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The exponential growth of digital services has positioned data centers among the most energy-intensive infrastructures in the modern economy, raising critical concerns regarding operational costs, carbon emissions, and the sustainable…

Machine Learning · Computer Science 2026-05-05 Abderaouf Bahi , Amel Ourici , Hasan Dincer , Serhat Yuksel , Akila Djebbar

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency…

Machine Learning · Computer Science 2022-02-08 Renke Huang , Yujiao Chen , Tianzhixi Yin , Qiuhua Huang , Jie Tan , Wenhao Yu , Xinya Li , Ang Li , Yan Du

In this paper, a novel Multi-agent Reinforcement Learning (MARL) approach, Multi-Agent Continuous Dynamic Policy Gradient (MACDPP) was proposed to tackle the issues of limited capability and sample efficiency in various scenarios controlled…

Systems and Control · Electrical Eng. & Systems 2023-09-27 Chenyang Miao , Yunduan Cui , Huiyun Li , Xinyu Wu

The optimal dispatch of energy storage systems (ESSs) presents formidable challenges due to the uncertainty introduced by fluctuations in dynamic prices, demand consumption, and renewable-based energy generation. By exploiting the…

Systems and Control · Electrical Eng. & Systems 2023-07-27 Shengren Hou , Edgar Mauricio Salazar Duque , Peter Palensky , Pedro P. Vergara

Microgrids (MGs) are important players for the future transactive energy systems where a number of intelligent Internet of Things (IoT) devices interact for energy management in the smart grid. Although there have been many works on MG…

Systems and Control · Electrical Eng. & Systems 2021-11-24 Hao Zhou , Atakan Aral , Ivona Brandic , Melike Erol-Kantarci

The utilization of large-scale distributed renewable energy promotes the development of the multi-microgrid (MMG), which raises the need of developing an effective energy management method to minimize economic costs and keep self…

Systems and Control · Electrical Eng. & Systems 2024-05-07 Yuanzheng Li , Shangyang He , Yang Li , Yang Shi , Zhigang Zeng

Home Energy Management Systems (HEMS) have emerged as a pivotal tool in the smart home ecosystem, aiming to enhance energy efficiency, reduce costs, and improve user comfort. By enabling intelligent control and optimization of household…

Machine Learning · Computer Science 2025-05-05 Mohammed Sumayli , Olugbenga Moses Anubi

Ongoing risks from climate change have impacted the livelihood of global nomadic communities, and are likely to lead to increased migratory movements in coming years. As a result, mobility considerations are becoming increasingly important…

Systems and Control · Electrical Eng. & Systems 2022-12-09 Cesare Caputo , Michel-Alexandre Cardin , Pudong Ge , Fei Teng , Anna Korre , Ehecatl Antonio del Rio Chanona

This paper presents a novel and effective deep reinforcement learning (DRL)-based approach to addressing joint resource management (JRM) in a practical multi-carrier non-orthogonal multiple access (MC-NOMA) system, where hardware…

Artificial Intelligence · Computer Science 2021-03-30 Shaoyang Wang , Tiejun Lv , Wei Ni , Norman C. Beaulieu , Y. Jay Guo

Energy management systems (EMS) are becoming increasingly important in order to utilize the continuously growing curtailed renewable energy. Promising energy storage systems (ESS), such as batteries and green hydrogen should be employed to…

Machine Learning · Computer Science 2022-12-13 Dongju Kang , Doeun Kang , Sumin Hwangbo , Haider Niaz , Won Bo Lee , J. Jay Liu , Jonggeol Na

The cost of the power distribution infrastructures is driven by the peak power encountered in the system. Therefore, the distribution network operators consider billing consumers behind a common transformer in the function of their peak…

Systems and Control · Electrical Eng. & Systems 2022-04-01 Wenqi Cai , Hossein N. Esfahani , Arash B. Kordabad , Sébastien Gros

Multi-Agent Reinforcement Learning (MARL) is a widely used technique for optimization in decentralised control problems. However, most applications of MARL are in static environments, and are not suitable when agent behaviour and…

Multiagent Systems · Computer Science 2014-09-17 Andrei Marinescu , Ivana Dusparic , Adam Taylor , Vinny Cahill , Siobhán Clarke

The recently emerging multi-mode plug-in hybrid electric vehicle (PHEV) technology is one of the pathways making contributions to decarbonization, and its energy management requires multiple-input and multipleoutput (MIMO) control. At the…

Robotics · Computer Science 2023-08-29 Min Hua , Cetengfei Zhang , Fanggang Zhang , Zhi Li , Xiaoli Yu , Hongming Xu , Quan Zhou

The rapid growth of data across fields of science and industry has increased the need to improve the performance of end-to-end data transfers while using the resources more efficiently. In this paper, we present a dynamic, multiparameter…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-27 Hasibul Jamil , Jacob Goldverg , Elvis Rodrigues , MD S Q Zulkar Nine , Tevfik Kosar

Efficient task scheduling in large-scale distributed systems presents significant challenges due to dynamic workloads, heterogeneous resources, and competing quality-of-service requirements. Traditional centralized approaches face…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-27 Daniel Benniah John

The control and managing of power demand and supply become very crucial because of penetration of renewables in the electricity networks and energy demand increase in residential and commercial sectors. In this paper, a new approach is…

Systems and Control · Electrical Eng. & Systems 2020-01-28 Seyyed Danial Nazemi , Khashayar Mahani , Ali Ghofrani , Burcu Ece Kose , Mahraz Amini , Mohsen A. Jafari

This paper presents a capacity-constrained incentive-based demand response approach for residential smart grids. It aims to maintain electricity grid capacity limits and prevent congestion by financially incentivising end users to reduce or…

Machine Learning · Computer Science 2026-02-19 Shafagh Abband Pashaki , Sepehr Maleki , Amir Badiee

We consider a typical heterogeneous network (HetNet), in which multiple access points (APs) are deployed to serve users by reusing the same spectrum band. Since different APs and users may cause severe interference to each other, advanced…

Information Theory · Computer Science 2020-08-11 Lin Zhang , Ying-Chang Liang

The increasing electricity use and reliance on intermittent renewable energy sources challenge power grid management during peak demand, making Demand Response programs and energy conservation measures essential. This research combines…

Optimization and Control · Mathematics 2024-07-12 Vincent Taboga , Hanane Dagdougui

This paper presents a multi-agent control architecture and an online optimization method based on dynamic average consensus to coordinate the power consumption of a large population of Thermostatically Controlled Loads (TCLs). Our objective…

Systems and Control · Electrical Eng. & Systems 2019-08-30 Mauro Franceschelli , Alessandro Pilloni , Andrea Gasparri