Extremum Seeking MPPT Against Commercial Power Optimizers

Every solar panel in a real installation is different from its neighbours at any given moment. Dust, partial shadow, aging, and temperature gradients all cause individual panels to produce less than their rated peak, and by different amounts at the same time. Getting the maximum available power out of the array as a whole is a harder problem than it looks. Commercial optimizers usually rely on per-panel MPPT loops, such as Perturb and Observe approaches, where each optimizer tracks only its own panel and adjusts its duty cycle without knowledge of neighboring panels. In a series-connected string, all converters share the same dc bus current, so changes in one converter can affect the whole string. This creates coupling, unpredictable transient behavior, and condition-dependent convergence during partial shading, temperature changes, and module mismatch. Extremum Seeking (ES) is a model-free real-time optimization technique that does not require knowledge of the power surface. A multivariable ES design treats the entire panel array as a single optimization problem, moving all duty cycles together toward the global maximum power point. Newton-based ES additionally estimates the Hessian, making convergence rate user-assignable and less dependent on irradiance, temperature, or shading conditions. The project asks whether this theoretical advantage holds up on real hardware. The project has access to physical Luxor ECO LINE HALF CELL monocrystalline panels, including 440-460 W and 540-560 W variants, and infrastructure for controlled experiments such as partial shading, step irradiance changes, and module mismatch. Commercial optimizer specifications and measured field data from SolarEdge, Tigo, and Huawei installations serve as the benchmark.