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Open Access Publications from the University of California

Scholarly Works (3 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2022)

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.

    Cover page: Modeling and Simulation of Electric Power Systems with Large Shares of Renewable Energy
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2020)
    Regional tree die-off events generate large quantities of standing dead wood, raising concern over catastrophic wildfire and other hazards. Governmental responses to tree die-off have often focused on incentivizing biomass energy production that utilizes standing dead trees removed for safety concerns. However, the full distribution of potential woody bioenergy feedstock after tree die-off has not been evaluated due to the complexities of surveying and precisely measuring large forested areas. In this paper, we present a novel method for estimating standing dead biomass at a fine spatial resolution that combines aerial survey data with forest structure maps. Using this method, we quantify biomass generated by the unprecedented tree die-off that occurred in California following a 4-year drought and widespread pest outbreaks. The results are used to estimate feasibly recoverable feedstock for energy production. We find that approximately 95.1 million bone-dry tons (BDT) of dead biomass resulted from 2012-2017 mortality, with a lower bound of 26.2 million BDT. In other words, of the aboveground live tree biomass in 2012, ~1.3-4.8% died by 2017. Of the standing dead biomass, 29% meets minimum constraints for potential cost-effective bioenergy feedstock. This proportion drops to as low as 15% in the most affected areas due to terrain slope, wilderness status, and other factors, highlighting the need to complement disposal via biomass energy with other strategies to mitigate the risks of the tree mortality crisis, which is likely to only become more severe over time due to climate change.
      Cover page: Characterization of the woody biomass feedstock potential resulting from California's drought.Creative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2022)
      With the growing penetration of converter-interfaced generation in power systems, the dynamical behavior of these systems is rapidly evolving. One of the challenges with converter-interfaced generation is the increased number of equations, as well as the required numerical timestep, involved in simulating these systems. Within this work, we explore the use of continuous-time echo state networks as a means to cheaply, and accurately, predict the dynamic response of power systems subject to a disturbance for varying system parameters. We show an application for predicting frequency dynamics following a loss of generation for varying penetrations of grid-following and grid-forming converters. We demonstrate that, after training on 20 solutions of the full-order system, we achieve a median nadir prediction error of 0.17 mHz with 95% of all nadir prediction errors within ±4 mHz. We conclude with some discussion on how this approach can be used for parameter sensitivity analysis and within optimization algorithms to rapidly predict the dynamical behavior of the system.
        Cover page: Continuous-time echo state networks for predicting power system dynamicsCreative Commons 'BY' version 4.0 license
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