III–V concentrator photovoltaic systems attain high efficiency through the use of series connected multi‐junction solar cells. As these solar cells absorb over distinct bands over the solar spectrum, they have a more complex response to real illumination conditions than conventional silicon solar cells. Estimates for annual energy yield made assuming fixed reference spectra can vary by up to 15% depending on the assumptions made. Using a detailed computer simulation, the behaviour of a 20‐cell InGaP/In0.01GaAs/Ge multi‐junction concentrator system was simulated in 5‐min intervals over an entire year, accounting for changes in direct normal irradiance, humidity, temperature and aerosol optical depth. The simulation was compared with concentrator system monitoring data taken over the same period and excellent agreement (within 2%) in the annual energy yield was obtained. Air mass, aerosol optical depth and precipitable water have been identified as atmospheric parameters with the largest impact on system efficiency. Copyright © 2012 John Wiley & Sons, Ltd.

A number of experimental studies on the dynamic behavior of the chemostat have shown that the specific growth rate does not instantaneously adjust to changes in the concentration of limiting substrate in the chemostat following disturbances in the steady state input limiting substrate concentration or in the steady state dilution rate. Instead of an instantaneous response, as would be predicted by the Monod equation, experimental studies have shown that the specific growth rate experiences a dynamic lag in responding to the changes in the concentration of limiting substrate in the culture vessel. The observed dynamic lag has been recognized by researchers in such terms as an inertial phenomenon and as a hysteresis effect, but as yet a systems engineering approach has not been applied to the observed data. The present paper criticizes the use of the hfonod equation as a dynamic relationship and offers as an alternative a dynamic equation relating specific growth rate to the limiting substrate concentration in the chemostat. Following the development of equations, experimental methods of evaluating parameters are discussed. Dynamic responses of analog simulations (incorporating the newly derived equations) are compared with the dynamic responses predicted by the Monod equation and with the dynamic responses of experimental chemostats.

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