Management of a PEM Electrolyzer in Hybrid Renewable Energy Systems - Fuzzy Modeling and Control: Theory and Applications - page 213

acquired by the research team through the operation of the test-bed Calderón et al.
( 2010 , 2011 ). Besides, several trial and error tests have been carried out to adjust
these parameters until reaching successful results. Triangular, trapezoidal, S-shaped
and Z-shaped membership functions have been used for input and output variables.
These ones conform to the desired design among those available in the Fuzzy Logic
toolbox of Matlab.
The input ranges depend on the variable. The narrowest range goes from 0 to 1
for SOC and the widest one goes from 0 to 1,000W/m 2

for solar irradiance. The

range of output signal is 0-8 5 V, interval where the electrolyzer behavior is linear.

Figure 12.5 presents the defined membership functions for all the involved variables.
The design of SOC membership functions is of paramount importance in the
design of the FLC and the consequent operation of the electrolyzer. The battery
bank smooths out the electrical power flow between the components of the hybrid
system. The battery is used for short-term energy storage, and also to deal with the
effects caused by instantaneous load, electrolyzer transients and wind energy peaks
(González et al. 2012 ).
The main gist of most power management strategies (PMSs) is that, above a
certain maximum threshold for the accumulator SOC, the electrolyzer may operate
using power provided by renewable energy units with occasional assistance from the
accumulator, and below a minimum accumulator SOC threshold, the operation of
the fuel cell will satisfy the load demand (Ipsakis et al. 2009 ).
The battery charge/discharge cycles ought to be minimized because its lifetime is
proportional to the number of cycles. In addition, the battery may be protected from
overcharging and deep discharges through a proper control law. For this reason, the
Low subset has been made larger to avoid operating on such low values to enlarge
the battery life span. Moreover, the highest hydrogen production takes place when
the SOC belongs to the subset High .
Two fuzzy partitions have been established for the solar irradiance, with Z and S
function types and Low and High labels respectively. This decision is based on the
criteria used in the previous stage. At that phase, a threshold of 500W/m 2 was used.
This value was experimentally determined, and was the minimum value under which
the modules were able to supply enough current to satisfy the load and electrolyzer
demand.
The generated hydrogen is stored, as exposed in the system description, in a set
of metal-hydride bottles, whose pressure acts as an input variable of the controller.
A pressure under the maximum level, 5 bar, indicates that there is available storage
capacity. Two fuzzy subsets, Low and High , with Z and S function types, respectively,
have been defined.
Three subsets have been defined, Low , Medium and High , with Z, triangular and
S function type respectively, for the PV module temperature. This description is
simple but effective. For example, under 20 ◦ C the temperature is considered low, so
the modules performance is high and the hydrogen production is favored.

.