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Criação de um sistema de apoio à decisão para instalação fotovoltaica com base na análise pormenorizada do perfil do consumidor
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Abstract(s)
A tentativa generalizada de uniformizar os sistemas de apoio à decisão para investimentos em
tecnologia fotovoltaica impede, muitas vezes, que os utilizadores finais tenham acesso a
soluções verdadeiramente personalizadas. Esta limitação compromete não só a capacidade de
corresponder às expectativas dos clientes, como também, de forma mais crítica, a precisão na
projeção do retorno do investimento com base em dados históricos de consumo.
A energia solar de base fotovoltaica tornou-se um dos eixos centrais da transformação
energética global, contribuindo de forma significativa para a redução da pegada carbónica e
para a diversificação do mix energético. Ainda assim, a sua integração em contextos domésticos
e empresariais levanta vários desafios — desde a dificuldade em adaptar soluções às
particularidades dos perfis de consumo, até à elaboração de propostas que conciliem
viabilidade técnica com sustentabilidade económica.
Em Portugal, os avanços têm sido notórios: segundo dados da REN, a 5 de setembro de 2024, a
produção de eletricidade proveniente de sistemas fotovoltaicos atingiu 3,99 TWh, superando
já o total registado em todo o ano de 2023 — e isto em apenas nove meses. No plano
internacional, a energia solar vive um crescimento explosivo: a capacidade instalada mundial
ultrapassou os 2 terawatts, com a China, os EUA e a Índia a ocuparem posições de liderança. O
contraste temporal é revelador — foram precisas quase sete décadas para alcançar o primeiro
TW (entre 1954 e 2022), mas bastaram dois anos adicionais para duplicar esse valor. Esta
evolução acelerada deve-se, em grande medida, à implementação de políticas públicas
favoráveis e à queda acentuada dos custos dos equipamentos.
A necessidade de um sistema de apoio à decisão eficaz e centrado no utilizador surge das
ineficiências frequentemente observadas nas instalações fotovoltaicas domésticas. Um sistema
com estas características deve considerar dados históricos de consumo detalhados, condições
solares regionais e variáveis específicas de cada cliente. Este projeto procura responder a essa
lacuna, através do desenvolvimento de uma ferramenta que forneça soluções personalizadas e
orientadas por dados — assegurando, assim, a viabilidade económica e uma maior satisfação
do utilizador.
The widespread attempt to standardize decision support systems for photovoltaic investment often prevents end users from accessing truly customized solutions. This limitation undermines not only the ability to meet client expectations but also, more critically, the accuracy of projecting project payback based on historical consumption data. Photovoltaic solar energy has become a central pillar of the global energy transition, playing a key role in reducing carbon emissions and diversifying the energy mix. Nevertheless, its integration into residential and commercial settings continues to pose several challenges — from the difficulty of tailoring solutions to specific consumption patterns, to the development of proposals that balance technical feasibility with economic sustainability. In Portugal, progress has been notable: according to data from REN, by 5 September 2024, electricity generation from photovoltaic systems had reached 3.99 TWh — already exceeding the total recorded for the entire year of 2023, and this in just nine months. On a global scale, solar power is experiencing exponential growth: installed capacity has surpassed 2 terawatts, with China, the United States, and India leading the market. The timeline speaks volumes — it took nearly seven decades to reach the first TW (from 1954 to 2022), but only two additional years to double it. This accelerated development has been largely driven by supportive public policies and a sharp decline in equipment costs. The need for an effective and user-oriented decision support system arises from the inefficiencies frequently observed in domestic PV installations. Such a system must consider detailed historical consumption data, regional solar conditions, and customer-specific variables. This project aims to address this gap by developing a tool that delivers personalized, data-driven solutions—ensuring both economic viability and enhanced user satisfaction.
The widespread attempt to standardize decision support systems for photovoltaic investment often prevents end users from accessing truly customized solutions. This limitation undermines not only the ability to meet client expectations but also, more critically, the accuracy of projecting project payback based on historical consumption data. Photovoltaic solar energy has become a central pillar of the global energy transition, playing a key role in reducing carbon emissions and diversifying the energy mix. Nevertheless, its integration into residential and commercial settings continues to pose several challenges — from the difficulty of tailoring solutions to specific consumption patterns, to the development of proposals that balance technical feasibility with economic sustainability. In Portugal, progress has been notable: according to data from REN, by 5 September 2024, electricity generation from photovoltaic systems had reached 3.99 TWh — already exceeding the total recorded for the entire year of 2023, and this in just nine months. On a global scale, solar power is experiencing exponential growth: installed capacity has surpassed 2 terawatts, with China, the United States, and India leading the market. The timeline speaks volumes — it took nearly seven decades to reach the first TW (from 1954 to 2022), but only two additional years to double it. This accelerated development has been largely driven by supportive public policies and a sharp decline in equipment costs. The need for an effective and user-oriented decision support system arises from the inefficiencies frequently observed in domestic PV installations. Such a system must consider detailed historical consumption data, regional solar conditions, and customer-specific variables. This project aims to address this gap by developing a tool that delivers personalized, data-driven solutions—ensuring both economic viability and enhanced user satisfaction.
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Keywords
Photovoltaic Systems Energy Consumption Decision Support Tool Solar Energy Investment Analysis Customized Solutions Sistemas fotovoltaicos Consumo de energia Ferramenta de apoio à decisão Energia solar Análise de investimento Soluções personalizadas
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