Energy Management Strategy Using ANFIS Approach for Hybrid Power System

Renewable Energy Sources are the promising hopes of upcoming years as they are abundant in nature and available free of cost. In addition to this, these sources are pollution-free which makes them a perfect substitute for fossil fuels. A Hybrid Power System (HPS) is one that has multiple power generating sources like Photo Voltaic (PV) system, Wind turbine, Fuel cell, etc. interconnected to supply electric power for varying demand requirements with / without energy storage backup. This paper concentrates on the automation for control and integration of Renewable energy systems Viz. PV system, Solid Oxide Fuel Cell (SOFC) with Nickel-Metal-Hydride (Ni-MH) battery together with a variable load. The Proposed HPS mainly focuses on the use of PV which is 100% clean in nature with no toxic emissions on power generation. Here, the solar photovoltaic system with power extracting maximum by algorithm used as the major supply contributor in the HPS to meet with variable load demands. If there is a deficit of power supply from PV, the power from the Ni-MH battery / SOFC is utilized to meet the varying load demands. On the other hand, if there is excess supply from PV system, the excess energy will be stored in the Ni-MH battery. For efficient supply-demand balance, the HPS makes use of various control strategies namely Proportional Integral (PI) and Adaptive Neuro Fuzzy Inference System (ANFIS)