SciELO - Scientific Electronic Library Online

 
vol.15 número4Empuje dinámico en estructuras de retención con inclusión compresibleSimulación de campos aleatorios con dependencia no multi-gaussiana empleando cópulas índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Ingeniería, investigación y tecnología

versão On-line ISSN 2594-0732versão impressa ISSN 1405-7743

Resumo

GIRALDO-CHAVARRIAGA, Juan Sebastián; CASTRILLON-LARGO, Jhon Alexander  e  GRANADA-ECHEVERRI, Mauricio. Stochastic AC Optimal Power Flow Considering the Probabilistic Behavior of the Wind, Loads and Line Parameters. Ing. invest. y tecnol. [online]. 2014, vol.15, n.4, pp.529-538. ISSN 2594-0732.

As is known, the insertion of new generation technologies, whether it is on transmission or distribution, has several effects on the traditional electric network, from technical changes to its regulation. There is a global interest on finding the best way to take advantage of those emerging technologies and the best way they can interact with the traditional power system. This paper proposes a methodology to exploit the maximum potential of the traditional electric network and the integration of a well-known generation technology such as the wind generation. To do so, we present a Probabilistic AC Optimal Power Flow (POPF) that takes into account load variation, wind’s stochastic behavior and variable line’s thermal rating which is usually used as a deterministic value in several studies. A validation of two proposed schemes of the Point Estimate Method (PEM) is made, not only for normal distributions but for different kinds of probability distributions, such as Weibull and generalized extreme value. Obtained results are compared with the Monte Carlo (MC) simulation indicating that the proposed method significantly reduces the computational burden while maintaining a high level of accuracy.

Palavras-chave : probabilistic optimal power flow; point estimate method; wind generation; distributed generation; Monte Carlo simulation.

        · resumo em Espanhol     · texto em Inglês

 

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons