TY - GEN
T1 - Maximum power point tracking for Photovoltaic systems using fuzzy logic and artificial neural networks
AU - Alabedin, A. M.Zein
AU - El-Saadany, E. F.
AU - Salama, M. M.A.
PY - 2011
Y1 - 2011
N2 - The maximum power point tracking (MPPT) aims to increase the efficiency of Photovoltaic (PV) systems by operating their PV panels at the optimum power point. Many strategies have been introduced to achieve this objective. However, these strategies vary in their tracking performance, computational complexity and cost. The rapid changes in environmental conditions and the nonlinearity in the current-voltage (I-V) characteristics of PV panels make the tracking problem complex. This paper presents the design of two controllers; one based on fuzzy logic, and the other based on artificial neural networks. Fuzzy logic controllers are simple, easy to implement, and does not need knowledge of the mathematical model of the system. Neural networks are known to be universal approximators for non-linear dynamic system. Thus, they can be used to estimate the reference parameters of the maximum power point. The two controllers are simulated under variable environmental factors to study their tracking performance.
AB - The maximum power point tracking (MPPT) aims to increase the efficiency of Photovoltaic (PV) systems by operating their PV panels at the optimum power point. Many strategies have been introduced to achieve this objective. However, these strategies vary in their tracking performance, computational complexity and cost. The rapid changes in environmental conditions and the nonlinearity in the current-voltage (I-V) characteristics of PV panels make the tracking problem complex. This paper presents the design of two controllers; one based on fuzzy logic, and the other based on artificial neural networks. Fuzzy logic controllers are simple, easy to implement, and does not need knowledge of the mathematical model of the system. Neural networks are known to be universal approximators for non-linear dynamic system. Thus, they can be used to estimate the reference parameters of the maximum power point. The two controllers are simulated under variable environmental factors to study their tracking performance.
UR - https://www.scopus.com/pages/publications/82855177908
U2 - 10.1109/PES.2011.6039690
DO - 10.1109/PES.2011.6039690
M3 - Conference contribution
AN - SCOPUS:82855177908
SN - 9781457710018
T3 - IEEE Power and Energy Society General Meeting
BT - 2011 IEEE PES General Meeting
T2 - 2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future
Y2 - 24 July 2011 through 28 July 2011
ER -
