A survey of contextual optimization methods for decision-making under uncertainty

U Sadana, A Chenreddy, E Delage, A Forel… - European Journal of …, 2024‏ - Elsevier
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …

A survey of contextual optimization methods for decision making under uncertainty

U Sadana, A Chenreddy, E Delage, A Forel… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …

Prescribed robustness in optimal power flow

R Mieth, HV Poor - Electric Power Systems Research, 2024‏ - Elsevier
For a timely decarbonization of our economy, power systems need to accommodate
increasing numbers of clean but stochastic resources. This requires new operational …

Learning with adaptive conservativeness for distributionally robust optimization: Incentive design for voltage regulation

Z Liang, Q Li, J Comden, A Bernstein… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Information asymmetry between the Distribution System Operator (DSO) and Distributed
Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage …

Revealing decision conservativeness through inverse distributionally robust optimization

Q Li, Z Liang, A Bernstein… - IEEE Control Systems …, 2024‏ - ieeexplore.ieee.org
This letter introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to
infer the conservativeness level of a decision-maker, represented by the size of a …

Scheduling Distributed Energy Resources Under Limited Observability of Distribution Grids

V Kekatos, R Annin, MK Singh, J Qin - Available at SSRN 5077244, 2025‏ - papers.ssrn.com
Distributed energy resources (DERs) should be scheduled in a coordinated manner to
postpone or avoid costly capacity upgrades. Nonetheless, the pervasive lack of data at the …

Solving Optimal Power Flow on a Data-Budget: Feature Selection on Smart Meter Data

V Kekatos, R Annin, MK Singh, J Qin - arxiv preprint arxiv:2502.06683, 2025‏ - arxiv.org
How much data is needed to optimally schedule distributed energy resources (DERs)? Does
the distribution system operator (DSO) have to precisely know load demands and solar …

A Joint Energy and Differentially-Private Smart Meter Data Market

S Chhachhi, F Teng - arxiv preprint arxiv:2412.07688, 2024‏ - arxiv.org
Given the vital role that smart meter data could play in handling uncertainty in energy
markets, data markets have been proposed as a means to enable increased data access …

Analysis of Data Value in Stochastic Optimal Power Flow for Distribution Systems

M Ghazanfariharandi, R Mieth - arxiv preprint arxiv:2406.13148, 2024‏ - arxiv.org
The rise of advanced data technologies in electric power distribution systems enables
operators to optimize operations but raises concerns about data security and consumer …

An Uncertainty-Aware Data-Driven Predictive Controller for Hybrid Power Plants

M Desai, H Sharma, S Mukherjee… - arxiv preprint arxiv …, 2025‏ - arxiv.org
Given the advancements in data-driven modeling for complex engineering and scientific
applications, this work utilizes a data-driven predictive control method, namely subspace …