Predicting the Power Generation from Renewable Energy Sources by using ANN

被引：3

作者：

Rubanenko, Olena ^{[1
]}

Gundebommu, Sree Lakshmi ^{[2
]}

Cosovic, Marijana ^{[3
]}

Lesko, Vladislav ^{[1
]}

机构：

[1] Vinnytsia Natl Tech Univ, Dept Elect Stn & Syst, Vinnytsya, Ukraine

[2] CVR Coll Engn, Hyderabad, India

[3] Univ East Sarajevo, Fac Elect Engn, East Sarajevo, Bosnia & Herceg

来源：

2021 20TH INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA (INFOTEH) | 2020年

关键词：

renewable energy sources; power grid; power balance; optimal control;

D O I：

10.1109/INFOTEH51037.2021.9400527

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes power generation forecasting for photovoltaic power plants by using Adaptive Neuro-Fuzzy Inference Systems library in MATLAB and considering meteorological factors. Renewable energy sources (RES) introduce compensation instability problems in the grid hence forecasting methods are considered. Especially important for grid operators is a day ahead forecasting as it can reduce negative imbalance price. Means of ensuring the balance reliability of the power system in terms of RES integration are presented. The installation of charging stations for electric vehicles or use of hydrogen technologies and modern storage systems can provide grid balance. In addition, decreasing the deviation of the current (real) value from the predicted value of power generation is a way to compensate for power unbalance.

引用

页数：6

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