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This paper explores the advantages of extremum seeking (ES) for wind and solar energy applications. The experimental results are also provided for the photovoltaic system. ES is an attractive alternative to perturb and observe (P&amp;O) techniques for solving maximum power point tracking (MPPT) problems in wind and solar systems. As a model-free, real-time optimization approach, ES is well suited for systems with unknown dynamics or those that are affected by high levels of uncertainty or external dynamics, like wind turbines (WT) and PV systems. ES has the dual benefit of rigorously provable convergence and the simplicity of hardware implementation. In addition to a probing signal, the ES algorithm employs only an integrator, as well as optional high-pass and a low-pass filters. Finally, multivariable MPPT based on ES for PV systems are presented, and the validity of the proposed algorithms with experimental results are verified. Experimental results verify the effectiveness of the Newton-based MPPT versus its scalar and multivariable gradient-based counterparts.

Extremum Seeking for Wind and Solar Energy Applications