153 research outputs found

    Market-based Allocation of Local Flexibility in Smart Grids: A Mechanism Design Approach

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    The European electricity market over the last 10 years : Which major changes occurred in the electricity markets, in particular in the electricity production of the European Union, in the past 10 years and what are the implications for the future?

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    Electricity forms the backbone of modern society and is vital for powering industries, fostering innovations and guaranteeing the functioning of essential services and technologies. Throughout the last few decades, the usage of electricity has risen exponentially and is forecasted to grow for the foreseeable future. This underscores the need for functioning electricity markets all around the globe. In the European context, electricity markets have been moving towards integration and the ultimate goal is to create a common European electricity market. This thesis aims to investigate the major changes undergone by European electricity markets over the last 10 years and showcase some of the recent events that have had a major impact on the European electricity markets. Consequently, implications for the future of European electricity markets will be discussed. Both a literature review aimed at evaluating shifts in the overall market design and mechanisms as well an analysis showing the changes in price and electricity production over the last 10 years were performed. Our findings suggest that during the analysed timeframe major changes occurred in the type of electricity produced. The introduction of new market mechanisms such as flow-based market coupling and a trend towards decentralization and utilizing IT technologies to leverage data such as the smart grid have changed the face of the European electricity markets. Major increases in electricity prices, further enforced by the current Russian invasion of Ukraine have moved the focus of market actors towards security of supply and affordability. It is likely that these developments will substantially impact the current market design and the way the EU transitions to a carbon-neutral market. Avenues for further research might include: Research that goes further back in time Evaluating the ideal market design for the European electricity market Performing in-depth regression analysis of price coupling between electricity prices and other variables such as gas prices, ETS prices, …nhhma

    Market Engineering

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    This open access book provides a broad range of insights on market engineering and information management. It covers topics like auctions, stock markets, electricity markets, the sharing economy, information and emotions in markets, smart decision-making in cities and other systems, and methodological approaches to conceptual modeling and taxonomy development. Overall, this book is a source of inspiration for everybody working on the vision of advancing the science of engineering markets and managing information for contributing to a bright, sustainable, digital world. Markets are powerful and extremely efficient mechanisms for coordinating individuals’ and organizations’ behavior in a complex, networked economy. Thus, designing, monitoring, and regulating markets is an essential task of today’s society. This task does not only derive from a purely economic point of view. Leveraging market forces can also help to tackle pressing social and environmental challenges. Moreover, markets process, generate, and reveal information. This information is a production factor and a valuable economic asset. In an increasingly digital world, it is more essential than ever to understand the life cycle of information from its creation and distribution to its use. Both markets and the flow of information should not arbitrarily emerge and develop based on individual, profit-driven actors. Instead, they should be engineered to serve best the whole society’s goals. This motivation drives the research fields of market engineering and information management. With this book, the editors and authors honor Professor Dr. Christof Weinhardt for his enormous and ongoing contribution to market engineering and information management research and practice. It was presented to him on the occasion of his sixtieth birthday in April 2021. Thank you very much, Christof, for so many years of cooperation, support, inspiration, and friendship

    Efficient double auction mechanisms in the energy grid with connected and islanded microgrids

