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Authors
Advisor(s)
Abstract(s)
A grande transformação no sistema elétrico de energia de que estamos a ser alvo deve-se
ao aumento do uso de energias renováveis juntamente com a liberalização do mercado
energético, transformando o sistema tradicional e centralizado numa smart grid, ou seja,
rede elétrica inteligente. O principal objetivo desta rede inteligente é a capacidade de
produção, transporte, distribuição e o uso final de energia elétrica de modo eficiente,
ambientalmente sustentável, viável economicamente e de forma confiável e segura deixando
assim a rede de energia elétrica estar estabelecida na estrutura tradicional (centralizada)
passando então a estar estabelecida numa estrutura descentralizada.
A rede elétrica inteligente é uma rede modernizada que utiliza as Tecnologias de Informação
e Comunicação (TICs) para reunir e agir sobre informações de modo automático
de forma a melhorar a fiabilidade e eficiência dos sistemas elétricos. Uma micro rede é
parte integrante de uma rede inteligente que integra recursos energéticos (normalmente
renováveis) em pequena escala.
Tendo por objetivo aumentar a sustentabilidade em micro redes, é fundamental a
aplicação de métodos de priorização, escalonamento e deslastre de cargas. Este trabalho
tem por objetivo aplicar técnicas inovadoras que visem otimizar os recursos existentes
numa rede elétrica inteligente que opera desconectada da rede principal. Em particular
pretende-se aplicar o conceito de campos de potencial elétrico de modo a conseguir distribuir
a produção de energia a partir de recursos energéticos renováveis pelas diversas
cargas e ao longo do tempo (isto é, ajustar a procura de energia elétrica pelas cargas à
oferta de energia elétrica oferecida pelos recursos de produção de energia), focando a priorização,
escalonamento e deslastre de cargas elétricas. Esta alocação considera os perfis do utilizador final, assim como o nível de utilidade das cargas de modo a que o impacto
seja minimizado.
A abordagem proposta foi testada num caso de estudo compreendendo uma micro
rede elétrica, pertencente à empresa Locionni em Itália, esta contém seis consumidores
(habitações unifamiliares) e nove produtores de energia elétrica.
The major transformation in the energy system we are targeting is due to the increased use of renewable energy along with the liberalization of the energy market, transforming the traditional and centralized system into a smart grid. The main objective of this intelligent network is the capacity to produce, transport, distribute and use electricity in an efficient, environmentally sustainable, economically viable and reliable and safe way, thus leaving the electricity grid established in the traditional structure (centralized) and then established in a decentralized structure. The smart grid is a modernized grid that uses the TICs to gather and act on information automatically to improve the reliability and efficiency of electrical systems. A microgrid is part of an intelligent network that integrates energy resources (usually renewable) on a small scale. With the objective of increasing sustainability in microgrid, it is fundamental to apply methods of prioritization, scheduling and load shedding. The objective of this work is to apply innovative techniques that optimize the existing resources in an intelligent electrical grids that operates disconnected from the main grids. In particular, it is intended to apply the concept of electric potential fields in order to be able to distribute the energy production from renewable energy resources by the various loads and over time (that is, to adjust the electric energy demand by the loads to the supply of electricity offered by energy production resources), focusing on the prioritization, scheduling and shedding of electric charges. This allocation considers the end-user profiles as well as the level of utility of the loads so that the impact is minimized. The proposed approach was tested in a case study comprising a microgrid owned by Locionni in Italy, which contains six consumers (single family dwellings) and nine electricity producers.
The major transformation in the energy system we are targeting is due to the increased use of renewable energy along with the liberalization of the energy market, transforming the traditional and centralized system into a smart grid. The main objective of this intelligent network is the capacity to produce, transport, distribute and use electricity in an efficient, environmentally sustainable, economically viable and reliable and safe way, thus leaving the electricity grid established in the traditional structure (centralized) and then established in a decentralized structure. The smart grid is a modernized grid that uses the TICs to gather and act on information automatically to improve the reliability and efficiency of electrical systems. A microgrid is part of an intelligent network that integrates energy resources (usually renewable) on a small scale. With the objective of increasing sustainability in microgrid, it is fundamental to apply methods of prioritization, scheduling and load shedding. The objective of this work is to apply innovative techniques that optimize the existing resources in an intelligent electrical grids that operates disconnected from the main grids. In particular, it is intended to apply the concept of electric potential fields in order to be able to distribute the energy production from renewable energy resources by the various loads and over time (that is, to adjust the electric energy demand by the loads to the supply of electricity offered by energy production resources), focusing on the prioritization, scheduling and shedding of electric charges. This allocation considers the end-user profiles as well as the level of utility of the loads so that the impact is minimized. The proposed approach was tested in a case study comprising a microgrid owned by Locionni in Italy, which contains six consumers (single family dwellings) and nine electricity producers.
Description
Keywords
Redes elétricas inteligentes Micro redes Priorização de cargas Escalonamento de cargas Campos de potencial