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We investigate the problem of allocating energy from renewable sources to flexible consumers in electricity markets. We assume there is a renewable energy supplier that provides energy according to a time-varying (and possibly…

Optimization and Control · Mathematics 2010-06-25 Michael J. Neely , Arash Saber Tehrani , Alexandros G. Dimakis

We study the problem of matching agents who arrive at a marketplace over time and leave after d time periods. Agents can only be matched while they are present in the marketplace. Each pair of agents can yield a different match value, and…

Data Structures and Algorithms · Computer Science 2018-08-13 Itai Ashlagi , Maximilien Burq , Chinmoy Dutta , Patrick Jaillet , Amin Saberi , Chris Sholley

We study the problem of improving the performance of online algorithms by incorporating machine-learned predictions. The goal is to design algorithms that are both consistent and robust, meaning that the algorithm performs well when…

Machine Learning · Computer Science 2020-10-23 Alexander Wei , Fred Zhang

In recent years, there have been several kinds of energy harvesting networks containing some tiny devices, such as ambient backscatter, ring and renewable sensor networks. During energy harvesting, such networks suffer from the energy…

Networking and Internet Architecture · Computer Science 2015-12-11 Jianhui Zhang , Mengmeng Wang , Zhi Li

Distribution networks are increasingly exposed to threats such as extreme weather, aging infrastructure, and cyber risks--resulting in more frequent contingencies and outages, a trend likely to persist. Microgrids, particularly dynamic…

Optimization and Control · Mathematics 2025-10-10 Hannah Moring , Bala Kameshwar Poolla , Harsha Nagarajan , Johanna L. Mathieu , Andrey Bernstein , David M. Fobes

Prediction intervals offer an effective tool for quantifying the uncertainty of loads in distribution systems. The traditional central PIs cannot adapt well to skewed distributions, and their offline training fashion is vulnerable to…

Applications · Statistics 2023-11-30 Yufan Zhang , Honglin Wen , Qiuwei Wu , Qian Ai

We study online boosting, the task of converting any weak online learner into a strong online learner. Based on a novel and natural definition of weak online learnability, we develop two online boosting algorithms. The first algorithm is an…

Machine Learning · Computer Science 2015-02-10 Alina Beygelzimer , Satyen Kale , Haipeng Luo

This paper proposes a two-step framework for techno-economic analysis of a demand-side flexibility service in distribution networks. Step one applies optimization-based modelling to propose a generic problem formulation which determines the…

Systems and Control · Electrical Eng. & Systems 2022-01-10 Timur Sayfutdinov , Charalampos Patsios , David Greenwood , Meltem Peker , Ilias Sarantakos

This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year randomized control trial in Switzerland, seeks…

Optimization and Control · Mathematics 2024-05-28 Kirk Bansak , Elisabeth Paulson

Energy consumption represents a significant cost in data center operation. A large fraction of the energy, however, is used to power idle servers when the workload is low. Dynamic provisioning techniques aim at saving this portion of the…

Performance · Computer Science 2012-02-28 Tan Lu , Minghua Chen

In this article, we introduce an adaptive online model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on…

Systems and Control · Electrical Eng. & Systems 2024-07-18 Vivek Khatana , Chin-Yao Chang , Wenbo Wang

The growing proliferation of microgrids and distributed energy resources in distribution networks has resulted in the development of Distribution Market Operator (DMO). This new entity will facilitate the management of the distributed…

Systems and Control · Computer Science 2017-11-13 Alireza Majzoobi , Mohsen Mahoor , Amin Khodaei

In this paper, we introduce a novel, non-recursive, maximal matching algorithm for double auctions, which aims to maximize the amount of commodities to be traded. It differs from the usual equilibrium matching, which clears a market at the…

Computer Science and Game Theory · Computer Science 2013-04-12 Jinzhong Niu , Simon Parsons

We consider an online version of the well-studied network utility maximization problem, where users arrive one by one and an operator makes irrevocable decisions for each user without knowing the details of future arrivals. We propose a…

Data Structures and Algorithms · Computer Science 2021-01-27 Ying Cao , Bo Sun , Danny H. K. Tsang

To accommodate the advent of microgrids (MG) managing distributed energy resources (DER) in distribution systems, an interactive two-stage joint retail electricity market mechanism is proposed to provide an effective platform for these…

Systems and Control · Electrical Eng. & Systems 2021-07-28 Chunyi Huang , Mingzhi Zhang , Chengmin Wang , Ning Xie , Jian Wang , Shi Peng

We propose a new approach to competitive analysis in online scheduling by introducing the novel concept of competitive-ratio approximation schemes. Such a scheme algorithmically constructs an online algorithm with a competitive ratio…

Data Structures and Algorithms · Computer Science 2012-11-01 Elisabeth Günther , Olaf Maurer , Nicole Megow , Andreas Wiese

We propose and develop a new algorithm for trading wind energy in electricity markets, within an online learning and optimization framework. In particular, we combine a component-wise adaptive variant of the gradient descent algorithm with…

Machine Learning · Computer Science 2023-05-22 Miguel Angel Muñoz , Pierre Pinson , Jalal Kazempour

Considering that the existing setup of the European electricity markets promotes the spatial coordination of neighbouring power systems only on the day-ahead market stage, regional system operators have to rely mainly on their internal…

Optimization and Control · Mathematics 2015-03-03 Stefanos Delikaraoglou , Pierre Pinson , Robert Eriksson , Tilman Weckesser

Emerging networked systems become increasingly flexible and reconfigurable. This introduces an opportunity to adjust networked systems in a demand-aware manner, leveraging spatial and temporal locality in the workload for online…

Data Structures and Algorithms · Computer Science 2019-05-08 Chen Avin , Ingo van Duijn , Stefan Schmid

We develop an online gradient algorithm for optimizing the performance of product-form networks through online adjustment of control parameters. The use of standard algorithms for finding optimal parameter settings is hampered by the…

Optimization and Control · Mathematics 2012-08-31 Jaron Sanders , Sem C. Borst , Johan S. H. van Leeuwaarden