Comparison of Probabilistic Forecasts for Predictive Voltage Control

被引：0
作者：
Panamtash, Hossein [1 ]
Mahdavi, Shahrzad [1 ]
Dimitrovski, Aleksandar [1 ]
Zhou, Qun [1 ]
机构：
[1] Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA
来源：
2020 52ND NORTH AMERICAN POWER SYMPOSIUM (NAPS) | 2021年
关键词：
Predictive Control; Probabilistic Forecast; Cooperative Control; Distributed Generation; Voltage Control; Quantile Regression;
D O I：
10.1109/NAPS50074.2021.9449769
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper explores predictive cooperative voltage control in distribution systems with highly variable sources such as photovoltaics (PV). The goal is to maintain the voltage profile within the limits despite the fluctuations due to sudden changes in solar power generation. The predictive voltage control method relies on probabilistic solar power and load forecasts to select the optimum Voltage Regulator (VR) taps appropriately. VR taps are selected to minimize the risk of voltage violation. A modified version of the IEEE 123 system is used as the case study. A 100% penetration of solar power is assumed for the distribution system with profiles for solar generation and loads added to the system. Three different probabilistic forecast models (Quantile Regression (QR), Gaussian distribution and volatility forecasting using Generalized Autoregressive Conditional Heteroskedasticity (GARCH)) are explored in this study. The results for the VR taps and Voltage Deviation Index (VDI) are compared to find the most effective forecast model.
引用
收藏
页数：6
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