Differential Evolution Aplication in Portfolio optimization for Electricity Markets

Smart Grid technologies enable the intelligent integration and management of distributed energy resources. Also, the advanced communication and control capabilities in smart grids facilitate the active participation of aggregators at different levels in the available electricity markets. The portfolio optimization problem consists in finding the optimal bid allocation in the different available markets. In this scenario, the aggregator should be able to provide a solution within a timeframe. Therefore, the application of metaheuristic approaches is justified, since they have proven to be an effective tool to provide near-optimal solutions in acceptable execution times. Among the vast variety of metaheuristics available in the literature, Differential Evolution (DE) is arguably one of the most popular and successful evolutionary algorithms due to its simplicity and effectiveness. In this paper, the use of DE is analyzed for solving the portfolio optimization problem in electricity markets. Moreover, the performance of DE is compared with another powerful metaheuristic, the Particle Swarm optimization (PSO), showing that despite both algorithms provide good results for the problem, DE overcomes PSO in terms of quality of the solutions.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 from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013 and grant agreement No 703689 (project ADAPT);info:eu-repo/semantics/publishedVersio

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

Otimização dos custos operacionais de uma comunidade energética considerando transações locais em “peer-to-peer”

A proliferação dos recursos energéticos distribuídos, aliada ao desenvolvimento das tecnologias de informação e comunicação, são fatores preponderantes para o desenvolvimento dos mercados locais de eletricidade. Neste tipo mercados, os participantes possuem um papel mais ativo, em comparação com o mercado grossista tradicional de eletricidade. Este trabalho foca-se no estudo dos mercados locais de eletricidade através de uma revisão bibliográfica sobre vários conceitos e mecanismos usados para este tipo de mercados. Para tal, o presente trabalho propõe um modelo de otimização que considera a minimização dos custos com a aquisição de eletricidade de uma comunidade considerando transações em peer-to-peer. Por forma a obter a solução do problema são utilizadas meta-heurísticas, para minimizar os custos energéticos dentro da comunidade considerando todas as transações de eletricidade possíveis. Para isso, o trabalho inclui um exemplo prático, considerando uma comunidade energética composta por 10 consumidores, 10 prosumers e 10 produtores. Adicionalmente, num dos cenários analisados no caso de estudo, considera-se ainda a existência de 2 produtores termoelétricos. Para este caso de estudo, recorreu-se ao uso de várias meta-heurísticas com o propósito de encontrar a melhor combinação de negociações peer-to-peer de forma a ser possível fazer uma comparação entre a possibilidade de existência do mercado local e a atual estrutura de mercado existente. Os resultados deste caso de estudo mostram não só uma redução nos custos energéticos da comunidade, mas também um aumento das receitas quando se considera a existência do mercado local com negociações peer-to-peer.The proliferation of distributed energy resources, along with the development of information and communication technologies, are key factors for developing local electricity markets. Participants play a more active role in this market than in the traditional wholesale electricity market. This work focuses on studying local electricity markets through a literature review of various concepts and mechanisms used for this type of market. In this sense, the present work proposes an optimization model that considers minimizing costs with the acquisition of electricity from a community considering peer-to-peer transactions. In order to obtain a solution to the problem, meta-heuristics are used, minimizing energy costs within the community, and considering all possible electricity transactions. For this, the work includes a practical example, considering an energy community composed of 10 consumers, 10 prosumers, and 10 producers. Additionally, in one of the scenarios analyzed in the case study, the existence of 2 thermoelectric generators is also considered. This case study proposed the use of several meta-heuristics to find the best combination of peer-to-peer negotiations in order to make a comparison between the use of a local market and the currently existing market structures. The results of this case study show not only a reduction in the energy costs of the community but also an increase in revenues when considering the existence of the local market with peer-to-peer negotiations

Renewable and Sustainable Energy: Current State and Prospects

The renewable energy sector is one of the fastest growing branches of the economy in the world, including in Poland. Extensive investigation in research centers results in the increased efficiency of obtaining energy from renewable sources, as well as a decrease in the prices of renewable energy installations. The development of renewable energy motivates further research and the development of new technologies. Investments in renewable energy may also benefit the local community by increasing the attractiveness of the region to tourists, creating opportunities for professional activation (especially in areas with high unemployment), increasing the competitiveness of the local economy and its energy efficiency and obtaining raw materials from local producers, mainly farmers, which are an additional source of income for them. Another possible economic advantage is charging lease fees, for instance, for land under wind turbines or fees for ground easement, in order to ensure access to the construction of power lines, e.g., connecting turbines to the grid; lowering heat prices for residents of a given town; building investment plots in or near heat plants and biogas plants, with the provision of heat and electricity at competitive prices directly from these plants; investors covering the costs of modernizing local roads; and creating new transmission, power lines and supply points

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

Nuevas estrategias de planificación de la producción en plantas termosolares con almacenamiento térmico

