Análise da utilização de sistemas de armazenamento de energia na suavização da curva de operação de uma usina fotovoltaica

• Ano de defesa: 2024
• Autor(a) principal: Mendes, Ivens Gabriel de Oliveira Ciríaco
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Energia Solar; Bateria de lítio; Energia - Armazenamento; Sistemas de energia elétrica; Solar energy; Batteries - Lithium; Energy - Storage; Electric power systems; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufc.br/handle/riufc/79475

The search for renewable energy sources (RES), such as solar and wind, has intensified due to the increasing demand for energy and accessibility for consumers. These sources are becoming increasingly competitive in terms of cost, driving the energy transition of electrical systems worldwide. However, the integration of RES into the existing infrastructure presents significant challenges, requiring the development of techniques to ensure the reliability and quality of the supplied energy. This study proposes a solution involving the Battery Energy Storage System (BESS) and analyzes the feasibility and effectiveness of integrating this technology together with the Voltage-Oriented Control (VOC) on the AC side of a photovoltaic plant (PVP), using the Power Ramp Rate (PRR) to control the power to be compensated by the battery bank in a scenario where the PVP is subject to variations in solar irradiance and other real operational conditions. The developed algorithm was tested in three different BESS parameterization scenarios: 30%/15min, 20%/15min, and 10%/15min, corresponding to scenarios 1, 2, and 3, respectively. The objective was to evaluate the BESS's ability to compensate for ramp rates exceeding the specified limits. In the first scenario, all ramp rates above the stipulated threshold were compensated, with a maximum rate of 24.92%/15min. In the second scenario, there was only one ramp rate above the specified limit, reaching 20.36%. In the third scenario, only one ramp exceeded the specified threshold, with a rate of 11.49%. These results highlight the algorithm's effectiveness.