Data-driven stochastic optimization for cyber-physical system risk management : smart power grids with renewable energy
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Authors
Yi, Yuan
Issue Date
2018-12
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Industrial and management engineering
Alternative Title
Abstract
Unit commitment decision is the fundamental operational decision for smart grids. Yet, the inherent unpredictable nature on both supply and demand sides, and our limited prior information of underlying input models lead to both stochastic and input uncertainty. To provide reliable and cost-efficient operational unit commitment decisions, we propose a new data-driven stochastic unit commitment model to hedge against the input and stochastic uncertainties simultaneously. Built on that, we develop a novel parallel optimization-based framework that further controls the finite sampling error caused by sample average approximation.
Description
December 2018
School of Engineering
School of Engineering
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY