| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 4.57 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
A flexibilidade energética desempenhará um papel fundamental no funcionamento dos sistemas energéticos, introduzindo um conjunto de benefícios a todas as partes interessadas envolvidas e mudando o mercado energético como o conhecemos. Espera-se que novas entidades com diferentes interesses emerjam nesse contexto, particularmente os agregadores, que permitirão que os utilizadores finais estejam cientes do valor da flexibilidade no seu consumo, ou simplesmente facilitar a participação destes, por exemplo, através do uso de Demand Response (DR) no mercado, para atender às necessidades do sistema. No entanto, para retirar o maior proveito possível da flexibilidade adquirida de pequenos clientes, uma resposta rápida do sistema será necessária, permitindo a interação entre agregadores e utilizadores residenciais. Portanto, o chamado sistema de gestão de energia residencial torna-se uma ferramenta essencial para a comunicação entre utilizadores finais e agregadores, realizando mudanças necessárias nos perfis de consumo em benefício de todas as partes envolvidas. Nesta dissertação é introduzido um modelo com o objetivo de conseguir uma correspondência entre a flexibilidade exigida por um agregador e a flexibilidade oferecida pelos utilizadores residenciais através da capacidade de um sistema de gestão de energia residencial de realizar um conjunto de tarefas que são abordadas com maior detalhe ao longo da dissertação. Este modelo é desenvolvido usando a ferramenta informática R, que com determinados dados de entrada, devolve parâmetros otimizados usando a otimização por enxame de partículas (PSO). A ferramenta considera uma minimização de uma função objetivo com os seguintes termos: custo dos diferentes tipos de equipamentos em estudo, flexibilidade oferecida pelo sistema de gestão residencial e flexibilidade requerida pelo agregador. Assim sendo, a metodologia apresentada é aplicada a um conjunto de utilizadores residenciais de forma a testar a sua eficácia e eficiência. A análise dos resultados comprova a viabilidade, a adequação, robustez e versatilidade da metodologia proposta para esta dissertação.
Energy flexibility will play a key role in the proper functioning of energy systems, introducing a set of benefits to all involved stakeholders and changing the shape of electricity markets as we know them. It is expected that new players with different interests will emerge in this context. Particularly, the aggregators might allow end-users to be aware of their consumption flexibility value, or merely facilitate consumer’s participation, for instance through the use of demand response in the market to meet system requirements. However, to take full advantage of the flexibility procurement of small customers, a prompt system response allowing the interaction between aggregators and residential users is needed. Therefore, the so-called Home Energy Management System (HEMS) becomes an active tool to communicate end-users with aggregators, performing the necessary changes in the consumption profiles in the benefit of all involved parts. In this dissertation, a model is introduced to match the flexibility required by an aggregator to the flexibility offered by residential users through the ability of a HEMS to perform a set of tasks that are addressed with detail throughout the dissertation. This model is developed using the R software, which with certain input data returns optimized parameters using particle swarm optimization (PSO). The tool considers a minimization of an objective function with the following terms: cost of the different types of equipment under study, flexibility offered by the residential management system and flexibility required by the aggregator. Thus, the presented methodology is applied to a set of residential users in order to test its effectiveness and efficiency. The analysis of the results, prove the feasibility, adequacy, robustness and versatility of the methodology proposed for this dissertation.
Energy flexibility will play a key role in the proper functioning of energy systems, introducing a set of benefits to all involved stakeholders and changing the shape of electricity markets as we know them. It is expected that new players with different interests will emerge in this context. Particularly, the aggregators might allow end-users to be aware of their consumption flexibility value, or merely facilitate consumer’s participation, for instance through the use of demand response in the market to meet system requirements. However, to take full advantage of the flexibility procurement of small customers, a prompt system response allowing the interaction between aggregators and residential users is needed. Therefore, the so-called Home Energy Management System (HEMS) becomes an active tool to communicate end-users with aggregators, performing the necessary changes in the consumption profiles in the benefit of all involved parts. In this dissertation, a model is introduced to match the flexibility required by an aggregator to the flexibility offered by residential users through the ability of a HEMS to perform a set of tasks that are addressed with detail throughout the dissertation. This model is developed using the R software, which with certain input data returns optimized parameters using particle swarm optimization (PSO). The tool considers a minimization of an objective function with the following terms: cost of the different types of equipment under study, flexibility offered by the residential management system and flexibility required by the aggregator. Thus, the presented methodology is applied to a set of residential users in order to test its effectiveness and efficiency. The analysis of the results, prove the feasibility, adequacy, robustness and versatility of the methodology proposed for this dissertation.
Description
Keywords
Agregador Flexibilidade Resposta à procura Sistema de gestão de energia Aggregator Flexibility Demand response Home energy management system