Abstract

Reliable, affordable access to electrical power is a requirement for almost all aspects of developed societies. Challenges associated with reducing carbon emissions has led to growing interest in nuclear-renewable hybrid energy systems (N-RHES). Much work has already been done in suggesting and analyzing various N-RHES using a variety of optimization techniques and assumptions. This work builds upon previous techniques for simultaneous combined design and dispatch optimization (CDDO) for hybrid energy systems (HES). The first contribution of this work is the development and application of sensitivity analysis tailored to the combined design and dispatch optimization problem. This sensitivity analysis cover uncertainty in design parameters, time series and dispatch horizon lengths. The result is a deeper insight into which sources of uncertainty are most important to account for and how the uncertainty around these sources can be quantified. The second contribution of this work is a novel multi-scale optimization algorithm for the combined HES design and dispatch optimization. This algorithm supports optimization of nonlinear models over very long-time horizons. This method is based on a multi-dimensional distribution of the optimal capacities for a system as determined by a large number of combined design and dispatch optimization problems each covering a subset of the complete time horizon. This method shows good agreement with the direct solution to multiple example systems and is then used to solve a problem with a dispatch horizon length 112.5 times longer than is solvable directly. The third contribution of this work is the application of the novel multi-scale method to three HES. Each of the application systems is used to demonstrate the strengths, validation and applicability of the developed algorithm to a wide range of possible HES/NHES designs.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering; Chemical Engineering

Rights

https://lib.byu.edu/about/copyright/