@inbook{de8dd657a9af43b2bc01810ea49ecfad,
title = "Predictive control of energy management system for fuel cell assisted photo voltaic hybrid power system",
abstract = "Distributed generation systems also known as hybrid power systems which involve renewable energy sources are extensively used due to their efficiency and green interface. Considering the varying environmental conditions, these systems are prone to many disadvantages and limitations. In order to overcome these constraints, intelligent techniques which can achieve steady process and power balance are to be implemented. This paper provides an intelligent control using fuzzy inference system and energy management algorithm for Fuel cell assisted PV Battery system. The supervisory control was implemented to achieve utmost feasible efficiency despite varying conditions such as irradiance and Hydrogen levels. With Levelized cost being adapted, an efficient energy management system attributes for even power distribution throughout the day can be implemented. Our thought process was demonstrated, and final software interface was simulated using MATLAB/Simulink to obtain results which confirm the effectiveness of the developed system.",
keywords = "Fuzzy logic controller, Energy management, Inference systems, MPPT, PVFC hybrid system, Fuel cell",
author = "Kurukuru, \{V.S. Bharath\} and M.A. Khan",
year = "2019",
doi = "10.1007/978-981-13-1819-1\_24",
language = "English",
isbn = "978-981-13-1818-4",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "245--254",
booktitle = "Applications of Artificial Intelligence Techniques in Engineering",
address = "Germany",
}