Chance Constrained Programming for Optimal Power Flow Under Uncertainty

By Hui Zhang, Pu Li. IEEE Transactions on Power Systems, 2011

280 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f48caeb71c26af8c46809221d708c8ebbe7eaabd

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Citations in the corpus

A tractable approximation of non-convex chance constrained optimization with non-Gaussian uncertainties (2015, methodology): “…and Möller 2003); robust control strategies (Feng, Dabbene, and Lagoa 2011; Lagoa, Li, and Sznaier 2005); power generation, transmission and supply (Zhang and Li 2010, 2011); finance and economics (Charnes and Cooper 1959; Rockafellar and Uryasev 2000; Wozabal 2012; Wozabal, Hochreiter, and…”
A Novel Probabilistic Optimal Power Flow Model With Uncertain Wind Power Generation Described by Customized Gaussian Mixture Model (2016, methodology): “Analogous CCOPF model is also constructed in [17] where the back-mapping and the linearization methods simplify the approximate probabilistic calculations during the nonlinear programming.”
Distributionally Robust Chance Constrained Optimal Power Flow with Renewables: A Conic Reformulation (2018, background): “Recently, including [4], [5], [8], [9], many studies tried to approximate the two-side chance constrained set (4) by two single-sided chance constraints.”
Distributionally Robust Chance-Constrained Optimal Power Flow With Uncertain Renewables and Uncertain Reserves Provided by Loads (2017, methodology): “CC-OPF problems to manage renewable energy and load uncertainty have been posed in [10]–[15], though none of this work considers load reserves or their uncertainty.”
Solving Probabilistic Optimal Power Flow Problem Using Quasi Monte Carlo Method and Ninth-Order Polynomial Normal Transformation (2014, unknown): “For the detailed introduction to the mathematical model of P-OPF, one can refer to [1], [7], and [23].”
Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty (2012, methodology): “To tackle this problem [50] proposes a simulation-based local optimization system consisting of an outer loop used to assess the validity of a control (and estimate its gradient) together with an inner loop that seeks to improve the control.”
A Novel Affine Arithmetic Method to Solve Optimal Power Flow Problems With Uncertainties (2014, methodology): “Finally, in [13], a Chance Constrained Programming (CPP) method is used to solve anOPF problemwith uncertain demand variables; in order”