Abstract: The increasing power load year by year has significantly enhanced the issue of peak valley difference in power load, thereby emphasizing the importance of fully utilizing the peak and valley filling capacity offered by battery energy storage systems. In this paper, a Quadratic programming energy storage optimization regulation strategy is proposed considering the suppression of battery charging and discharging times. The main ideas are as follows: 1) The Quadratic programming method is utilized to track the daily load fluctuation and preliminarily plan the charging and discharging power of the battery energy storage system. 2) The upper and lower power limits are set and dynamic iteration is conducted according to the comparison between the real-time computing battery charging and discharging times and the maximum allowable charging and discharging times. 3) The battery energy storage charge and discharge power, as well as the load power optimized by Quadratic programming, are dynamically partitioned based on the upper and lower power limits of dynamic iteration. This strategy shapes and restrains the charge and discharge power curve, thus effectively reducing the number of battery charges and discharges. A systematic simulation analysis is conducted on four typical daily load data of a certain power line in Zunyi, Guizhou, so as to verify the feasibility of this method. The experimental results demonstrate that this method further suppresses the charging and discharging times of the battery energy storage system under the premise of Quadratic programming optimization regulation, playing an important role in battery health control.