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Using a fuzzy agent in modeling lead-acid battery operating in grid connected wind energy conversion systems

Ibrahim, M and Khairy, A and Hagras, H and Zaher, M (2010) Using a fuzzy agent in modeling lead-acid battery operating in grid connected wind energy conversion systems. In: UNSPECIFIED, ? - ?.

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Abstract

This paper investigates the performance of a leadacid battery in a grid connected wind energy generator system. Wind energy has gained much credit in the past two decades as a sustainable energy resource. The penetration of wind energy generators into the electric utility grids is expected to increase to about 1.5 TW within the present decade. Due to the intermittent nature of the wind, there have been serious concerns about reliability and operation of the utility power grids. Battery storage is suggested to compensate wind power fluctuations and smooth the power fed to the utility grids. The battery storage in such applications has dynamic operating conditions and is subjected to different ageing mechanisms which stimulate the capacity degradation and hence influence the feasibility of their implementation. This paper investigates the implementation of fuzzy agent modeling as a powerful technique to estimate the dynamic and sophisticated electrochemical battery degradation mechanisms. Accordingly, the real behavior, the feasibility of the battery and its effect on wind power fed to the utility grid can be judged. The investigated system is simulated using real measurement data of a 600 kW rated power wind turbine. The simulation results of different battery capacities show that the integration of the battery storage has compensated the fluctuations of the generated wind power and smoothed the power fed to the utility grid. Moreover, the fuzzy agent has generated very important information about the battery degradation and available capacity (in this case of about 85%) after one year of operation. © 2010 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 18 Sep 2013 09:59
Last Modified: 23 Jan 2019 00:17
URI: http://repository.essex.ac.uk/id/eprint/4724

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