Management of a PEM Electrolyzer in Hybrid Renewable Energy Systems - Fuzzy Modeling and Control: Theory and Applications - page 208

system for HPS. Changes in the operation parameters and algorithm and its appli-
cation to the plant in real time is a vital feature when researching about control
strategies.
Different control techniques have been studied for HPS such as control based on
the battery state of charge (Ipsakis et al. 2009 ; Uzunoglu et al. 2009 ), logical control
(El-Shatter et al. 2006 ; Khan and Iqbal 2009 ), sliding mode control (Valenciaga and
Puleston 2005 ; Battista et al. 2006 ) optimal control based on genetic algorithms
(Dufo-López et al. 2007 ), predictive control (Zervas et al. 2008 ;Wuetal. 2009 ), and
Petri nets (Figueiredo and Sá da Costa 2008 ;Luetal. 2010 ; Calderón et al. 2010 ).
Moreover, during last years Fuzzy Logic Control (FLC) has become object of
study in the field of management and control of HPS. The main advantages of fuzzy
logic are the fast decision capability and that historical data and mathematical mod-
els are not required. Erdinc and Uzunoglu ( 2011 ) indicate the usefulness of these
features and the suitable structure of fuzzy logic for the control of power systems.
Chen et al. ( 2013 ) consider that fuzzy logic offers a practical way for designing
nonlinear control systems capable to manage nonlinear systems as hybrid wind-
solar-hydrogen systems. Courtecuisse et al. ( 2010 ) propose a methodology to design
a fuzzy logic based supervision of hybrid renewable energy systems. They allege that
fuzzy logic is well adapted to deal with the complexity of the system, the difficulty
to obtain or use accurate models, as well as the difficulty to predict the behavior of
the renewable sources.
The growing attention received by FLC is demonstrated by the numerous authors
who have successfully applied it to hybrid renewable energy systems: (Jeong et al.
2005 ; El-Shatter et al. 2006 ; Erdinc andUzunoglu 2011 ;Erdincetal. 2012 ; Hajizadeh
and Golkar 2007 ; Bilodeau and Agbossou 2006 ; Stewart et al. 2009 ;Lietal. 2011 ;
Kyriakarakos et al. 2012 ; Chávez-Ramírez et al. 2013 ; Safari et al. 2013 ).
Furthermore, several authors have reported successful applications of OLE for
Process Control (OPC), communication between Matlab and Simulink environment
and a S7 Siemens Programmable Logic Controller (PLC) (Lieping et al. 2007 ; Linlin
et al. 2011 ; Manjunath and Raman 2011 ; Mingliang et al. 2011 ).
In this chapter, a control scheme based on a six input and one output fuzzy logic
controller is proposed. It has been designed and tested to drive an electrolyzer in
an experimental hybrid renewable energy system. Global management of this pro-
totype is carried by a PLC. The fuzzy controller runs in Simulink and the real-time
data exchange with the PLC goes through OPC technology. The rest of the chapter
is organized as follows. Section 12.2 describes the renewable energy system. The
developed FLC is analyzed in Sect. 12.3 . Section 12.4 focuses on the architecture of
real-time control by means of the PLC. In Sect. 12.5 , the results of the hybrid test-bed
under real conditions are shown. Finally, some conclusions are drawn in Sect. 12.6 .
12.2 System Description
The prototype of the hybrid renewable energy system with hydrogen energy storage
comprises a photovoltaic (PV) generator, a wind turbine generator, a battery set,
an electrolyzer, a metal-hydride system for hydrogen storage, a fuel cell and a