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The dispatchable region of volatile renewable power generation (RPG) quantifies how much uncertainty the power system can handle at a given operating point. State-of-the-art dispatchable region (DR) research has studied how system…

Systems and Control · Electrical Eng. & Systems 2022-04-26 Yanqi Liu , Zhigang Li , Wei Wei , Jiehui Zheng , Hongcai Zhang

Uncertainty in distributed renewable generation threatens the security of power distribution systems. The concept of the dispatchable region was developed to assess the ability of power systems to accommodate renewable generation at a given…

Systems and Control · Electrical Eng. & Systems 2023-02-28 Zhigang Li , Wenjing Huang , J. H. Zheng , Q. H. Wu

The increasing penetration of Renewable Energy Sources (RES) requires more Flexibility Resources (FR), generally thermal units and storages, must be kept in the system to accommodate the uncertainties from RES. The challenge is how the…

Optimization and Control · Mathematics 2015-12-31 Hongxing Ye , Jianhui Wang , Zuyi Li

The concept of dispatchable region is useful in quantifying how much renewable generation power the system can handle. In this paper, we aim to provide an improved dispatchable region approximation method in distribution networks. First,…

Optimization and Control · Mathematics 2022-05-03 Yue Chen , Changhong Zhao

This paper proposes a reliable energy scheduling framework for distributed energy resources (DER) of a residential area to achieve an appropriate daily electricity consumption with the maximum affordable demand response. Renewable and…

Systems and Control · Electrical Eng. & Systems 2020-07-23 Anahita Moradmand , Mehrdad Dorostian , Bahram Shafai

The concept of dispatchable region plays a pivotal role in quantifying the capacity of power systems to accommodate renewable generation. In this paper, we extend the previous approximations of the dispatchable regions on direct current…

Optimization and Control · Mathematics 2025-03-31 Bohang Fang , Yue Chen , Changhong Zhao

AI heralds a step-change in the performance and capability of wireless networks and other critical infrastructures. However, it may also cause irreversible environmental damage due to their high energy consumption. Here, we address this…

Machine Learning · Computer Science 2019-10-14 Zhiyong Du , Yansha Deng , Weisi Guo , Arumugam Nallanathan , Qihui Wu

Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due to the introduction of renewable-based generation. To deal…

Systems and Control · Electrical Eng. & Systems 2022-08-02 Hou Shengren , Edgar Mauricio Salazar , Pedro P. Vergara , Peter Palensky

This study presents a real-time energy management framework for hybrid community microgrids integrating photovoltaic, wind, battery energy storage systems, diesel generators, and grid interconnection. The proposed approach formulates the…

Systems and Control · Electrical Eng. & Systems 2025-07-01 Moslem Uddin , Huadong Mo , Daoyi Dong

Traditional power dispatch methods have difficulties in accommodating large-scale variable renewable generation (VRG) and have resulted in unnecessary VRG spillage in the practical industry. The recent dispatchable-interval-based methods…

Systems and Control · Computer Science 2016-02-25 Zhigang Li , Feng Qiu , Jianhui Wang

The increasing use of renewable energy sources (RESs) and responsive loads has made power systems more uncertain. Meanwhile, thanks to the development of advanced metering and forecasting technologies, predictions by RESs and load owners…

Optimization and Control · Mathematics 2023-08-01 Rui Xie , Pierre Pinson , Yin Xu , Yue Chen

The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms…

Systems and Control · Electrical Eng. & Systems 2023-05-10 Hou Shengren , Pedro P. Vergara , Edgar Mauricio Salazar Duque , Peter Palensky

The exponential growth in demand for digital services drives massive datacenter energy consumption and negative environmental impacts. Promoting sustainable solutions to pressing energy and digital infrastructure challenges is crucial.…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-11 Vanamala Venkataswamy , Jake Grigsby , Andrew Grimshaw , Yanjun Qi

In dynamic programming (DP) and reinforcement learning (RL), an agent learns to act optimally in terms of expected long-term return by sequentially interacting with its environment modeled by a Markov decision process (MDP). More generally…

Machine Learning · Computer Science 2022-01-03 Mastane Achab , Gergely Neu

Dynamic line rating (DLR) models the transmission capacity of overhead lines as a function of ambient conditions. It takes advantage of the physical thermal property of overhead line conductors, thus making DLR less conservative compared to…

Optimization and Control · Mathematics 2016-12-06 Bolun Xu , Andreas Ulbig , Goran Andersson

The expansion of renewable energy could help realizing the goals of peaking carbon dioxide emissions and carbon neutralization. Some existing grid dispatching methods integrating short-term renewable energy prediction and reinforcement…

Machine Learning · Computer Science 2022-04-12 Xinhang Li , Zihao Li , Nan Yang , Zheng Yuan , Qinwen Wang , Yiying Yang , Yupeng Huang , Xuri Song , Lei Li , Lin Zhang

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

Reliable operation in power systems is becoming more difficult as the penetration of random renewable resources increases. In particular, operators face the risk of not scheduling enough traditional generators in the times when renewable…

Optimization and Control · Mathematics 2013-05-28 Junjie Qin , Baosen Zhang , Ram Rajagopal

Risk Limiting Dispatch (RLD) was proposed recently as a mechanism that utilizes information and market recourse to reduce reserve capacity requirements, emissions and achieve other system operator objectives. It induces a set of simple…

Optimization and Control · Mathematics 2012-12-04 Junjie Qin , Han-I Su , Ram Rajagopal

In the event of a total loss of thrust, a pilot must identify a reachable landing site and subsequently execute a forced landing. To do so, they must estimate which region on the ground can be reached safely in gliding flight. We call this…

Optimization and Control · Mathematics 2024-07-30 Giovanni Piccioli
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