Adaptive Neuro-Fuzzy Inference Systems as a Strategy for Predicting and Controling the Energy Produced from Renewable Sources

被引：29

作者：

Dragomir, Otilia Elena ^{[1
]}

Dragomir, Florin ^{[1
]}

Stefan, Veronica ^{[1
]}

Minca, Eugenia ^{[1
]}

机构：

[1] Valahia Univ Targoviste, Automat Comp Sci & Elect Engn Dept, Targoviste 130024, Romania

来源：

ENERGIES | 2015年 / 8卷 / 11期

关键词：

forecasting; neural network; Adaptive Neuro-Fuzzy Inference Systems; renewable energy sources; ERROR MEASURES; NETWORK;

D O I：

10.3390/en81112355

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：

The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to each modeling step, able to lead us to an optimal neural network forecasting tool. In order to underline the effects of users' decision making on the forecasting performance, in the second part of the article, two Adaptive Neuro-Fuzzy Inference System (ANFIS) models are tested and evaluated. Several scenarios are built by changing: the prediction time horizon (Scenario 1) and the shape of membership functions (Scenario 2).

引用

页码：13047 / 13061

页数：15

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