Decision support for participation in electricity markets considering the transaction of services and electricity at the local level

[EN] The growing concerns regarding the lack of fossil fuels, their costs, and their impact on the environment have led governmental institutions to launch energy policies that promote the increasing installation of technologies that use renewable energy sources to generate energy. The increasing penetration of renewable energy sources brings a great fluctuation on the generation side, which strongly affects the power and energy system management. The control of this system is moving from hierarchical and central to a smart and distributed approach. The system operators are nowadays starting to consider the final end users (consumers and prosumers) as a part of the solution in power system operation activities. In this sense, the end-users are changing their behavior from passive to active players. The role of aggregators is essential in order to empower the end-users, also contributing to those behavior changes. Although in several countries aggregators are legally recognized as an entity of the power and energy system, its role being mainly centered on representing end-users in wholesale market participation. This work contributes to the advancement of the state-of-the-art with models that enable the active involvement of the end-users in electricity markets in order to become key participants in the management of power and energy systems. Aggregators are expected to play an essential role in these models, making the connection between the residential end-users, electricity markets, and network operators. Thus, this work focuses on providing solutions to a wide variety of challenges faced by aggregators. The main results of this work include the developed models to enable consumers and prosumers participation in electricity markets and power and energy systems management. The proposed decision support models consider demand-side management applications, local electricity market models, electricity portfolio management, and local ancillary services. The proposed models are validated through case studies based on real data. The used scenarios allow a comprehensive validation of the models from different perspectives, namely end-users, aggregators, and network operators. The considered case studies were carefully selected to demonstrate the characteristics of each model, and to demonstrate how each of them contributes to answering the research questions defined to this work.[ES] La creciente preocupación por la escasez de combustibles fósiles, sus costos y su impacto en el medio ambiente ha llevado a las instituciones gubernamentales a lanzar políticas energéticas que promuevan la creciente instalación de tecnologías que utilizan fuentes de energía renovables para generar energía. La creciente penetración de las fuentes de energía renovable trae consigo una gran fluctuación en el lado de la generación, lo que afecta fuertemente la gestión del sistema de potencia y energía. El control de este sistema está pasando de un enfoque jerárquico y central a un enfoque inteligente y distribuido. Actualmente, los operadores del sistema están comenzando a considerar a los usuarios finales (consumidores y prosumidores) como parte de la solución en las actividades de operación del sistema eléctrico. En este sentido, los usuarios finales están cambiando su comportamiento de jugadores pasivos a jugadores activos. El papel de los agregadores es esencial para empoderar a los usuarios finales, contribuyendo también a esos cambios de comportamiento. Aunque en varios países los agregadores están legalmente reconocidos como una entidad del sistema eléctrico y energético, su papel se centra principalmente en representar a los usuarios finales en la participación del mercado mayorista. Este trabajo contribuye al avance del estado del arte con modelos que permiten la participación activa de los usuarios finales en los mercados eléctricos para convertirse en participantes clave en la gestión de los sistemas de potencia y energía. Se espera que los agregadores desempeñen un papel esencial en estos modelos, haciendo la conexión entre los usuarios finales residenciales, los mercados de electricidad y los operadores de red. Por lo tanto, este trabajo se enfoca en brindar soluciones a una amplia variedad de desafíos que enfrentan los agregadores. Los principales resultados de este trabajo incluyen los modelos desarrollados para permitir la participación de los consumidores y prosumidores en los mercados eléctricos y la gestión de los sistemas de potencia y energía. Los modelos de soporte de decisiones propuestos consideran aplicaciones de gestión del lado de la demanda, modelos de mercado eléctrico local, gestión de cartera de electricidad y servicios auxiliares locales. Los modelos propuestos son validan mediante estudios de casos basados en datos reales. Los escenarios utilizados permiten una validación integral de los modelos desde diferentes perspectivas, a saber, usuarios finales, agregadores y operadores de red. Los casos de estudio considerados fueron cuidadosamente seleccionados para demostrar las características de cada modelo y demostrar cómo cada uno de ellos contribuye a responder las preguntas de investigación definidas para este trabajo

