This paper presents a new algorithm for tracking maximum power point in photovoltaic systems. This is a fast tracking algorithm, where an initial approximation of maximum power point is (MPP) quickly achieved using a variable step-size. Subsequently, the exact maximum power point can be targeted using any conventional method like the hill-climbing or incremental conductance method. Thus, the drawback of a fixed small step-size over the entire tracking range is removed, resulting in reduced number of iterations and much faster tracking compared to conventional methods. The strength of the algorithm comes from the fact that instead of tracking power, which does not have a one-to-one relationship with duty cycle, it tracks an intermediate variable /spl beta/, which has a monotonically increasing, one-to-one relationship. The algorithm has been verified on a photovoltaic system modeled in Matlab-Simulink software. The algorithm significantly improves the efficiency during the tracking phase as compared to a conventional algorithm. It is especially suitable for fast changing environmental conditions. The proposed algorithm can be implemented on any fast controller such as the digital signal processor. All the details of this study are presented.
[1]
Hartmut Hinz,et al.
A ripple-based maximum power point tracking algorithm for a single-phase, grid-connected photovoltaic system
,
1998
.
[2]
Robert L. Steigerwald,et al.
Microcomputer Control of a Residential Photovoltaic Power Conditioning System
,
1985,
IEEE Transactions on Industry Applications.
[3]
V. Fernão Pires,et al.
Teaching nonlinear modeling, simulation, and control of electronic power converters using MATLAB/SIMULINK
,
2002,
IEEE Trans. Educ..
[4]
Tsutomu Hoshino,et al.
Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions
,
1995
.
[5]
Juing-Huei Su,et al.
Learning feedback controller design of switching converters via MATLAB/SIMULINK
,
2002,
IEEE Trans. Educ..
[6]
Geoffrey R. Walker,et al.
Evaluating MPPT Converter Topologies Using a Matlab PV Model
,
2000
.