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Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and…

Optimization and Control · Mathematics 2015-03-02 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

Due to limited metering infrastructure, distribution grids are currently challenged by observability issues. On the other hand, smart meter data, including local voltage magnitudes and power injections, are communicated to the utility…

Optimization and Control · Mathematics 2016-12-21 Siddharth Bhela , Vassilis Kekatos , Sriharsha Veeramachaneni

On-demand service platforms face a challenging problem of forecasting a large collection of high-frequency regional demand data streams that exhibit instabilities. This paper develops a novel forecast framework that is fast and scalable,…

Econometrics · Economics 2024-06-03 Yu Jeffrey Hu , Jeroen Rombouts , Ines Wilms

In case of high impact low probability events, in order to restore the critical loads of the distribution network as much as possible, it is necessary to employ all available resources such as microgrids and distributed generations. This…

Systems and Control · Electrical Eng. & Systems 2021-07-15 Ali Shakeri Kahnamouei , Saeed Lotfifard

A well-performing prediction model is vital for a recommendation system suggesting actions for energy-efficient consumer behavior. However, reliable and accurate predictions depend on informative features and a suitable model design to…

Machine Learning · Computer Science 2022-12-20 Alona Zharova , Antonia Scherz

Load data from power network clusters indicates economic development in each area, crucial for predicting regional trends and guiding power enterprise decisions. The Transformer model, a leading method for load prediction, faces challenges…

Machine Learning · Computer Science 2024-07-31 Cheng Jiang , Gang Lu , Xue Ma , Di Wu

Utilities face the challenge of responding to power outages due to storms and ice damage, but most power grids are not equipped with sensors to pinpoint the precise location of the faults causing the outage. Instead, utilities have to…

Optimization and Control · Mathematics 2016-05-20 Lina Al-Kanj , Warren B. Powell , Belgacem Bouzaiene-Ayari

As the cost of the residential solar system decreases, rooftop photovoltaic (PV) has been widely integrated into distribution systems. Most rooftop PV systems are installed behind-the-meter (BTM), i.e., only the net demand is metered, while…

Signal Processing · Electrical Eng. & Systems 2022-03-15 Fankun Bu , Rui Cheng , Zhaoyu Wang

In this chapter, we report on our experience with domestic flexible electric energy demand based on a regular commercial (HVAC)-based heating system in a house. Our focus is on investigating the predictability of the energy demand of the…

Systems and Control · Electrical Eng. & Systems 2024-07-24 Dirk Reinhardt , Wenqi Cai , Sebastien Gros

Proliferation of advanced metering devices with high sampling rates in distribution grids, e.g., micro-phasor measurement units ({\mu}PMU), provides unprecedented potentials for wide-area monitoring and diagnostic applications, e.g.,…

Machine Learning · Computer Science 2017-03-30 Iman Niazazari , Hanif Livani

Demand response services at the distribution level are emerging as enabling strategies for improving grid reliability in the presence of intermittent renewable generation and grid congestion. For residential loads, space heating and…

Optimization and Control · Mathematics 2025-05-22 Erhan Can Ozcan , Emiliano Dall'Anese , Ioannis Ch. Paschalidis

The rapid expansion of online shopping has increased the demand for timely parcel delivery, compelling logistics service providers to enhance the efficiency, agility, and predictability of their hub networks. In order to solve the problem,…

Machine Learning · Computer Science 2026-02-04 Xinyue Pan , Yujia Xu , Benoit Montreuil

Residential Load Profile (RLP) generation and prediction are critical for the operation and planning of distribution networks, especially as diverse low-carbon technologies (e.g., photovoltaic and electric vehicles) are increasingly…

Machine Learning · Computer Science 2025-10-28 Weijie Xia , Chenguang Wang , Peter Palensky , Pedro P. Vergara

This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed,…

Systems and Control · Computer Science 2018-06-25 Sarmad Hanif , D. F. R. Melo , Mehdi Maasoumy , Tobias Massier , Thomas Hamacher , Thomas Reindl

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid strategies like demand response and peak shaving. In…

Machine Learning · Computer Science 2024-11-26 Dafang Zhao , Xihao Piao , Zheng Chen , Zhengmao Li , Ittetsu Taniguchi

Managing supply and demand in the electricity grid is becoming more challenging due to the increasing penetration of variable renewable energy sources. As significant end-use consumers, and through better grid integration, buildings are…

Systems and Control · Electrical Eng. & Systems 2020-08-14 Anjukan Kathirgamanathan , Mattia De Rosa , Eleni Mangina , Donal P. Finn

Participation in residential energy demand response programs requires an active role by the consumers. They contribute flexibility in how they use their appliances as the means to adjust energy consumption, and reduce demand peaks, possibly…

Systems and Control · Electrical Eng. & Systems 2020-04-29 Farzam Fanitabasi , Evangelos Pournaras

Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In…

Heat, Ventilation and Air Conditioning (HVAC) systems play a critical role in maintaining a comfortable thermal environment and cost approximately 40% of primary energy usage in the building sector. For smart energy management in buildings,…

Machine Learning · Computer Science 2024-02-22 Dafang Zhao , Zheng Chen , Zhengmao Li , Xiaolei Yuan , Ittetsu Taniguchi

Long-term planning of a robust power system requires the understanding of changing demand patterns. Electricity demand is highly weather sensitive. Thus, the supply side variation from introducing intermittent renewable sources, juxtaposed…

Machine Learning · Computer Science 2022-09-13 Reshmi Ghosh , Michael Craig , H. Scott Matthews , Constantine Samaras , Laure Berti-Equille