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Chance-constrained optimization has emerged as a promising framework for managing uncertainties in power systems. This work advances its application to the DC Optimal Power Flow (DC-OPF) model, developing a novel approach to uncertainty…

Systems and Control · Electrical Eng. & Systems 2026-03-18 Tianyang Yi , D. Adrian Maldonado , Anirudh Subramanyam

This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small…

Monitoring data transfer performance is a crucial task in scientific computing networks. By predicting performance early in the communication phase, potentially sluggish transfers can be identified and selectively monitored, optimizing…

Machine Learning · Computer Science 2025-12-17 Jacob Taegon Kim , Alex Sim , Kesheng Wu , Jinoh Kim

Electricity load forecasting plays an important role in the energy planning such as generation and distribution. However, the nonlinearity and dynamic uncertainties in the smart grid environment are the main obstacles in forecasting…

Neural and Evolutionary Computing · Computer Science 2018-11-09 Faisal Mohammad , Ki Boem Lee , Young-Chon Kim

The increasing use of renewable energy sources with variable output, such as solar photovoltaic and wind power generation, calls for Smart Grids that effectively manage flexible loads and energy storage. The ability to forecast consumption…

Machine Learning · Computer Science 2014-04-02 Andreas Veit , Christoph Goebel , Rohit Tidke , Christoph Doblander , Hans-Arno Jacobsen

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

The rapid growth of inverter-based resources (IBRs) and distributed energy resources (DERs) has fundamentally altered the long-term voltage stability characteristics of modern power systems. This article leverages the advantages of machine…

Systems and Control · Electrical Eng. & Systems 2026-04-24 Ahmed Alkhonain , Kiran Kumar Challa , Amarsagar Reddy Ramapuram Matavalam , Alok Kumar Bharati , Venkataramana Ajjarapu

The uncertainty associated with solar photo-voltaic (PV) power output is a big challenge to design, manage and implement effective demand response and management strategies. Therefore, an accurate PV power output forecast is an utmost…

Signal Processing · Electrical Eng. & Systems 2018-11-26 Muhammad Qamar Raza , N. Mithulananthan , Jiaming Li , Kwang Y. Lee , Hoay Beng Gooi

Precise probabilistic forecasts are fundamental for energy risk management, and there is a wide range of both statistical and machine learning models for this purpose. Inherent to these probabilistic models is some form of uncertainty…

Machine Learning · Computer Science 2025-10-10 Andreas Lebedev , Abhinav Das , Sven Pappert , Stephan Schlüter

Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the…

The energy market relies on forecasting capabilities of both demand and power generation that need to be kept in dynamic balance. Today, when it comes to renewable energy generation, such decisions are increasingly made in a liberalized…

Machine Learning · Computer Science 2022-03-15 Odin Foldvik Eikeland , Finn Dag Hovem , Tom Eirik Olsen , Matteo Chiesa , Filippo Maria Bianchi

Energy forecasting has a vital role to play in smart grid (SG) systems involving various applications such as demand-side management, load shedding, and optimum dispatch. Managing efficient forecasting while ensuring the least possible…

Machine Learning · Computer Science 2022-05-25 Devinder Kaur , Shama Naz Islam , Md. Apel Mahmud , Md. Enamul Haque , ZhaoYang Dong

Accurate electrical consumption forecasting is crucial for efficient energy management and resource allocation. While traditional time series forecasting relies on historical patterns and temporal dependencies, incorporating external…

Machine Learning · Computer Science 2025-06-18 Fabien Bernier , Maxime Cordy , Yves Le Traon

Forecasting power consumptions of integrated electrical, heat or gas network systems is essential in order to operate more efficiently the whole energy network. Multi-energy systems are increasingly seen as a key component of future energy…

Machine Learning · Computer Science 2025-03-11 Corneliu Arsene , Alessandra Parisio

With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cause random voltage fluctuations as their output power depends…

Systems and Control · Electrical Eng. & Systems 2020-08-26 Mohammad Abujubbeh , Sai Munikoti , Balasubramaniam Natarajan

This paper deals with the problem of the electricity consumption forecasting method. An MPSO-BP (modified particle swarm optimization-back propagation) neural network model is constructed based on the history data of a mineral company of…

Neural and Evolutionary Computing · Computer Science 2018-10-23 Youshan Zhang , Liangdong Guo , Qi Li , Junhui Li

Uncertainty analysis in the form of probabilistic forecasting can provide significant improvements in decision-making processes in the smart power grid for better integrating renewable energies such as wind. Whereas point forecasting…

Machine Learning · Statistics 2018-03-30 Kostas Hatalis , Shalinee Kishore , Katya Scheinberg , Alberto Lamadrid

China has made great achievements in electric power industry during the long-term deepening of reform and opening up. However, the complex regional economic, social and natural conditions, electricity resources are not evenly distributed,…

Machine Learning · Statistics 2021-03-02 Xingcai Zhou , Jiangyan Wang

Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and…

Optimization and Control · Mathematics 2016-09-09 Line Roald , Sidhant Misra , Thilo Krause , Goran Andersson

Imbalance (on-line energy gap between contracted supply and actual demand, and associated cost) reduction is going to be a crucial service for a Power Producer and Supplier (PPS) in the deregulated energy market. PPS requires forward market…

Systems and Control · Computer Science 2016-09-09 Shantanu Chakraborty , Toshiya Okabe