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.
Keywords: Artificial intelligence, Citical loads, Optimal scheduling, Power management, Residential photovoltaic systems.
About this chapter
Cite this chapter as:
C. Pradip, Murugananth Gopal Raj, S. John Alexis, A. Manickavasagam ;AI-Based Domestic Load Scheduling and Power Management for Renewable Energy Exporters, Marvels of Artificial and Computational Intelligence in Life Sciences (2023) 1: 104. https://doi.org/10.2174/9789815136807123010011
DOI https://doi.org/10.2174/9789815136807123010011 |
Publisher Name Bentham Science Publisher |