UC Berkeley

To date, electric power systems are the most important technological achievement in the energy sector. Interconnected power systems require a careful operation to maintain supply stability and maintain efficient energy usage. Amid this complexity, two critical global transitions are needed: (1) moving away from greenhouse gases which negatively contribute to climate change; and (2) moving away from fossil fuels, which currently support transportation and heating systems.

Computer simulations are the only tools available to do the necessary research and development required to accomplish these goals. However, the practices and tools used by the electric power industry were developed for operational situations that are vastly different from current challenges for energy transition. Variable Renewable Energy uncertainty, fast varying resources, and fundamental changes to the energy transformation physics require an update to the operational and simulation practices.

This work started focusing on the simulation of future systems, and by the time it was written, it had become a dissertation on the practices needed for today's system. We discuss the requirements needed to improve scientific computing practices and conduct simulations more systematically when developing new operation models. The work has designed and implemented three software tools to develop simulations: the first includes PowerSystems.jl –– a software package that handles the data ingestion and processing required for simulations across multiple time scales. The second tool includes PowerSimulations.jl which resolves issues of model-limited choice when implementing operations simulations of large interconnected systems. The third tool includes PowerSimulations.jl, which is based on a formalization of the simulation of power system operations and provides a scalable computational platform. Third, PowerSimulationDynamics.jl which concentrates on the modeling of power systems dynamics with a strong focus on integrating Inverter Base Resources. PowerSystems.jl and PowerSimulations.jl both enable the development of a novel Automatic Generation Control model that can assess reserve deployments. Both tools are used to develop a Markovian Graph approach when integrating probabilistic forecasts into operators' risk assessments.

Finally, this dissertation investigates the simulation techniques that are needed for system dynamics and challenges the applicability long-held simulation practices. It seeks to uncover the theoretical elements of simulation needs for the future grid. Results from PowerSimulationDynamics.jl confirm this dissertation's hypotheses and demonstrates the effectiveness of the simulation approach in replicating existing models. Furthermore, the findings in this thesis critically showcase the capabilities to simulate dynamics systems accurately using model transformations that reduces computational complexity without loss of accuracy.