Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. In this thesis, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control energy systems in wholesale energy markets. Traditionally, energy systems are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between energy systems' bidding, scheduling, and control decisions and the energy market clearing and settlement processes, while incorporating operational uncertainties. We show the importance of understanding and quantifying complex resource-grid interactions, and how this framework can guide the design of future energy systems with case studies. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework creates abundant future research opportunities within the context of energy markets, e.g., advanced bidding, operation, and control strategies of energy systems. The framework is applicable to all energy technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).