AI-Based Domestic Load Scheduling and Power Management for Renewable Energy Exporters
- Authors: C. Pradip1, Murugananth Gopal Raj2, S. John Alexis3, A. Manickavasagam4
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View Affiliations Hide AffiliationsAffiliations: 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 4 Department of Electrical and Electronics Engineering, Ahalia School of Engineering and Technology, Palakkad, Kerala, India
- Source: Marvels of Artificial and Computational Intelligence in Life Sciences , pp 104-120
- Publication Date: September 2023
- Language: English
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.
Hardbound ISBN:
9789815136814
Ebook ISBN:
9789815136807
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