Modelo para medir o potencial de adoção dos consumidores à tecnologia fotovoltaica a partir de Power Big Data

• Ano de defesa: 2024
• Autor(a) principal: Nascimento, Felipe Moraes do
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia de Produção; UFSM; Programa de Pós-Graduação em Engenharia de Produção; Centro de Tecnologia
• Palavras-chave em Português: Energia solar; Geração distribuída; Análise do comportamento; Apoio à decisão; Adoção fotovoltaica; Operadores do sistema de distribuição; Sustentabilidade da distribuição; Power Big Data; Solar energy; Distributed generation; Behavior analysis; Decision support; Photovoltaic adoption; Distribution system operators; Distribution sustainability; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/31994

The electricity sector is undergoing a historic transformation from the grid to the distributed generation and storage model, and photovoltaic energy is one of the main technologies used in this transformation around the world. In several countries, laws have been published that allow electricity consumers to connect generation systems to the distribution network, such as Law 14,300, of January 6, 2022, in Brazil. The prosumer is the new agent in electricity markets, and its decision-making process related to photovoltaic adoption is vulnerable to the influences of individual heterogeneity and complex interactions, as it involves high initial investment costs, external influences and lack of information. The different behavioral aspects give new meaning to the consumer's relationship with energy, causing implications mainly in the relationship between the consumer and Distribution System Operators (OSD), who are key actors in photovoltaic acceptance. However, the proliferation of technology challenges the very nature of natural monopoly and is not necessarily aligned with the OSD's business objectives, so it is necessary for OSDs to be better informed for decision-making related to photovoltaic diffusion. This research developed two models, the first based on consumer opinion and the second datadriven from Power Big Data, an innovative approach that seeks to combine data analysis and multi-criteria methods for measuring consumer behavior when the number of alternatives is substantially high. The model based on consumer opinion was applied to 20 experts and 29 consumers, of which nine consumers showed a migration potential of more than 90%. Furthermore, exploring the potential of Distribution System Operators' Power Big Data identified 15 influential data attributes in 10 KPIs of photovoltaic technology adoption. The case study analyzed the photovoltaic uptake potential of 25,180 consumers and 30,858 consumer units in southern Brazil. Two computational tools were developed for the practical application of modeling, a mobile application for the opinion model and a web application for the Power Big Data model. The results highlight the substantial contribution of the proposed models in understanding the determining factors for the photovoltaic adoption decision and in measuring the diagnosis of the potential to adhere to photovoltaic technology, with successful adaptability to heterogeneous data sets and practical applicability reinforcing their usefulness in complex environments, providing valuable insights for distribution system operators, integrators, and policymakers.