3.8 Proceedings Paper

Artificial intelligence based forecast models for predicting solar power generation

期刊

MATERIALS TODAY-PROCEEDINGS
卷 5, 期 1, 页码 796-802

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.matpr.2017.11.149

关键词

Energy; Forecasting; Photovoltaic; Artificial Neural Network; Adaptive Neuro -Fuzzy Inference System

向作者/读者索取更多资源

Carbon discharges from monetary movement proceed to rise and India is the third-biggest emitter among individual nations. The Renewable Energy is the way forward and the problems in harvesting it should surmount through policy and technical approaches. The prime disadvantage with most of the Renewable Energy resources is their susceptibility to the whim and vagaries of nature and becoming a variable random source of power. Predicting the power from these variable power sources define and determine the operation of the system. In this paper, ANN and ANFIS based forecast model for predicting the PV Generation are presented. The designed forecast model is trained using historical data. The results of the proposed model are validated and compared by considering data set of PV power generating station. A simulation model of proposed system is developed in MATLAB to evaluate the system performance. (c) 2018 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据