Micro-Grid Renewable Energy Integration and Operational Optimization for Smart Grid Applications Using a Deep Learning

IF 1.7 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Components and Systems Pub Date : 2024-03-04 DOI:10.1080/15325008.2023.2296960

Hemlata Gangwar, Syam Machinathu Parambil Gangadharan, Leena Daniel, B. Srinivasa Kumar, P. Hariramakrishnan, G. Ramkumar, M. Arunkumar, P. Ganeshan, Ahmad A. Ifseisi

引用次数: 0

Abstract

The conceptual prediction approaches for solar energy and Photovoltaic energy are thoroughly reviewed in this work. Employing enhanced gated recurrent units (GRUs) and recurrent neural networks (RN...

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利用深度学习实现智能电网应用中的微电网可再生能源集成和运行优化

这项工作对太阳能和光伏能源的概念预测方法进行了全面回顾。采用增强型门控递归单元（GRUs）和递归神经网络（RN...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Electric Power Components and Systems 工程技术-工程：电子与电气

CiteScore

2.70

自引率

6.70%

发文量

审稿时长

7.2 months

期刊介绍： Electric Power Components and Systems publishes original theoretical and applied papers of permanent reference value related to the broad field of electric machines and drives, power electronics converters, electromechanical devices, electrical equipment, renewable and sustainable electric energy applications, and power systems. Specific topics covered include: -Electric machines- Solid-state control of electric machine drives- Power electronics converters- Electromagnetic fields in energy converters- Renewable energy generators and systems- Power system planning- Transmission and distribution- Power system protection- Dispatching and scheduling- Stability, reliability, and security- Renewable energy integration- Smart-grid and micro-grid technologies.