The University of California, Irvine (UCI) uses a 19 MW natural gas combined cycle (NGCC) to provide nearly all campus energy requirements. Meanwhile, the University of California system has committed to achieving carbon neutrality at all facilities by 2025. This has resulted in an influx of new energy efficiency and onsite solar generation, increasing the duration of NGCC part load operation. In addition, the shift towards carbon neutrality has resulted in the pursuit of renewable natural gas via anaerobic digestion to replace conventional fossil fuels. The combination of other sources of renewable generation and the shift towards more expensive fuels has created the need to boost NGCC part load performance. This work focuses on the methods used at UCI to explore the NGCC operating space in order to optimize part-load performance. In this work, a physical gas turbine and heat recovery steam generator model are developed and used with an exhaustive search optimization method to predict maximum part load plant efficiency. NGCC control elements considered in this work include gas turbine inlet guide vane modulation and changing combustor outlet temperature. This optimization was also used to explore replacing the current engine with a two-shaft or smaller gas turbine. Results indicate that there are some possible benefits with increased modulation of inlet guide vanes, but the largest efficiency gains are achieved when allowing the compressor to operate at variable speed. Shifting towards a smaller engine could also enable more consistent full power operation, but must be paired with additional resources in order to meet the campus demand.