Comparative Study between Wind and Fuel Cell by Using Fuzzy Logic Control
C.A. Pradeep Kumar1, A. Benuel Sathish Raj2
1C.A. Pradeep Kumar, BE Degree from Park College of Engineering & Technologies, Anna University, (Tamil Nadu), India.
2A. Benuel Sathish Raj, B.E Degree from Park College of Engineering & Technologies, Anna University, (Tamil Nadu), India.
Manuscript received on January 22, 2014. | Revised Manuscript received on February 15, 2014. | Manuscript published on February 28, 2014. | PP: 292-298 | Volume-3, Issue-3, February 2014. | Retrieval Number: C2704023314/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Due to ever increasing energy consumption, rising public awareness of environmental protection, and steady progress in power deregulation, alternative (i.e., renewable and fuel cell based) distributed generation (DG) systems have attracted increased interest. Wind and photovoltaic (PV) power generation are two of the most promising renewable energy technologies. Fuel cell (FC) systems also show great potential in DG applications of the future due to their fast technology development and many merits they have, such as high efficiency, zero or low emission (of pollutant gases) and flexible modular structure. This study presents different power management strategies of a stand-alone hybrid power system and controlled by using fuzzy logic control. The system consists of two power generation systems, a wind turbine and a proton exchange membrane fuel cell (PEMFC). Wind turbine is the main supply for the system, and the fuel cell performs as a backup power source. Different energy sources in the system are integrated through an AC bus. Therefore, continuous energy supply needs energy storing devices. The state of charge (SOC), charge-discharge currents are affecting the battery energy efficiency. The control algorithm is simulated using Matlab-Simulink.
Keywords: Wind, Fuel cell, Fuzzy, Dynamic Simulation, MAT LAB Simulink modeling.