Model predictive control of interconnected microgrids and electric vehicles

[ES] La microrred como elemento agregador de fuentes de generación, cargas y sistemas de almacenamiento de energía aparece como tecnología clave para dotar a los sistemas eléctricos de suficiente flexibilidad para una transición energética basada en fuentes renovables. Sin embargo, el problema de control para la gestión de energía se vuelve complejo cuando se incrementa el número de sistemas conectados a una misma microrred. De igual forma, se requiere flexibilidad para integrar a los vehículos eléctricos. La interacción entre las distintas microrredes y los vehículos hacen necesarias herramientas avanzadas de control para resolver el problema de optimización. El objeto del presente trabajo es presentar distintas herramientas de control predictivo basado en el modelo (Model Predictive Control, MPC) para resolver el problema de control asociado a este tipo de sistemas. En concreto, se abordan dos problemas: la conexión de vehículos eléctricos a la microrred y la interconexión de varias microrredes. Para el primer caso se analizan dos escenarios, según que el intercambio de energía sea uni o bidireccional y se presenta la forma de optimizar la operación usando MPC. En el segundo caso se aborda el problema usando técnicas de control distribuido.[EN] Microgrids, as aggregators of sources, loads and energy storage systems, appear as key technology to provide the required flexibility to electric power systems to carry out an energy transition based on renewable sources. Nevertheless, the control problem becomes complex when the number of connected components to the same microgrid increases. Also, the system requires flexibility to integrate electric vehicles. The complexity given by the associated control problem to optimize the energy exchange between microgrids and the electric vehicles makes necessary the development of advanced control tools. In this work, dierent Model Predictive Control (MPC) strategies are introduced in order to face the challenge of the control problem formulation of this kind of systems. Specifically, two problems are addressed: the connection of electric vehicles to the microgrid and the interconnection of several microgrids. For the first case, two scenarios are analyzed, depending on whether the energy exchange is uni or bidirectional, the way to optimize the operation using MPC is presented and examples of use are shown. For the second case, the problem isaddressed using distributed control techniques.Este trabajo ha sido realizado parcialmente gracias al apoyo del Ministerio de Econom´ıa, Industria y Competitividad de Espana mediante el proyecto CONFIGURA (DPI2016-78338-R) y por la Comision Europea, en el proyecto AGERAR (0076- ´ AGERAR-6-E), dentro del programa Interreg Spain-Portugal (POCTEP).Bordons, C.; Garcia-Torres, F.; Ridao, M. (2020). 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Comparison of Distributed Predictive Control Algorithms Applied to Interconnected Microgrids

[Resumen] Las microrredes son sistemas de distribución de energía eléctrica que favorecen la integración de fuentes de energía renovable de distintos tipos, e incorporando también, sistemas de almacenamiento de energía, para posteriormente, ser consumida en momentos de mayor necesidad. En estos sistemas, es de vital importancia implementar una estrategia de control que regule la distribución de la energía entre los distintos equipos. Los controladores basados en Model Predictive Control (MPC) funcionan de una manera muy satisfactoria debido a su carácter óptimo y previsor ante los cambios en las situaciones. Resulta interesante conectar varias microrredes para que funcionen de manera conjunta, transportando energía de una a otra cuando alguna de ellas lo necesite y a otra le sobre. El problema de control para este caso es de una complejidad mayor, pudiendo seguir distintas estrategias basadas en controladores tipo MPC. En este trabajo se ofrece una comparativa entre distintas estrategias de control distribuido, implementadas en un simulador de microrredes desarrollado en Matlab.[Abstract] Microgrids are electric energy distribution systems that facilitate the integration of renewable energy sources, and incorporate energy storage systems to be used when needed. In these systems, it is vital to implement a control strategy that manipulates the energy distribution between the equipment. Controllers based on Model Predictive Control have a very successful response due to their optimum results and their anticipatory behavior. It is interesting to connect several microgrids, working together, so they can exchange energy one to another when one needs more energy and other has exceeds. The control problem in this case is more complex but there are different strategies, based on MPC, that can solve this problem. This paper offers a comparative between a centralized strategy and three multi-agent strategies, tested in a “microgrid simulator” developed in Matlab Simulink.Ministerio de Economía y Competitividad; DPI2016-78338-