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Intelligent Control of the Energy Generation Systems

Intelligent Control of the Energy Generation Systems

Nicu Bizon
Copyright: © 2010 |Pages: 57
ISBN13: 9781605667379|ISBN10: 1605667374|EISBN13: 9781605667386
DOI: 10.4018/978-1-60566-737-9.ch002
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MLA

Bizon, Nicu. "Intelligent Control of the Energy Generation Systems." Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection, edited by Kostas Metaxiotis, IGI Global, 2010, pp. 40-96. https://doi.org/10.4018/978-1-60566-737-9.ch002

APA

Bizon, N. (2010). Intelligent Control of the Energy Generation Systems. In K. Metaxiotis (Ed.), Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection (pp. 40-96). IGI Global. https://doi.org/10.4018/978-1-60566-737-9.ch002

Chicago

Bizon, Nicu. "Intelligent Control of the Energy Generation Systems." In Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection, edited by Kostas Metaxiotis, 40-96. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-737-9.ch002

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Abstract

In this book chapter are analyzed the Energy Generation System (EGS) topologies, used in automotive systems, and the grid inverter systems, with intelligent control algorithms (fuzzy logic controller, genetic algorithm, etc.). The EGS blocks are modelled using Matlab & Simulink ® program. A necessary block is the EGS power interface between the fuel cell stack and the batteries stack, usually a boost converter that uses a Peak Current Controller (PCC) with a Boundary Control with Current Taper (BCCT). The control law is a function of fuel cell current and battery voltage, which prevents the “boiling” of the batteries. The control objective for this power interface is also the fuel cell current ripple minimization, used in order to improve the fuel cell stack life cycle. Clocked and non-clocked control methods are tested in order to obtain a small fuel cell current ripple, better a dynamic response, and robustness against system uncertainty disturbances. The EGS behaviour is tested by bifurcation diagrams. It is shown that performances increase if the control law is a function that depends by the fuel cell current ripple and battery voltage. The clocked PCC using the BCCT 2-D law is implemented by a fuzzy logic controller. The power load dynamic is compensated using an ultracapacitors stack as a dynamic energy compensator, connected by a bi-directional converter to the batteries stack bus. Small fuel cell current ripple using compact batteries and ultracapacitors stacks will be obtained by the appropriate design of the control surface, using an Integrated Fuzzy Control (IFC) for both power interfaces.

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