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    Doctor of PhilosophyDepartment of Electrical and Computer EngineeringSanjoy DasThe future energy grid is expected to operate in a decentralized fashion as a network of autonomous microgrids that are coordinated by a Distribution System Operator (DSO), which should allocate energy to them in an efficient manner. Each microgrid operating in either islanded or grid-connected mode may be considered to manage its own resources. This can take place through auctions with individual units of the microgrid as the agents. This research proposes efficient auction mechanisms for the energy grid, with is-landed and connected microgrids. The microgrid level auction is carried out by means of an intermediate agent called an aggregator. The individual consumer and producer units are modeled as selfish agents. With the microgrid in islanded mode, two aggregator-level auction classes are analyzed: (i) price-heterogeneous, and (ii) price homogeneous. Under the price heterogeneity paradigm, this research extends earlier work on the well-known, single-sided Kelly mechanism to double auctions. As in Kelly auctions, the proposed algorithm implements the bidding without using any agent level private infor-mation (i.e. generation capacity and utility functions). The proposed auction is shown to be an efficient mechanism that maximizes the social welfare, i.e. the sum of the utilities of all the agents. Furthermore, the research considers the situation where a subset of agents act as a coalition to redistribute the allocated energy and price using any other specific fairness criterion. The price homogeneous double auction algorithm proposed in this research ad-dresses the problem of price-anticipation, where each agent tries to influence the equilibri-um price of energy by placing strategic bids. As a result of this behavior, the auction’s efficiency is lowered. This research proposes a novel approach that is implemented by the aggregator, called virtual bidding, where the efficiency can be asymptotically maximized, even in the presence of price anticipatory bidders. Next, an auction mechanism for the energy grid, with multiple connected mi-crogrids is considered. A globally efficient bi-level auction algorithm is proposed. At the upper-level, the algorithm takes into account physical grid constraints in allocating energy to the microgrids. It is implemented by the DSO as a linear objective quadratic constraint problem that allows price heterogeneity across the aggregators. In parallel, each aggrega-tor implements its own lower-level price homogeneous auction with virtual bidding. The research concludes with a preliminary study on extending the DSO level auc-tion to multi-period day-ahead scheduling. It takes into account storage units and conven-tional generators that are present in the grid by formulating the auction as a mixed inte-ger linear programming problem

    Hydrodynamics-Biology Coupling for Algae Culture and Biofuel Production

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    International audienceBiofuel production from microalgae represents an acute optimization problem for industry. There is a wide range of parameters that must be taken into account in the development of this technology. Here, mathematical modelling has a vital role to play. The potential of microalgae as a source of biofuel and as a technological solution for CO2 fixation is the subject of intense academic and industrial research. Large-scale production of microalgae has potential for biofuel applications owing to the high productivity that can be attained in high-rate raceway ponds. We show, through 3D numerical simulations, that our approach is capable of discriminating between situations where the paddle wheel is rapidly moving water or slowly agitating the process. Moreover, the simulated velocity fields can provide lagrangian trajectories of the algae. The resulting light pattern to which each cell is submitted when travelling from light (surface) to dark (bottom) can then be derived. It will then be reproduced in lab experiments to study photosynthesis under realistic light patterns

    Surveillance of Complex Auction Markets: a Market Policy Analytics Approach

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    The dissertation consists of four essays that investigates the merits of big data-driven decision-making in the surveillance of complex auction markets. In the first essay, Avci and her co-researchers examine the aggregate-level bidding strategies and market efficiency in a multi-time tariff setting by using parametric and semi parametric methods. In the second essay, they address three key forecasting challenges; risk of selection of an inadequate forecasting method and transparency level of the market and market-specific multi-seasonality factors in a semi-transparent auction market. In the third essay, they demonstrate the effect of information feedback mechanisms on bidders’ price expectations in complex auction markets with the existence of forward contracts. They develop a research model that empirically tests the impact of bidders’ attitudes on their price expectation through their trading behavior and tested their hypotheses on real ex-ante forecasts, evaluated ex-post. In the fourth essay, they investigate characterization of bidding strategies in an oligopolistic multi-unit auction and then examine the interactions between different strategies and auction design parameters. This dissertation offers important implications to theory and practice of surveillance of complex auction markets. From the theoretical perspective, this is, to our best knowledge, the first research that systematically examines the interplay of different informational and strategic factors in oligopolistic multi-unit auction markets. From the policy perspective, Avci’s research shows that integration of big data analytics and domain-specific knowledge improves decision-making in surveillance of complex auction markets

    Ontologies for the Interoperability of Heterogeneous Multi-Agent Systems in the scope of Energy and Power Systems

