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Flexibilidad energética en barrio de edificios residenciales mediante la activación de la masa termica. Resultados experimentales en un entorno semivirtual
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Advisor(s)
Abstract(s)
RESUMEN: En los próximos años los edificios se convertirán en productores y consumidores de energía al mismo tiempo. Por esta razón, la gestión de la demanda a nivel de edificio y a nivel de barrio a través de un agregador independiente requerirá de sistemas de control inteligentes con el objetivo de optimizar y gestionar dos aspectos: maximizar el uso de energía renovable local y usar la energía de la red en el momento más oportuno. El presente estudio se enfoca en los resultados de un sistema de algoritmos de optimización multi-nivel testeados en tiempo real. El experimento desarrollado reproduce, en dos laboratorios físicamente alejados 100 km, el comportamiento de dos edificios de un mismo barrio mediante un sistema semi-virtual donde unos modelos del edificio determinan su demanda energética emulandola en los laboratorios haciendo actuar al equipamiento físico en condiciones reales de trabajo. Los resultados muestran que la gestión inteligente de la masa térmica del edificio con los algoritmos de optimización puede aportar los mismos beneficios que instalar una batería eléctrica actuando con algoritmos inteligentes o de autoconsumo.
ABSTRACT: In the coming years, buildings will become energy producers and consumers at the same time. To optimize the system operation, smart control algorithms shall manage the energy demand of an individual building and of entire districts of buildings. The algorithms goals shall maximize the use of the renewable energy produced on-site and using the energy from the electric grid at the most appropriate time. The current study focus on the results of a multilevel optimization system tested in real-time. The experiment performed reproduces, in two laboratories 100 km away, the behavior of two buildings of similar characteristics hypothetically located in the same district. This is done with energy building models which allows emulating their energy demands connected to real laboratory equipment (heat pumps, PV, batteries and management and control systems). Results of the experiments show that the smart activation of the building’s thermal mass can bring similar benefits than installing an electric battery that acts following smart or self-consumption management strategies.
ABSTRACT: In the coming years, buildings will become energy producers and consumers at the same time. To optimize the system operation, smart control algorithms shall manage the energy demand of an individual building and of entire districts of buildings. The algorithms goals shall maximize the use of the renewable energy produced on-site and using the energy from the electric grid at the most appropriate time. The current study focus on the results of a multilevel optimization system tested in real-time. The experiment performed reproduces, in two laboratories 100 km away, the behavior of two buildings of similar characteristics hypothetically located in the same district. This is done with energy building models which allows emulating their energy demands connected to real laboratory equipment (heat pumps, PV, batteries and management and control systems). Results of the experiments show that the smart activation of the building’s thermal mass can bring similar benefits than installing an electric battery that acts following smart or self-consumption management strategies.
Description
CIES2020 - XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia Solar
Keywords
Energy efficiency in buildings Energy management Optimization Thermal performance
Pedagogical Context
Citation
Salom, J... [et.al.] - Flexibilidad energética en barrio de edificios residenciales mediante la activación de la masa termica. Resultados experimentales en un entorno semivirtual. In: CIES2020: As Energias Renováveis na Transição Energética: Livro de Comunicações do XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia Solar. Helder Gonçalves, Manuel Romero (Ed.). Lisboa, Portugal: LNEG, 3-5 Novembro, 2020, p. 997-1006
Publisher
LNEG - Laboratório Nacional de Energia e Geologia