The three-anchor buoy comprehensive observation platform serves as an efficient tool for achieving comprehensive, three-dimensional ocean monitoring. However, the uncertainty of the photovoltaic power supply system in the ocean monitoring environment gives rise to issues such as inadequate power supply and battery overcharging/overdischarging, thereby increasing both maintenance costs and frequency. Therefore, this paper proposes an energy management system for real-time scheduling of observation frequency based on battery state of charge. The Python-based buoy energy management verification model was constructed to validate the efficacy of the proposed energy management strategy. The findings demonstrated that the monitoring frequency of the buoy could be autonomously adjusted based on battery state of charge, enabling maintenance of a battery state of charge level around 0.5 during periods of insufficient light in winter, while ensuring a stable observation frequency of 4–5 times per day.