A comprehensive review on electric vehicles smart charging: solutions, strategies, technologies, and challenges

The role of electric vehicles (EVs) in energy systems will be crucial over the upcoming years due to their environmental-friendly nature and ability to mitigate/absorb excess power from renewable energy sources. Currently, a significant focus is given to EV smart charging (EVSC) solutions by researchers and industries around the globe to suitably meet the EVs' charging demand while overcoming their negative impacts on the power grid. Therefore, effective EVSC strategies and technologies are required to address such challenges. This review paper outlines the benefits and challenges of the EVSC procedure from different points of view. The role of EV aggregator in EVSC, charging methods and objectives, and required infrastructure for implementing EVSC are discussed. The study also deals with ancillary services provided by EVSC and EVs' load forecasting approaches. Moreover, the EVSC integrated energy systems, including homes, buildings, integrated energy systems, etc., are reviewed, followed by the smart green charging solutions to enhance the environmental benefit of EVs. The literature review shows the efficiency of EVSC in reducing charging costs by 30 %, grid operational costs by 10 %, and renewable curtailment by 40 %. The study gives key findings and recommendations which can be helpful for researchers and policymakers

Optimal Management of community Demand Response

More than one-third of the electricity produced globally is consumed by the residential sectors [1], with nearly 17% of CO2 emissions, are coming from residential buildings according to reports from 2018 [2] [3]. In order to cope with increase in electricity demand and consumption, while considering the environmental impacts, electricity providers are seeking to implement solutions to help them balance the supply with the electricity demand while mitigating emissions. Thus, increasing the number of conventional generation units and using unreliable renewable source of energy is not a viable investment. That’s why, in recent years research attention has shifted to demand side solutions [4]. This research investigates the optimal management for an urban residential community, that can help in reducing energy consumption and peak and CO2 emissions. This will help to put an agreement with the grid operator for an agreed load shape, for efficient demand response (DR) program implementation. This work uses a framework known as CityLearn [2]. It is based on a Machine Learning branch known as Reinforcement Learning (RL), and it is used to test a variety of intelligent agents for optimizing building load consumption and load shape. The RL agent is used for controlling hot water and chilled water storages, as well as the battery system. When compared to the regular building usage, the results demonstrate that utilizing an RL agent for storage system control can be helpful, as the electricity consumption is greatly reduced when it’s compared to the normal building consumption

Estado del arte de la gestión de la energía eléctrica desde el lado de la demanda

