution to the increasing uncertainty in power systems produced by the continuous development and penetration of distributed generation based on renewable energy. Many studies have shown the benefits for system operators and stakeholders of diverse ancillary services derived from demand-side flexibility. Cost-benefit analysis on these flexibility services should be carried out to determine the profitable applications, as well as the required adjustments on energy market, price schemes and normative framework to maximize the positive impacts of the available flexibility. This paper endeavors to review the main topics, variables and indexes related to the profitability analysis on demand-side flexibility, as well as the influence of energy markets, pricing and standards on revenue maximization. The conclusions drawn from this review demonstrate that the profitability of flexibility services considerably de-pends on energy market structure, involved assets, electricity prices and current ancillary services remuneration.Peer ReviewedPostprint (published version