Publicação: Probabilistic Algorithm based on 2m+1 Point Estimate Method Edgeworth considering Voltage Confidence Intervals for Optimal PV Generation
Carregando...
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Tipo
Trabalho apresentado em evento
Direito de acesso
Resumo
Photovoltaic (PV) systems widespread into distribution networks due to its environmentally friendly source of energy, cost-competitive option and system support benefits. However, traditional distribution networks were not designed to operate under a high penetration of intermittent generation posing technical challenges for grid operation and planning. Therefore, probabilistic tools become suitable to cater for uncertainties in generation and demand, thus, leading to a more realistic network representation. Furthermore, the need for harvesting potential energy in an uncertain environment are essential for an efficient grid operation. In this context, this work proposes a probabilistic algorithm based on 2m+1 Point Estimate Method Edgeworth to tackle technical issues considering voltage confidence levels that is used for maximizing PV generation. Tests in a IEEE 33 buses radial distribution system using the proposed probabilistic algorithm yields higher accuracy of cost probability distribution, voltage confidence intervals and a faster computational time when compared to Monte Carlo simulation.
Descrição
Palavras-chave
2m+1 Point Estimate Method Edgeworth, Optimal Probability PV Generation, Probabilistic Algorithm Optimization, Voltage Confidence Intervals
Idioma
Inglês
Como citar
2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022.