El agotamiento de los recursos naturales y la dependencia a vectores energéticos importados ha generado varias crisis energéticas a lo largo de siglo XX, las cuales se han extendido a hasta nuestros días. Por otro lado, los efectos nocivos de los gases de efecto invernadero en el clima global han generado una crisis climática tal, que todos los países están comprometidos a mitigar. La comunidad internacional sugiere un cambio de enfoque en la explotación energética, ven necesario pasar del consumismo a la conservación. Es así como la gestión energética mundial inicia su innovación, conceptos como desarrollo sostenible, transformación digital o economía circular irrumpen en la escena de la prestación de servicios. Este nuevo paradigma ya no admite una gestión centralizada, sino una distribuida, y la gestión de la energía eléctrica desde el lado de la demanda engloba todos estos conceptos novedosos y los aplica en la explotación de la red eléctrica. A pesar que la gestión de la demanda eléctrica (GDE) data desde 1975, su desarrollo e implantación en la estructura del sistema eléctrico empieza a tomar relevancia global en la segunda década de este siglo, esto a causa de la mejora de la infraestructura tecnológica disponible. La hipótesis general de la investigación radica en la idea de que la demanda se comporta de forma elástica a las variaciones de precio, y esto permite gestionarla. Por otro lado, con la finalidad de determinar el estado del arte de la GDE se realizó un barrido de información desde sus orígenes hasta la actualidad, esto permitió determinar los puntos de interés y a partir de estos, profundizar en el tema investigado. Hasta inicios de este siglo, Estados Unidos era el principal consumidor de recursos energéticos, y el único que había desarrollado estrategias de GDE en la operación de su sistema eléctrico. Hoy por hoy, de sus experiencias se obtiene que los programas de conservación energética sirven para reducir la energía total consumida mientras que los programas de respuesta de la demanda sirven para reducir los picos de demanda. Además, mediante los dispositivos tecnológicos que necesita la GDE para operar, se puede integrar tecnologías que aportan a la flexibilidad de la demanda como la generación distribuida y el almacenamiento energético. En la actualidad, la respuesta de la demanda (RD) se destaca de los otros programas de GDE debido a que tiene una amplia gama de oportunidades de negocio disponible. Además, el carácter dinámico de la demanda necesita una estrategia de control permanente la cual se dificulta sin un proceso automatizado. La comunidad científica se ha abocado al desarrollo de algoritmos que permitan la automatización de la respuesta de la demanda, en especial han tomado relevancia los algoritmos basados en inteligencia artificial ya que permiten la integración directa del cliente y del mercado. En la actualidad, tanto Estados Unidos y China avanzan consistentemente en la implantación de programas de GDE. La Unión Europea, a pesar de ser el tercer mayor consumidor energético del mundo, y que el 67% de esos recursos energéticos provienen del extranjero, aún no ha consolidado una política clara sobre cómo implementar estos programas en la operación de sus redes eléctricas. Y es que la GDE no es solo una forma de reducirla o mejorar la eficiencia de la red, la GDE es un sofisticado proceso tecnológico que incluye un marco legal claro, financiamiento para modernizar la red e investigación que ahonde sobre las costumbres y preferencias del cliente, y cómo estás inciden en su consumo energético.The depletion of natural resources and dependence on imported energy carriers has generated several energy crises throughout the 20th century, which have extended to the present day. On the other hand, the harmful effects of greenhouse gases on the global climate have generated an environmental crisis that all countries are committed to mitigate. The international community suggests a change of approach in energy exploitation; they see the need to move from consumerism to conservation. This is how global energy management begins its innovation, concepts such as sustainable development, digital transformation or circular economy burst onto the scene of service provision. This new paradigm no longer allows for centralized but distributed management, and demand-side power management encompasses all these new concepts and applies them to the operation of the electricity grid. Although demand side management (DSM) dates back to 1975, its development and implementation in the structure of the electricity system began to take on global relevance in the second decade of this century, due to the improvement of the available technological infrastructure. The general hypothesis of the research lies in the idea that demand behaves elastically to price variations, and this allows it to be managed. On the other hand, in order to determine the state of the art of DSM, a sweep of information was carried out from its origins to the present day, which made it possible to determine the points of interest and, based on these, to delve deeper into the topic under investigation. Until the beginning of this century, the United States was the main consumer of energy resources and the only country that had developed strategies for DSM in the operation of its electricity system. Today, from its experiences, energy conservation programs serve to reduce the total energy consumed while demand response programs serve to reduce peak demand. In addition, through the technological devices that the DSM needs to operate, it is possible to integrate technologies that contribute to demand flexibility such as distributed generation and energy storage. Currently, demand response (DR) stands out from other DSG programs because it has a wide range of business opportunities available. In addition, the dynamic nature of demand requires a permanent control strategy which is difficult without an automated process. The scientific community has focused on the development of algorithms that allow the automation of demand response; especially algorithms based on artificial intelligence have gained relevance as they allow direct integration of the customer and the market. Currently, both the United States and China are making consistent progress in the implementation of DSM programs. The European Union, despite being the third largest energy consumer in the world, with 67% of its energy resources coming from abroad, has not yet consolidated a clear policy on how to implement these programs in the operation of its electricity grids. Because DSM is not just a way to reduce or improve grid efficiency, DSM is a sophisticated technological process that includes a clear legal framework, funding to modernize the grid, and research that delves into customer habits and preferences and how they affect their energy consumption.Universidad de Sevilla. Máster en Sistemas de Energía Eléctric