With
the growing demand for energy and increasing environmental
concerns, there is an imminent requirement for a paradigm shift from
nonrenewable sources toward renewable sources for energy generation.
Among the emerging technologies, the photovoltaic (PV) system holds
immense promise due to the abundant availability of the source (solar
irradiance), low installation cost, and ease of scale-up. It is known
that the efficiency of a PV system, not-withholding its dependency
on other factors, decreases with an increase in the module temperature.
The module temperature in turn is a function of disturbances, especially,
intermittent weather variables, solar irradiance, ambient temperature,
and wind speed. In this work, we propose, develop, and design a module
temperature control system consisting of an adaptive model predictive
controller that manipulates the flow rate of a water coolant flowing
on the module. The controller design is based on (i) an expression
for computing the PV efficiency as a function of time and (ii) an
improvised comprehensive thermal model that accounts for the effects
of disturbances and the coolant flow on the module temperature. The
adaptive model predictive controller is tuned based on a trade-off
between achieved control error and control effort. Further, an optimal
set-point (for the module temperature) that achieves a desirable trade-off
between the average power gain (due to temperature control) and the
power consumed (due to coolant pump) is determined through numerical/simulation
studies. In silico simulations on two geographical regions demonstrate
that the proposed control scheme results in a maximum improvement
in efficiency of nearly 10%.