Hybrid particle swarm optimization of electricity market participation portfolio

This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of optimal participation in multiple electricity markets. The decision time is usually very important when planning the participation in electricity markets. This environment is characterized by the time available to take action, since different electricity markets have specific rules, which requires participants to be able to adapt and plan their decisions in a short time. Using metaheuristic optimization, participants' time problems can be resolved, because these methods enable problems to be solved in a short time and with good results. This paper proposes a hybrid resolution method, which is based on the particle swarm optimization metaheuristic. An exact mathematical method, which solves a simplified, linearized, version of the problem, is used to generate the initial solution for the metaheuristic approach, with the objective of improving the quality of results without representing a significant increase of the execution time.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 703689 (project ADAPT) and No 641794 (project DREAM-GO); NetEfficity Project (P2020 − 18015); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE pro-gram and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Case-based reasoning using expert systems to determine electricity reduction in residential buildings

Case-based reasoning enables solving new problems using past experience, by reusing solutions for past problems. The simplicity of this technique has made it very popular in several domains. However, the use of this type of approach to support decisions in the power and energy domain is still rather unexplored, especially regarding the flexibility of consumption in buildings in response to recent environmental concerns and consequent governmental policies that envisage the increase of energy efficiency. In order to determine the amount of consumption reduction that should be applied in a building, this article proposes a methodology that adapts the past results of similar cases in order to achieve a decision for the new case. A clustering methodology is used to identify the most similar previous cases, and an expert system is developed to refine the final solution after the combination of the similar cases results. The proposed CBR methodology is evaluated using a set of real data from a residential building. Results prove the advantages of the proposed methodology, demonstrating its applicability to enhance house energy management systems by determining the amount of reduction that should be applied in each moment, thus allowing such systems to carry out the reduction through the different loads of the building.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and a grant agreement No 703689 (project ADAPT); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013info:eu-repo/semantics/publishedVersio

Prosumer Community Portfolio Optimization via Aggregator: The Case of the Iberian Electricity Market and Portuguese Retail Market

The participation of household prosumers in wholesale electricity markets is very limited, considering the minimum participation limit imposed by most market participation rules. The generation capacity of households has been increasing since the installation of distributed generation from renewable sources in their facilities brings advantages for themselves and the system. Due to the growth of self-consumption, network operators have been putting aside the purchase of electricity from households, and there has been a reduction in the price of these transactions. This paper proposes an innovative model that uses the aggregation of households to reach the minimum limits of electricity volume needed to participate in the wholesale market. In this way, the Aggregator represents the community of households in market sales and purchases. An electricity transactions portfolio optimization model is proposed to enable the Aggregator reaching the decisions on which markets to participate to maximize the market negotiation outcomes, considering the day-ahead market, intra-day market, and retail market. A case study is presented, considering the Iberian wholesale electricity market and the Portuguese retail market. A community of 50 prosumers equipped with photovoltaic generators and individual storage systems is used to carry out the experiments. A cost reduction of 6–11% is achieved when the community of households buys and sells electricity in the wholesale market through the AggregatorThis work has received funding from the European Union's Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276) and from FEDER Funds through COMPETE program and from National Funds through FCT under projects CEECIND/01811/2017 and UID/EEA/00760/2019info:eu-repo/semantics/publishedVersio

