Short-term Load Forecasting in Grid-connected Microgrid

被引：0

作者：

Izzatillaev, Jurabek ^{[1
]}

Yusupov, Ziyodulla ^{[2
]}

机构：

[1] Acad Sci, Semicond Solar Cells Lab, Phys Tech Inst, Tashkent, Uzbekistan

[2] Karabuk Univ, Dept Elect Elect, Karabuk, Turkey

来源：

2019 7TH INTERNATIONAL ISTANBUL SMART GRIDS AND CITIES CONGRESS AND FAIR (ICSG ISTANBUL 2019) | 2019年

关键词：

Artificial neural networks; forecasting; load; microgrid; NEURAL-NETWORKS; MANAGEMENT;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The integration of distributed energy resources (DER) into main grid need to consider the influence of many factors. One of them is the determination of electric load in Microgrid. Creating a feasible and efficient Microgrid based on the predicted power load is more relevant. The paper analyzes the forecasting of the electric energy consumption in Microgrids, analyzes the area of applicability, advantages and disadvantages of short-term forecasting methods of power consumption. Two methods - Group Method of Data Handling (GMDH) and Artificial Neural Networks (ANN) are used to determine short-term load forecasting.

引用

页码：71 / 75

页数：5

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