The classic Photovoltaic system maximum power point tracking technique cannot concurrently take into account the dynamic response speed and steady-state accuracy when the light intensity changes. To address this issue, a new composite variable step MPPT control algorithm is developed in this study. Based on the three-stage variable step incremental conductance method, the algorithm adds the Kalman filtering algorithm to pre-process the photovoltaic cells output signal, and uses a new calculation approach to adjust the variable step coefficient. As a result, the perturbation step can be automatically modified according to changes in the external environment, which resolves the issues with poor dynamic reaction speed when the classic variable step algorithm started and the light changed. Compared to conventional MPPT control algorithms, the improved MPPT strategy can be easily realized using a hardware control system since it has a simplified control logic and requires less data to be calculated. In this study, the hardware circuit of the enhanced MPPT control algorithm is built using the ESP32 as the primary control chip. This chip can be utilized in conjunction with the Internet of Things to enable remote monitoring of the solar power system’s operational state. According to test results, the algorithm can instantly detect the maximum power point in all lighting circumstances with tracking accuracy of up to 99.6% and a reduction in dynamic response time of the system to 0.12 s.