Otimização de Portfólio de Participação em Mercados de Energia Elétrica

Na atualidade são visíveis as mudanças ocorridas nos mercados de energia elétrica, em consequência da introdução maciça de energia proveniente de fontes renováveis. Pelo facto de serem renováveis são de grande interesse para a população, pois o custo de produção e as emissões de gases, que contribuem para o efeito de estufa durante o seu funcionamento, são nulas. Estas características são essenciais para as mais altas chefias das instituições europeias, que impuseram políticas para promover a utilização e instalação de tecnologia para o aproveitamento das fontes que facultam as energias renováveis. Os estados membros europeus mostraram-se recetíveis a estas políticas e incentivaram o investimento nestas tecnologias. Deste modo, houve uma enorme introdução de energias de arater intermitente e instável que condicionaram o normal funcionamento dos sistemas de energia elétrica, o que, por sua vez, conduziu a inúmeras mudanças no setor. Esta reestruturação teve impacto em todo o setor, como é o caso dos mercados de energia elétrica, onde surgiram novas formas de negociação e foram criadas novas entidades de mercado. Com estas alterações, a complexidade dos mercados de energia elétrica aumentou, assim como a imprevisibilidade dos mesmos. Por isso, tornou-se essencial a existência de formas de apoio que auxilie a tomada de decisão por parte das entidades de mercado. Com a emergência de todas estas exigências, tornou-se fundamental o desenvolvimento de ferramentas para auxílio na tomada de decisão. Estas ferramentas ajudam as diversas entidades a perceber o funcionamento dos mercados e prever as interações que ocorrerão entre as diferentes entidades existentes no mercado. A inteligência artificial teve um papel crucial no desenvolvimento destas ferramentas, nomeadamente os sistemas multiagente, que têm sido uma solução muito explorada pelos interessados no setor. Estes, utilizam várias técnicas da inteligência artificial, o que lhes permite serem adaptativos a diferentes situações, simular os diferentes agentes existentes no mercado, permitir diversos tipos de negociação, e ainda aprender ao longo da sua utilização. No entanto, apesar de estas ferramentas atualmente estarem voltadas para o estudo do funcionamento do sistema elétrico, deixam de lado o contexto de negociação e descartam o apoio às decisões do vendedor/comprador de eletricidade. O largo âmbito de aplicação da inteligência artificial fornece diversas experiências, nomeadamente ferramentas de otimização meta-heurísticas, que permitem a resolução de problemas num curto espaço de tempo, e com uma qualidade de resultados muito próxima daquela alcançada por técnicas determinísticas à custa de um elevado tempo de execução. O trabalho desenvolvido nesta dissertação tem como objeto de estudo a falha supra referenciada. Sugere uma metodologia de negociação da energia elétrica que permite vender e comprar a mesma em diferentes mercados com regras específicas, e indica um portfólio de participação nos vários mercados em que cada interveniente pode negociar. A metodologia apresentada permite gerar cenários realistas a partir do resultado da otimização do portfólio, que podem ser tomados em consideração na decisão dos intervenientes de mercado, e assim conseguirem retirar o máximo proveito das suas negociações. Os resultados apresentados foram obtidos através da utilização de dados reais provenientes dos diferentes operadores de mercados. Estes dados são válidos para a formulação de diferentes cenários que possam ser considerados no ato da negociação.Nowadays, there are several relevant changes in electricity markets, which are a consequence of the massive introduction of renewable energies. The fact that they are renewable is of great interest for all of us, because the cost of production of this energy is null and emissions of greenhouse gases are also zero during operation. This feature aroused great interest in the high European institutions that have imposed policies to promote the use and installation of technology for the use of sources that provide renewable energy. European member states have shown receptiveness to these policies, potentiating the investment in these technologies and thus hearing a great introduction of intermittent and unstable energy that conditioned the normal operation of power systems and led to further inevitable changes in an already under-restructuring power and energy sector. This restructuring had an impact throughout the industry, as is the case of the electricity markets, where new forms of trading emerged and new market entities were created. With these changes the complexity of electricity markets increased as well as the associated unpredictability. This made is essential to have support tools to aid decision making by the arket entities. With the emergence of all these requirements it is fundamental to develop tools in order to assist the decision-making process, and to help understanding the functioning of markets and predict the interactions that occur between the existing market entities. Artificial intelligence has an important role in the development of these tools. Multi-agent systems, in particular, have been much explored by stakeholders in the sector as a valid solution. They use various techniques of artificial intelligence that allows them to be adaptive to any situation, to simulate the different existing players in the market, allowing any type of trading and enabling them to learn the logo of its use. However, these tools are directed to study of the proper functioning of the electrical system, leaving aside the negotiation context and the decision support for the seller / buyer of electricity. The applicability of artificial intelligence is not limited to electricity markets. It is also applied in many other areas due to its optimization tools that enable solving problems in a short time and with very similar results to those achieved by deterministic techniques, at the cost of a high execution time. The work in this dissertation addresses the above-mentioned gaps, and suggests an electricity trading decision support methodology to buy and sell electricity in different markets with specific rules. This is done by suggesting a portfolio of market participation that each party can perform. The presented methodology generates realistic scenarios from the portfolio optimization of the results that may be taken into account in the decision of market participants; and allow these players to take full advantage of it. The results were obtained through the use of real data stemmed from different market operators, which are valid for the generation of different scenarios that can be taken into account in the negotiation act

