The escalating demand of electrical power is mostly fulfilled by fossil fuels such as coal, oil, and natural gas, which are continuously subjected to price fluctuations. To reduce the burden on these sources and to counteract the environmental degradation, hybrid power systems (HPS) incorporating cleaner energy are drawings attention. Solar and wind power have emerged as promising alternatives owing to their abundant availability and the ability to provide energy at competitive costs. However, the volatile nature of these renewable sources poses challenges in power generation scheduling. Integrating large-scale energy storage with HPS may enhance the system's economic performance and voltage security. This study presents a comparative analysis of the performance among three HPSs, i.e., solar + thermal (ST), hydro + thermal (HT), and HT + PHS configurations while aiming at minimizing the generation costs and voltage deviations within an optimal power flow framework. The IEEE 30-bus system is used to validate the model, and a comparison is made among the Rao-3 algorithm and Flower Pollination Algorithm to identify the optimal generation schedules that satisfy the fitness functions efficiently.