(184h) Non-Linear Model Predictive Control of Module Temperature in Photovoltaic System
AIChE Annual Meeting
2018
2018 AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Control
Monday, October 29, 2018 - 3:30pm to 5:00pm
With the growing demand in energy and environmental concerns, a paradigm shift towards
renewable energy sources is imminent. Among the existing renewable resources, solar
technology is the most promising one, because of its abundance, relatively low installation cost
and ease of scale-up in the plant capacity. One of the prominent technologies based on solar
energy is built on the photovoltaic (PV) cell, which transforms the solar energy either into
electrical or heat energy. A PV module is a large combination of cells that are connected either
in series or parallel in order to meet the power demand. The efficiency of the PV module is
highly dependent on module temperature which is sensitive to solar irradiance and ambient
temperature. The effect of module temperature on voltage and power is shown in Figure 1.
As evident from Figure 1, the efficiency of PV module decreases with increase in module
temperature, which is significantly influenced by the intermittent nature of insolation and
ambient temperature. Since it is not possible to adjust the levels of these disturbances, a
cooling system is necessary to control the module temperature [2]. The success of such a
cooling system critically rests on the development of an accurate model that explains
the effect of solar irradiance and ambient temperature on the module temperature.
Ilhan [3] proposed a spiral heat exchanger placed on the surface of the panel in order to provide
active cooling. Teo [4] proposed an active air cooling system attached to the back of the PV
panel. The few works that appear in the reported literature control the module temperature by
use of ON/OFF controller for the coolant system. On the other hand, the use of
well-established model-predictive control (MPC) framework for improving the power efficiency
is quite attractive.
In this work, we first present a revised nonlinear model of PV/thermal and coolant system that
explains the dependency of insolation and ambient temperature on the module temperature.
Subsequently a nonlinear model predictive control (NL-MPC) strategy is developed which
determines the optimal coolant flow rate so as to control the panel temperature in the presence
of operating constraints.
It may be noted that an NL-MPC strategy was implemented by Eduardo [1] for a solar
trough, where the objective is to control the temperature of the oil flow in order to improve the
solar thermal plant efficiency.
The proposed NL-MPC architecture for the PV cell is shown in Figure 2. Simulation results
show (to be reported in the full-length paper) that the proposed NL-MPC for the PV module
results in a significant improvement in PV/thermal system efficiency. References
[1] Eduardo F. Camacho and A. J. G. Model predictive control in solar trough plants: A review. IFAC-PapersOnLine, 48(23):278 – 285, 2015. 5th IFAC Conference on Nonlinear Model Predictive Control NMPC 2015.
[2] Dong-J. Kim, Dae H. Kim, Sujala Bhattarai, and Jae-H. Oh. Simulation and model validation of the surface cooling system for improving the power of a photovoltaic module. Journal of Solar Energy Engineering, 133(4):041012, 2011.
[3] lhan C., Ali E. G., Hsamettin D., and Bahri A. Cooling of a photovoltaic module with temperature controlled solar collector. Energy and Buildings, 72:96 – 101, 2014.
[4] H.G. Teo, P.S. Lee, and M.N.A. Hawlader. An active cooling system for photovoltaic modules. Applied Energy, 90(1):309 – 315, 2012. Energy Solutions for a Sustainable World, Special Issue of International Conference of Applied Energy, ICA2010, April 21-23, 2010, Singapore.