A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem

Energy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.This research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC), CEECIND/02814/2017, and UIDB/000760/2020. Ricardo Faia has received support under the Ph.D. grant SFRH/BD/133086/2017 and COVID/BD/152167/2021 from National Funds through (FCT).info:eu-repo/semantics/publishedVersio

A New Hybrid-Adaptive Differential Evolution for a Smart Grid Application Under Uncertainty

Power systems are showing a dynamic evolution in the last few years, caused in part by the adoption of smart grid technologies. The integration of new elements that represent a source of uncertainty, such as renewables generation, electric vehicles, variable loads and electricity markets, poses a higher degree of complexity causing that traditional mathematical formulations struggle in finding efficient solutions to problems in the smart grid context. In some situations, where traditional approaches fail, computational intelligence has demonstrated being a very powerful tool for solving optimization problems. In this paper, we analyze the application of Differential Evolution (DE) to address an energy resource management problem under uncertain environments. We perform a systematic parameter tuning to determine the best set of parameters of four state-of-the-art DE strategies. Having knowledge of the sensitivity of DE to the parameter selection, self-adaptive parameter control DE algorithms are also implemented, showing that competitive results can be achieved without the application of parameter tuning methodologies. Finally, a new hybrid-adaptive DE algorithm, HyDE, which uses a new “DE/target - to - perturbed_best/1” strategy and an adaptive control parameter mechanism, is proposed to solve the problem. Results show that DE strategies with fixed parameters, despite very sensitive to the setting, can find better solutions than some adaptive DE versions. Overall, our HyDE algorithm excelled all the other tested algorithms, proving its effectiveness solving a smart grid application under uncertainty.his work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013info:eu-repo/semantics/publishedVersio

Dynamic Fuzzy Clustering Method for Decision Support in Electricity Markets Negotiation

Artificial Intelligence (AI) methods contribute to the construction of systems where there is a need to automate the tasks. They are typically used for problems that have a large response time, or when a mathematical method cannot be used to solve the problem. However, the application of AI brings an added complexity to the development of such applications. AI has been frequently applied in the power systems field, namely in Electricity Markets (EM). In this area, AI applications are essentially used to forecast / estimate the prices of electricity or to search for the best opportunity to sell the product. This paper proposes a clustering methodology that is combined with fuzzy logic in order to perform the estimation of EM prices. The proposed method is based on the application of a clustering methodology that groups historic energy contracts according to their prices’ similarity. The optimal number of groups is automatically calculated taking into account the preference for the balance between the estimation error and the number of groups. The centroids of each cluster are used to define a dynamic fuzzy variable that approximates the tendency of contracts’ history. The resulting fuzzy variable allows estimating expected prices for contracts instantaneously and approximating missing values in the historic contracts.info:eu-repo/semantics/publishedVersio

