Abstract
In photovoltaic (PV) water pumping systems, a maximum
power point tracking (MPPT) controller is extremely
important. Since PV generators exhibit nonlinear I-V
characteristics and their maximum power point varies with
solar insolation. Therefore, the MPPT controller optimises the
solar energy conversion by ensuring that the PV generator
runs at the maximum power point at all times under different
illumination conditions. In this paper, a new artificial neural
network (ANN) based searching algorithm is proposed for
maximum power point tracking (MPPT). The system is
composed of solar array, buck converter and centrifugal pump
load driven by a permanent magnet DC motor. The proposed
ANN controller uses the output power of the PV generator
and speed of the DC motor as input signals and generates the
pulse width modulation (PWM) control signal to adjust the
operating duty ratio of a buck converter to match the load
impedance to the internal impedance of the PV array; thus
maximizing the motor speed and the water discharge rate of a
centrifugal pump. A complete dynamic simulation of the
system is developed in MATLAB/SIMULINK to demonstrate
the feasibility of the ANN control scheme under different
sunlight insolation levels. The results obtained verify that the
proposed ANN controller shows a significant improvement in
the power extraction performance under different sunlight
conditions, when compared with a directly-connected PV generator
energized pumping system. Moreover, the
simulation results match the calculated improvement.
power point tracking (MPPT) controller is extremely
important. Since PV generators exhibit nonlinear I-V
characteristics and their maximum power point varies with
solar insolation. Therefore, the MPPT controller optimises the
solar energy conversion by ensuring that the PV generator
runs at the maximum power point at all times under different
illumination conditions. In this paper, a new artificial neural
network (ANN) based searching algorithm is proposed for
maximum power point tracking (MPPT). The system is
composed of solar array, buck converter and centrifugal pump
load driven by a permanent magnet DC motor. The proposed
ANN controller uses the output power of the PV generator
and speed of the DC motor as input signals and generates the
pulse width modulation (PWM) control signal to adjust the
operating duty ratio of a buck converter to match the load
impedance to the internal impedance of the PV array; thus
maximizing the motor speed and the water discharge rate of a
centrifugal pump. A complete dynamic simulation of the
system is developed in MATLAB/SIMULINK to demonstrate
the feasibility of the ANN control scheme under different
sunlight insolation levels. The results obtained verify that the
proposed ANN controller shows a significant improvement in
the power extraction performance under different sunlight
conditions, when compared with a directly-connected PV generator
energized pumping system. Moreover, the
simulation results match the calculated improvement.
Original language | English |
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Title of host publication | 3rd Renewable Power Generation Conference (RPG 2014) |
Place of Publication | Naples |
Publisher | IET |
DOIs | |
Publication status | Published - 24 Sept 2014 |
Event | 3rd Renewable Power Generation Conference, RPG 2014 - Naples, UK United Kingdom Duration: 24 Sept 2014 → 25 Sept 2014 |
Conference
Conference | 3rd Renewable Power Generation Conference, RPG 2014 |
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Country/Territory | UK United Kingdom |
City | Naples |
Period | 24/09/14 → 25/09/14 |