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    Tesis por compendio de publicaciones[ES]El sector eléctrico, tradicionalmente dirigido por monopolios y poderosas empresas de servicios públicos, ha experimentado cambios significativos en las últimas décadas. Los avances más notables son una mayor penetración de las fuentes de energía renovable (RES por sus siglas en inglés) y la generación distribuida, que han llevado a la adopción del paradigma de las redes inteligentes (SG por sus siglas en inglés) y a la introducción de enfoques competitivos en los mercados de electricidad (EMs por sus siglas en inglés) mayoristas y algunos minoristas. Las SG emergieron rápidamente de un concepto ampliamente aceptado en la realidad. La intermitencia de las fuentes de energía renovable y su integración a gran escala plantea nuevas limitaciones y desafíos que afectan en gran medida las operaciones de los EMs. El desafiante entorno de los sistemas de potencia y energía (PES por sus siglas en inglés) refuerza la necesidad de estudiar, experimentar y validar operaciones e interacciones competitivas, dinámicas y complejas. En este contexto, la simulación, el apoyo a la toma de decisiones, y las herramientas de gestión inteligente, se vuelven imprescindibles para estudiar los diferentes mecanismos del mercado y las relaciones entre los actores involucrados. Para ello, la nueva generación de herramientas debe ser capaz de hacer frente a la rápida evolución de los PES, proporcionando a los participantes los medios adecuados para adaptarse, abordando nuevos modelos y limitaciones, y su compleja relación con los desarrollos tecnológicos y de negocios. Las plataformas basadas en múltiples agentes son particularmente adecuadas para analizar interacciones complejas en sistemas dinámicos, como PES, debido a su naturaleza distribuida e independiente. La descomposición de tareas complejas en asignaciones simples y la fácil inclusión de nuevos datos y modelos de negocio, restricciones, tipos de actores y operadores, y sus interacciones, son algunas de las principales ventajas de los enfoques basados en agentes. En este dominio, han surgido varias herramientas de modelado para simular, estudiar y resolver problemas de subdominios específicos de PES. Sin embargo, existe una limitación generalizada referida a la importante falta de interoperabilidad entre sistemas heterogéneos, que impide abordar el problema de manera global, considerando todas las interrelaciones relevantes existentes. Esto es esencial para que los jugadores puedan aprovechar al máximo las oportunidades en evolución. Por lo tanto, para lograr un marco tan completo aprovechando las herramientas existentes que permiten el estudio de partes específicas del problema global, se requiere la interoperabilidad entre estos sistemas. Las ontologías facilitan la interoperabilidad entre sistemas heterogéneos al dar un significado semántico a la información intercambiada entre las distintas partes. La ventaja radica en el hecho de que todos los involucrados en un dominio particular los conocen, comprenden y están de acuerdo con la conceptualización allí definida. Existen, en la literatura, varias propuestas para el uso de ontologías dentro de PES, fomentando su reutilización y extensión. Sin embargo, la mayoría de las ontologías se centran en un escenario de aplicación específico o en una abstracción de alto nivel de un subdominio de los PES. Además, existe una considerable heterogeneidad entre estos modelos, lo que complica su integración y adopción. Es fundamental desarrollar ontologías que representen distintas fuentes de conocimiento para facilitar las interacciones entre entidades de diferente naturaleza, promoviendo la interoperabilidad entre sistemas heterogéneos basados en agentes que permitan resolver problemas específicos de PES. Estas brechas motivan el desarrollo del trabajo de investigación de este doctorado, que surge para brindar una solución a la interoperabilidad de sistemas heterogéneos dentro de los PES. Las diversas aportaciones de este trabajo dan como resultado una sociedad de sistemas multi-agente (MAS por sus siglas en inglés) para la simulación, estudio, soporte de decisiones, operación y gestión inteligente de PES. Esta sociedad de MAS aborda los PES desde el EM mayorista hasta el SG y la eficiencia energética del consumidor, aprovechando las herramientas de simulación y apoyo a la toma de decisiones existentes, complementadas con las desarrolladas recientemente, asegurando la interoperabilidad entre ellas. Utiliza ontologías para la representación del conocimiento en un vocabulario común, lo que facilita la interoperabilidad entre los distintos sistemas. Además, el uso de ontologías y tecnologías de web semántica permite el desarrollo de herramientas agnósticas de modelos para una adaptación flexible a nuevas reglas y restricciones, promoviendo el razonamiento semántico para sistemas sensibles al contexto

    Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

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    The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication
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