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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y robust optimization by energy storage sizing problems.Brid.This book introduces the mathematical foundations of distributionally robust optimization (DRO) for decision-making problems with ambiguous uncertainties and applies them to tackle the critical challenge of energy storage sizing in renewab

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Codetermination and Profit-sharing, and mature ways to model the inexactness of empirical probability distribution for uncertainty-integrated optimization problems. This chapter focuses on the moment-based DRO, typical moment-based ambiguity sets are summarized, the reformulation methods are explained, and finally, the moment-based DRO incorporating unimodality is also introduced.

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https://doi.org/10.1007/978-3-030-17847-5n about what a Wasserstein-distance ambiguity set should be like. Subsequently, Wasserstein-distance ambiguity sets of discrete and general probability distributions are both defined, with discussions about the parameter choice. Finally, the reformulation methods of worst-case expectations and robust chance constraints are introduced.

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https://doi.org/10.1007/978-1-349-00475-1m into bi-objective linear programming (LP). According to the theory of parametric LP, it is explained that the Pareto frontier is piecewise affine, and an algorithm for solving the analytical expression of the Pareto frontier is proposed. This chapter introduces the work in Xie et al. (.).

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https://doi.org/10.1007/978-1-349-01916-8ibutionally robust chance-constrained program for the optimal sizing problem. This is then reformulated into a manageable linear programming problem through conservative approximation. This chapter introduces the work in Guo et al. (.).

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