As a critical form of clean energy, solar photovoltaics (PV) have expanded rapidly in the United States, particularly in the electricity market operated by the Electric Reliability Council of Texas (ERCOT). Large-scale solar integration has played a positive role in displacing high-emission generation units and reducing system costs, yet its inherent intermittency and forecast uncertainty pose significant operational and economic challenges. Using high-frequency nodal panel data, this study systematically evaluates the impacts of large-scale PV generation on the Texas electricity market. The results indicate that, overall, solar integration contributes to cost reductions at the system level, but forecast errors and intermittency increase the demand for reserve capacity and ancillary services, thereby driving up system balancing costs. The policy implications of this study are threefold: first, optimizing PV siting and strengthening infrastructure investments—such as forecasting technologies, storage, and grid-enhancing equipment—are crucial to addressing regional disparities; second, the introduction of a dynamic cost assessment framework can support more precise ancillary service procurement strategies and reduce the operational burden of uncertainty. Overall, this study provides new empirical evidence on the effects of PV forecast uncertainty on electricity markets and offers policy guidance for maintaining both market efficiency and system reliability while advancing the decarbonization of the energy system.