Decarbonization goals, competitive energy markets, declining technology costs, and tax credits have stimulated significant growth in low-carbon energy resources, especially wind and solar, which increases variability of energy dispatched. Energy storage and transmission can address this variability by offering balancing, reliability, and flexibility services, but it is important to address the many interdependencies between generation, storage, and transmission when developing reliable and optimal portfolios. This is especially true as generation and transmission infrastructure is expensive and long-lived. Sub-optimal planning may lead to lock-in of both investments and associated emissions. This project explores tradeoffs and drivers between new generation and storage investments and new transmission network investments by using a coordinated expansion planning approach. Traditional planning first identifies least-cost generation expansion plans, and then least-cost transmission additions, potentially missing other cost-effective options. Coordinated expansion planning co-optimizes generation and transmission (with storage), while also capturing system capacity and flexibility needs. Additionally, traditional planning is often based on deterministic modeling approaches that use a fixed set of inputs, with uncertainty assessed exogenously through scenario and/or sensitivity analyses. The coordinated expansion planning approach used in this project offers an opportunity to study the tradeoffs between generation, storage, and transmission investments using a novel endogenous representation of uncertainty, which as results show can change planning outcomes. The Midcontinent Independent System Operator's power system is selected as the case study, and optimal portfolios are evaluated under alternative natural gas price and carbon policy futures.