Operating Power Reserve Quantification Through PV Generation Uncertainty Analysis of A Microgrid

被引:0
|
作者
Yan, Xingyu [1 ]
Francois, Bruno [1 ]
Abbes, Dhaker [2 ]
机构
[1] EC Lille, L2EP, Cite Sci, CS 20048, F-59651 Villeneuve Dascq, France
[2] HEI, L2EP, F-59800 Lille, France
关键词
Artificial Neural Networks; microgrid uncertainty; power reserve quantification; variability; INTEGRATION; SYSTEMS; ENERGY;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to renewable energy sources (RES) variable nature and their wide integration into power systems, setting an adequate operating power reserve is important to compensate unpredictable imbalance between generation and consumption. However, this power reserve should be ideally minimized to reduce system cost with a satisfying security level. Although many forecasting methodologies have been developed for forecasting energy generation and load demand, management tools for decision making of operating reserve are still needed. This paper deals with power reserve quantification through uncertainty analysis with a photovoltaic (PV) generator. Indeed, using an artificial neural network based predictor (ANNs), PV power and load have been forecasted 24 hours ahead, and also forecasting errors have been predicted. Through forecasting uncertainty analysis, the power reserve quantification is calculated according to various risk indexes.
引用
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页数:6
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