Uma entidade subvalorizada? Estudo retrospetivo realizado no CHUCB

Introdução: As doenças cardiovasculares estão na linha da frente da morbi-mortalidade em Portugal, sendo responsáveis por um grande número de mortes e incapacidades. Dentro deste espectro, encontramos a Hipertensão Arterial como um dos maiores fatores risco para entidades como o AVC, o Enfarte Agudo do Miocárdio, a Insuficiência Cardíaca e a Doença Renal Crónica. De acordo com o estudo PHYSA, levado a cabo pela Sociedade Portuguesa de Hipertensão, a prevalência de HTA ronda os 42,2% na população adulta do nosso País e, para além disso, a maioria dos doentes hipertensos (57,4%) mantém a HTA não controlada. Como podemos averiguar, apesar das armas farmacológicas existentes no tratamento da HTA, grande parte desta população não é tratada ou é tratada de forma inadequada. Dado o peso desta entidade, não só em Portugal, como em todo o mundo, reforça-se a necessidade de uma identificação e gestão precoce desta doença. Nesta medida, o serviço de urgência recebe a importância acrescida de local de rastreio e envio para seguimento, quer nos casos sem história prévia de HTA, bem como aqueles que apresentam HTA não controlada. De facto, o Colégio Americano de Médicos de Emergência (ACEP) enfatiza a importância do follow-up para todos os pacientes que entrem na urgência com valores de pressão arterial superiores a 140/90 mmHg. No entanto, muitos dos estudos que se debruçam nesta temática demonstram uma realidade contrária, na qual a pressão arterial elevada é negligenciada no serviço de urgência, realçando a necessidade de dar maior enfoque a todos estes casos neste local. Objetivos: Determinar de que forma é gerida a pressão arterial elevada dos indivíduos que se deslocam ao Serviço de Urgência do Centro Hospitalar Universitário Cova da Beira. Determinar se é efetuado follow-up aos indivíduos que se deslocam ao SU com valores de pressão arterial elevada. Métodos: Estudo retrospetivo, onde são incluídas todas as pessoas que se deslocaram ao Serviço de Urgência do Centro Hospitalar Cova da Beira, no período de tempo de 1 de Maio de 2018 a 31 de Maio do mesmo ano, apresentando valores de pressão arterial sistólica =140 mmHg e/ou valores de pressão arterial diastólica =90 mmHg. Dentro desta população procuramos verificar como é feita a gestão destes pacientes, em termos médicos e farmacológicos. São excluídos, utentes com idade inferior a 18 anos, grávidas, indivíduos que deram entrada no SU por traumatismo, doentes sem história clínica, doentes que tenham abandonado o SU antecipadamente. Resultados: Das 1202 entradas no SU no período de tempo descrito, nas quais foi aferida a pressão arterial, apenas 340 foram selecionados, por apresentarem valores consistentes com Hipertensão Arterial, bem como não apresentarem demais critérios de exclusão. Pudemos constatar que grande parte destes episódios correspondem a pessoas de faixas etárias mais avançadas e, para além disso, pertencem ligeiramente mais ao sexo feminino. Perante o episódio de pressão arterial elevada, constatamos que em apenas 77 (22,7%) dessas ocorrências existiu aconselhamento médico para follow-up dos valores tensionais. Esta atitude apresentou uma frequência semelhante ao longo dos três graus de hipertensão arterial e não foi afetada por fatores como o sexo e a idade. Finalmente, verificou-se que em 134 (39.4%) ocorrências se optou por realizar algum tipo de medicação anti-hipertensiva ou ansiolítica. Dentro das diferentes opções farmacológicas, destacam-se o uso dos IECAs (38,7%), dos ansiolíticos (38,6%), e dos diuréticos de ansa (35,5%). Conclusão: Os dados recolhidos levam-nos a concluir que existe um seguimento incorreto num número substancial de episódios, onde encontramos doentes que se apresentam no SU com valores tensionais elevados. O número significativo de medicação ansiolítica fornecida no SU a esta população leva-nos a supor que tais ocorrências poderão ser justificadas por fatores como, a ansiedade decorrente do ambiente do serviço de urgência. Comparativamente, a investigações com um objetivo semelhante, encontramos resultados mais positivos. Mais esforços deverão ser feito para o reconhecimento e seguimentos destes indivíduos, permitindo uma intervenção mais precoce ou uma otimização terapêutica, caso já padeçam de hipertensão arterial.Introduction: Cardiovascular diseases are at the forefront of morbidity and mortality in Portugal, accounting for a large number of deaths and disabilities. Within this spectrum, we find Arterial Hypertension as one of the major risk factors for entities such as stroke, acute myocardial infarction, heart failure and chronic renal disease. According to the PHYSA study carried out by the Portuguese Society of Hypertension, the prevalence of hypertension is around 42.2% in the adult population of our country and, in addition, the majority of hypertensive patients (57.4% %) maintains blood pressure uncontrolled. As we can see, despite the pharmacological weapons that exist in the treatment of hypertension, much of this population is not treated or treated