Avaliação do impacto da produção eólica na reserva operativa de curto e longo prazo utilizando séries temporais

• Ano de defesa: 2019
• Autor(a) principal: SANTOS, Fernando Manuel Carvalho da Silva
• Orientador(a): BRANCO, Tadeu da Mata Medeiros
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Pará
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Elétrica
• Departamento: Instituto de Tecnologia
• País: Brasil
• Palavras-chave em Português: Fontes variáveis; Energia eólica; Reserva operativa; Séries temporais; Simulação de monte carlo
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufpa.br/jspui/handle/2011/11328

One of the main concerns of a system planner is to size generation equipment, mainly for meeting the load growth and to achieve certain spinning reserve requirements. In general, generation systems must be sized with sufficient capacity, flexibility and robustness to respond to several operational challenges. However, the volatility and variability that comes from renewable generation is a relatively recent concern for the system planners. This thesis evaluates the potential of diverse wind power patterns to balance the global power output of wind farms using the concept of operating reserve assessment. To achieve this, operating reserve assessment models are utilized to evaluate bulk generation systems under several conditions of wind power geographic distribution. Different wind behavior patterns and wind power penetration levels are tested using a modified configuration of the IEEE RTS-96 and a planning configuration of the Portuguese Generation System. The results highlight that on a large country scale system with different wind characteristics, the diversification of wind behavior might be conducive to a compensation of wind power fluctuations, which may significantly decrease the need for system operating reserves. This effect is verified using probability distribution functions of reserve needs estimated by sequential Monte Carlo simulations (SMCS), such that useful information regarding generation capacity flexibility is drawn from the evaluations.