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We propose and analyze the application of statistical functional depth metrics for the selection of extreme scenarios in day-ahead grid planning. Our primary motivation is screening of probabilistic scenarios for realized load and renewable…

Machine Learning · Statistics 2025-05-13 Guillermo Terrén-Serrano , Michael Ludkovski

Accurate prediction of remaining useful life under creep conditions is essential for the structural reliability of high-temperature components in critical engineering systems. Traditional approaches based on deterministic parametric models…

Computational Engineering, Finance, and Science · Computer Science 2026-05-08 Victor Maudonet , Carlos Frederico Trotta Matt , Americo Cunha

Long-term reservoir management often uses bounds on the reservoir level, between which the operator can work. However, these bounds are not always kept up-to-date with the latest knowledge about the reservoir drainage area, and thus become…

Optimization and Control · Mathematics 2018-01-29 Thibaut Cuvelier , Pierre Archambeau , Benjamin Dewals , Quentin Louveaux

With an increasing need for more flexible mobility services, we consider an operational problem arising in the planning of Demand Adaptive Systems (DAS). Motivated by the decision of whether to accept or reject passenger requests in real…

Optimization and Control · Mathematics 2025-03-12 Benedikt Lienkamp , Mike Hewitt , Axel Parmentier , Maximilian Schiffer

Rolling origin forecast instability refers to variability in forecasts for a specific period induced by updating the forecast when new data points become available. Recently, an extension to the N-BEATS model for univariate time series…

Machine Learning · Computer Science 2025-01-22 Daan Caljon , Jeff Vercauteren , Simon De Vos , Wouter Verbeke , Jente Van Belle

Accurate forecasting is critical for reliable power grid operations, particularly as the share of renewable generation, such as wind and solar, continues to grow. Given the inherent uncertainty and variability in renewable generation,…

Applications · Statistics 2025-10-20 Alireza Moradi , Mathieu Tanneau , Reza Zandehshahvar , Pascal Van Hentenryck

In this paper, we study the operational problem of connected hydro power reservoirs which involves sequential decision-making in an uncertain and dynamic environment. The problem is traditionally formulated as a stochastic dynamic program…

Optimization and Control · Mathematics 2022-05-17 Farzaneh Pourahmadi , Trine Krogh Boomsma

Resilient supply chains are critical, especially for Original Equipment Manufacturers (OEMs) that power today's digital economy. Safety Stock dimensioning-the computation of the appropriate safety stock quantity-is one of several mechanisms…

Applications · Statistics 2025-11-07 Elvis Agbenyega , Cody Quick

With growing intermittency and uncertainty in distribution networks around the world, ensuring operational integrity is becoming challenging. Recent use cases of dynamic operating envelopes (DOEs) indicate that they can be utilized for…

Systems and Control · Electrical Eng. & Systems 2023-07-07 Md Umar Hashmi , Dirk Van Hertem

The most common approaches for solving multistage stochastic programming problems in the research literature have been to either use value functions ("dynamic programming") or scenario trees ("stochastic programming") to approximate the…

Optimization and Control · Mathematics 2022-01-04 Warren B Powell , Saeed Ghadimi

Dynamic operating envelopes (DOEs) have been introduced in recent years as a means to manage the operation of distributed energy resources (DERs) within the network operational constraints. DOEs can be used by network operators to…

Optimization and Control · Mathematics 2023-08-29 Bin Liu , Julio H. Braslavsky

The penetration of renewable energies requires additional storages to deal with intermittency. Accordingly, there is growing interest in evaluating the opportunity cost (usage value) associated with stored energy in large storages, a cost…

Optimization and Control · Mathematics 2025-01-20 Camila Martinez Parra , Michel de Lara , Jean-Philippe Chancelier , Pierre Carpentier , Jean-Marc Janin , Manuel Ruiz

We propose a dynamical model for the estimation of Operational Risk in banking institutions. Operational Risk is the risk that a financial loss occurs as the result of failed processes. Examples of operational losses are the ones generated…

Risk Management · Quantitative Finance 2012-02-14 Marco Bardoscia , Roberto Bellotti

High penetration of renewable energy sources and the increasing share of stochastic loads require the explicit representation of uncertainty in tools such as the optimal power flow (OPF). Current approaches follow either a linearized…

Systems and Control · Computer Science 2020-07-24 Andreas Venzke , Lejla Halilbasic , Uros Markovic , Gabriela Hug , Spyros Chatzivasileiadis

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Virtual battery (VB)…

Systems and Control · Electrical Eng. & Systems 2020-03-20 Indrasis Chakraborty , Sai Pushpak Nandanoori , Soumya Kundu , Karanjit Kalsi

Distributionally robust stochastic optimization (DRSO) is an approach to optimization under uncertainty in which, instead of assuming that there is a known true underlying probability distribution, one hedges against a chosen set of…

Optimization and Control · Mathematics 2022-05-03 Rui Gao , Anton J. Kleywegt

In countries with an extended use of district heating (DH), the integrated operation of DH and power systems can increase the flexibility of the power system achieving a higher integration of renewable energy sources (RES). DH operators can…

Optimization and Control · Mathematics 2018-11-30 Ignacio Blanco , Daniela Guericke , Anders N. Andersen , Henrik Madsen

In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, numerous modern forecasting methods are still designed to create deterministic forecasts. Transforming…

Machine Learning · Computer Science 2023-02-06 Kaleb Phipps , Benedikt Heidrich , Marian Turowski , Moritz Wittig , Ralf Mikut , Veit Hagenmeyer

Tanker water systems play critical role in providing adequate service to meet potable water demands in the face of acute water crisis in many cities globally. Managing tanker movements among the supply and demand sides requires an efficient…

Optimization and Control · Mathematics 2024-08-02 Abhilasha Maheshwari , Shamik Misra , Ravindra Gudi , Senthilmurugan Subbiah , Chrysi Laspidou

We propose a framework employing stochastic differential equations to facilitate the long-term stability analysis of power grids with intermittent wind power generations. This framework takes into account the discrete dynamics which play a…

Systems and Control · Computer Science 2017-03-10 Xiaozhe Wang , Tao Wang , Hsiao-Dong Chiang , Jianhui Wang , Hui Liu
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