En respuesta a los problemas energéticos actuales, la generación eléctrica basada en energía renovable intermitente, como la energía solar y eólica, ha crecido significativamente durante los últimos años gracias a la disminución de costes. Este tipo de generación presenta un carácter intermitente, variable y de difícil predicción, lo que dificulta su integración en la red eléctrica. Sin embargo, la energía termosolar posee ciertas características que pueden compensar en parte las desventajas anteriores. Esta tecnología captura la radiación solar en forma de energía térmica por medio del calentamiento de un fluido, para más tarde convertirla en electricidad.Por el hecho de emplear energía térmica como forma de energía intermedia, se complementa muy bien con sistemas de almacenamientotérmico. Gracias a este almacenamientoenergético, este tipo de plantas presenta cierto grado de gestionabilidad, existiendo la posibilidad de regular la producción. Esta propiedad favorece su participación en el mercado eléctrico, donde el objetivo del productor de electricidad es maximizar los beneficios económicos derivados de la venta de electricidad. Este objetivo puede lograrse cuando se planifica la producción en función del perfil de precios de venta de la electricidad. Puede plantear se, por tanto, un problema de planificación óptima de la producción. Considerando sólo el mercado diario de la electricidad, la resolución de este problema de optimización permite obtener el plan diario de generación, que debe enviarse al mercado normalmente el día anterior. Se deduce de lo anterior que en el caso de plantas renovables, además de la necesidad de disponer de una predicción de los precios de la electricidad, se requiere una prediccióndel recurso natural para poder abordar el problema. Los objetivos principales de esta Tesis son el diseño de nuevas estrategias de planificaciónóptima de la producción para una planta termosolar con almacenamiento térmico, y el estudio mediante simulación del rendimiento económico de cada estrategia cuando se considera la participación de la planta en el mercado diario de la electricidad. La planificación óptima se obtiene empleando programación lineal entera mixta, que es la herramienta matemática más usada para resolver este tipo de problemas. La primera estrategia realiza una replanificación horaria de la producción, considerando los ingresos derivados de la venta de electricidad en un determinado horizonte temporal y las posibles penalizaciones por desvíos respecto al plan de generación ya comprometido. Esta estrategia permite introducir en el problema la nueva información disponible cada hora, abordando de esta manera la incertidumbre presente en las predicciones y en el propio modelado del problema. La segunda estrategia incluye un mecanismo que penaliza los cambios en la producción. Además, este mecanismo penaliza de manera diferente las variaciones según el estado del bloque de potencia: operación normal, arranque y parada. De esta manera se consigue aumentar el número de grados de libertad del problema en busca de mejores soluciones. Esta reducción de la variabilidad en la generación tiene como ventajas una extensión en la vida útil de los elementos del bloque de potencia, una reducción de sus costes de mantenimiento y una simplificación de la operación. Se propon e una metodoloqía para estimar el máximo nivel de penalización de las variaciones que no perjudique el rendimiento económico. Finalmente, se desarrolló otra estrategia que combina la replanificación horaria con la penalización de las variaciones. El impacto económico de las estrategias anteriores se ha evaluado mediante simulaciones sobre una planta de 50 MW de tipo cilindro parabólico. Se han empleado datos realistas para elrecurso solar, los precios de la electricidad, los costes de penalización y las predicciones de todos estos datos. Los resultados confirman las mejoras esperadas en cada una de las estrategias.In response to current energy problems, electricity generatiOn based on intermittent renewable energy, such as solar and wind energy, has grown significantly in recent years thanks to the decrease in costs. This type of generation has an intermittent, variable and difficult prediction character, which makes it difficult to integrate into the electricity grid. However, solar thermal energy has certain characteristics that can partially compensate for the above disadvantages. This technology captures solar radiation in the form of thermal energy by heating a fluid, to later convert it into electricity. By using thermal energy as a form of intermediate energy, this technology is complemented very well with thermal energy storage systems. Thanks to this energy storage system, this type of plants has a certain degree of dispatchability, with the possibility of regulating production. This property favors its participation in the electricity market, where the objective of the electricity producer is to maximize the economic benefits derived from the sale of electricity. This objective can be achieved when production is scheduled based on the electricity sales price profile. Therefore, an optimal generation scheduling problem may arise. Considering only theday-ahead energy market, the resolution of this optimization problem allows obtaining the daily generation schedule, which must be sent to the market normally the day befare. It follows from the above that in the case of renewable plants, in addition to the need to have a prediction of electricity prices, a forecast of the natural resource is required to address the problem. The main objectíves of this Thesis are the design of new strategies for optímal generation scheduling applied to a concentrating solar power plant, and the study by simulation of the economic performance of each strategy when considering the participation of the plant in the day-ahead energy market. The optimal generation schedule is obtained using mixed integer linear programming, which is the most used mathematical tool to solve these types of problems. The first strategy performs an hourly rescheduling of the generation, considering the revenues derived from the sale of electricity in a certain time horizon and the possible penalties for deviatíons from the generation schedule already committed. This strategy allows to include into the problem the new information available every hour, thus addressing the uncertainty present in the predictions and in the modeling of the problem itself. The second strategy includes a mechanism that penalizes changes in generation. In addition, this mechanism penalizes variations differently according to the state of the power block: normal operation, startup and shutdown. In this way, it is possible to increase the number of degrees of freedom of the problem in seárch of better solutions. This reduction of the variability in the generation has as advantages an extension in the lifetime of the elements of the power block, a reduction of its maintenance costs andan easier plant operability. A methodology is proposed to estimate the maximum level of penalty for variations that does not affect economic performance. Finally, another strategy was developed that combines hourly rescheduling with the penalization of variations. The economic impact of the above strategies has been evaluated through simulations on a 50 MW parabolic trough collector plant. Realistic data for the solar resource, electricity prices, penalty costs and predictions of all these data have been used. The results confirm the expected improvements in each of the strategies

Current Topics on Risk Analysis: ICRA6 and RISK2015 Conference

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