A Production Simulation Tool for Systems With Integrated Wind Energy Resources

The rapid increase in wind power capacity over the past decade has resulted from the adoption of policies that encourage the wider use of renewable energy sources in order to reduce CO 2 and the dramatic cost reductions due to technology advancements. The high variability in wind speeds poses major...

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Veröffentlicht in:IEEE transactions on power systems 2011-11, Vol.26 (4), p.2285-2292
Hauptverfasser: Maisonneuve, N., Gross, G.
Format: Artikel
Sprache:eng
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Zusammenfassung:The rapid increase in wind power capacity over the past decade has resulted from the adoption of policies that encourage the wider use of renewable energy sources in order to reduce CO 2 and the dramatic cost reductions due to technology advancements. The high variability in wind speeds poses major difficulties in power system planning and operations, leading to an acute need for practical planning and operations tools to study the effects of the integration of wind resources into the grid. This paper addresses the need in the planning domain through the development of a computationally efficient probabilistic production simulation approach with the capability to quantify the variable effects of systems for varying levels of wind penetration with the uncertainty in the variability/intermittency effects of wind generation at multiple sites together with the other sources of uncertainty explicitly represented. The simulation approach is based on the identification of the prevailing wind regimes in the regions where wind resources are located and the judicious application of conditional probability concepts in incorporating the wind regime representation. The regimes-based approach described in the paper effectively captures both the seasonal and the diurnal variations of renewable resources and their correlation with the load seasonal and diurnal changes. Additionally, the proposed approach explicitly quantifies the impacts of wind on the additional reserve requirements on the controllable resources. The paper illustrates the effectiveness of the approach by its application to large-scale test systems using historical data.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2011.2143437