Titlebook: Distributionally Robust Optimization and its Applications in Power System Energy Storage Sizing; Rui Xie,Wei Wei Book 2024 The Editor(s) (

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The Notebooks from Underground,n, the basics of probability and risk measures are summarized. Subsequently, optimization theories are reviewed, including convex optimization, conic programs and duality, multi-objective optimization, stochastic programming, and robust optimization. Some results are stated without proof and referen

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https://doi.org/10.1007/978-3-030-64210-5e, followed by an explanation of distributionally robust uncertainties, including worst-case expectations, robust chance constraints, and distributionally robust risk measures. Subsequently, a model of two-stage DRO is presented, which will serve as the main optimization framework applied to various

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Codetermination and Profit-sharing,second-order moments constraints. Moment-based DRO not only has the longest history among different DRO techniques but also is one of the most popular and mature ways to model the inexactness of empirical probability distribution for uncertainty-integrated optimization problems. This chapter focuses

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https://doi.org/10.1007/978-1-349-00475-1bjective optimization model to minimize load shedding Shortfall risk and total investment cost, taking into account the uncertainty of renewable energy generation and load. To account for the inaccuracy of empirical probability distributions, an ambiguity set of probability distributions is construc