AI-Based Domestic Load Scheduling and Power Management for Renewable Energy Exporters-Reference-Cited by-同舟云学术

AI-Based Domestic Load Scheduling and Power Management for Renewable Energy Exporters

Published:2023-09-18 Issue: Volume: Page:104-120
ISSN:
Container-title:Marvels of Artificial and Computational Intelligence in Life Sciences
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Author:

Pradip C.¹,Gopal Raj Murugananth²,John Alexis S.³,Manickavasagam A.²

Affiliation:

1. Department of Electrical and Electronics Engineering, NSS College of Engineering, Palakkad, Kerala, India

2. Department of Electrical and Electronics Engineering, Ahalia School of Engineering and Technology, Palakkad, Kerala, India

3. Department of Mechanical Engineering, Ahalia School of Engineering and Technology, Palakkad, Kerala, India

Abstract

Residential Photovoltaic systems (RPV) are flattering and widespread among customers due to government policies. The power sources available in RPV include a grid, a PV system and a battery. The principal cost of residential photovoltaic systems is a bit high. When more power is exported, the customer who has installed it will export more power for their benefit. It can be achieved by efficiently scheduling the three sources and managing the power export. Artificial Intelligence-based systems can effectively take care of it because they provide effective decision-making solutions.

Publisher

BENTHAM SCIENCE PUBLISHERS

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