To enhance the economic efficiency and renewable energy consumption rate of industrial park integrated source-grid-load-storage systems, this paper investigates the integrated optimization of hydrogen energy storage systems. Addressing the tightly coupled nature of HES configuration and operational dispatch, this study proposes a co-optimization methodology, formulating the problem as a mixed-integer linear programming model aimed at minimizing daily operational costs. This model simultaneously optimizes the capacity configuration of equipment like electrolyzers and hydrogen storage tanks alongside their 24-h operational strategies, and is efficiently solved using the YALMIP toolbox and CPLEX solver within the MATLAB environment. A comparative analysis of scenarios with and without HES reveals that integrating an optimally configured HES system significantly reduces the park's weekly operational cost by 38.8% and achieves 100% local consumption of photovoltaic power, greatly eliminating curtailment. The findings confirm that the proposed optimization algorithm effectively determines the optimal HES configuration, significantly improving both the economic and environmental performance of the system, thereby providing a theoretical foundation and decision-making support for the low-carbon energy planning of industrial parks.