Advances in Large-Scale Security-Constrained Economic Dispatch: Loss Modeling, Stochastic Dispatch, and Proxy Verification
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Zhao, Haoruo
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Abstract
Security-Constrained Economic Dispatch (SCED) optimizes generation resources to meet demand at minimal cost while maintaining grid reliability. This thesis presents novel optimization techniques for large-scale SCED problems that improve computational tractability and solution quality for modern power systems. Chapter 1 introduces a novel linear model for line loss outer approximation (LLOA) in DC optimal power flow, a critical component of SCED that models network constraints, providing an efficient and practical approach that balances accuracy and computational tractability for large-scale power systems. Chapter 2 develops a stochastic look-ahead dispatch (SLAD) framework for real-time energy markets, demonstrating that stochastic optimization is now computationally viable for five-minute market clearing, offering greater savings compared to the traditional deterministic formulation with flexible ramping products. Chapter 3 presents an optimization-based method for bound tightening in a rolling-horizon fashion for neural network verification and Chapter 4 introduces a compact formulation for optimality verification of optimization proxies for DC optimal power flow and knapsack problems.
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2025-04-29
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Dissertation