The purpose of this paper is to present a performance comparison between two maximum power point tracking algorithms. These two algorithms are incremental conductance (INC) which is an improved version of the perturb and observe algorithm, and the second algorithm is the Kalman filter applied to a photovoltaic system. In this work, a photovoltaic panel is modeled in PSIM tool; a Boost converter controlled by the maximum power point tracker is put between the PV panel and the load. Then the two algorithms are implemented by using C language and C block provided by PSIM tool. Next, several tests under stable and variable environmental conditions are made for the two algorithms, and results show a better performance of the Kalman filter compared to the INC in terms of response time, efficiency and steady-state oscillations.

中文翻译：

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卡尔曼滤波器与增量电导算法优化光伏能量的比较

本文的目的是介绍两种最大功率点跟踪算法之间的性能比较。这两种算法是增量电导（INC），它是微扰和观测算法的改进版本，第二种算法是应用于光伏系统的卡尔曼滤波器。由最大功率点跟踪器控制的Boost转换器置于PV面板和负载之间。然后使用PSIM工具提供的C语言和C块实现这两种算法。接下来，针对这两种算法在稳定和可变环境条件下进行了几次测试，结果表明，在响应时间，效率和稳态振荡方面，卡尔曼滤波器的性能优于INC。