Impact of modelling non-normality and stochastic dependence of variables on operating reserve determination of power systems with high penetration of wind power
| Autor: | S. Mohammad Mousavi Agah, Damian Flynn |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Engineering Wind power Operating reserve business.industry 020209 energy media_common.quotation_subject 020208 electrical & electronic engineering Energy Engineering and Power Technology Probability density function 02 engineering and technology Reliability engineering Electric power system Base load power plant 0202 electrical engineering electronic engineering information engineering Statistical analysis Non normality Electrical and Electronic Engineering business Physics::Atmospheric and Oceanic Physics Normality media_common |
| Zdroj: | International Journal of Electrical Power & Energy Systems. 97:146-154 |
| ISSN: | 0142-0615 |
| DOI: | 10.1016/j.ijepes.2017.11.002 |
| Popis: | A method is presented for dynamic determination of the operating reserve requirement in power systems with high wind penetration, by considering the non-normal nature of wind power uncertainty and variability as well as their stochastic dependence on the wind power forecast. Distinct from previous methods, a generalised approach is proposed to characterise the probability density of wind power uncertainty and variability at distinct wind power forecast levels. As an illustration, the approach is applied in Ireland to determine the required operating reserve at different time scales within hourly scheduling periods to meet a certain reliability level. Statistical analysis indicates that the results are sensitive to normality and independence assumptions generally adopted in previous studies, and such assumptions may lead to under/over-estimation of the required operating reserve. Thus, the proposed method, which is not based on these limiting assumptions, emerges as a more realistic solution to define operating reserve targets dynamically. It further provides insight for planning studies and the operation of power systems with high wind power penetration. |
| Databáze: | OpenAIRE |
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