improperly. Given the weight of this entity, not only in Portugal, but also throughout the world, the need for an early identification and management of this disease is reinforced. To this extent, the emergency department receives an increased importance as the site of screening and referral for follow-up, both in cases without previous history of hypertension, as well as those with uncontrolled hypertension. In fact, the American College of Emergency Physicians emphasizes the importance of follow-up for all patients who enter the emergency department with blood pressure values above 140/90 mmHg. However, many of the studies that address this issue demonstrate a contrary reality, in which high blood pressure is neglected in the emergency department, emphasizing the need to focus all these cases in this setting. Objectives: To determine how high blood pressure is managed in individuals who travel to the emergency department of Cova da Beira University Hospital Center. To determine if follow-up is performed on individuals who move to the US with high blood pressure values. Methods: Retrospective study, which included all the people who went to the Emergency Department of the Cova da Beira University Hospital Center, from May 1 2018 to May 31 of the same year, presenting systolic blood pressure values =140 mmHg and/or diastolic blood pressure values =90 mmHg. Within this population we seek to verify how these patients are managed, in medical and pharmacological terms. Patients younger than 18 years of age, pregnant women, individuals who entered the ED due to trauma, patients without a medical history, and patients who abandoned the ED in advance are excluded. Results: Of the 1202 entries in the ED during the time period described, in which blood pressure was measured, only 340 were selected because they presented values consistent with arterial hypertension, as well as no other exclusion criteria. We can see that most of these episodes correspond to people of more advanced age and, moreover, belong slightly more to the female sex. Faced with the episode of high blood pressure, we found that in only 77 (22.7%) of these occurrences there was medical advice for follow-up of blood pressure values. This attitude showed a similar frequency over the three degrees of hypertension and wasn’t affected by factors such as gender or age. Finally, it was verified that in 134 (39.4%) occurrences was opted to perform some type of antihypertensive or anxiolytic medication. Among the different pharmacological options, the use of ACE inhibitors (38.7%), anxiolytics (38.6%), and loop diuretics (35.5%) were the most important. Conclusion: The data collected lead us to conclude that there is an incorrect follow-up in a substantial number of episodes, where we find patients presenting in the ED with high blood pressure values. The significant number of anxiolytic medication given in the ED to this population leads us to suppose that such occurrences may be justified by factors such as anxiety arising from the emergency room environment. Comparatively, to investigations with a similar objective, we find more positive results. Further efforts should be made for the recognition and follow-up of these individuals, allowing for an earlier intervention or a therapeutic optimization if they already suffer from hypertension

Local Electricity Markets for Electric Vehicles: An Application Study Using a Decentralized Iterative Approach

Local electricity markets are emerging solutions to enable local energy trade for the end users and provide grid support services when required. Various models of local electricity markets (LEMs) have been proposed in the literature. The peer-to-peer market model appears as a promising structure among the proposed models. The peer-to-peer market structure enables electricity transactions between the players in a local energy system at a lower cost. It promotes the production from the small low–carbon generation technologies. Energy communities can be the ideal place to implement local electricity markets as they are designed to allow for larger growth of renewable energy and electric vehicles, while benefiting from local transactions. In this context, a LEM model is proposed considering an energy community with high penetration of electric vehicles in which prosumer-to-vehicle (P2V) transactions are possible. Each member of the energy community can buy electricity from the retailer or other members and sell electricity. The problem is modeled as a mixed-integer linear programing (MILP) formulation and solved within a decentralized and iterative process. The decentralized implementation provides acceptable solutions with a reasonable execution time, while the centralized implementation usually gives an optimal solution at the expense of reduced scalability. Preliminary results indicate that there are advantages for EVs as participants of the LEM, and the proposed implementation ensures an optimal solution in an acceptable execution time. Moreover, P2V transactions benefit the local distribution grid and the energy community