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Surrogate‐assisted optimal re‐dispatch control for risk‐aware regulation of dynamic total transfer capability

Gao Qiu, Youbo Liu, Junyong Liu, Lingfeng Wang, Tingjian Liu, Hongjun Gao, Shafqat Jawad
2021 IET Generation, Transmission & Distribution  
Particularly, in order to be aware of control risk from the predictive error of the deep belief networks, prediction intervals (PIs) are produced improved by using ensemble learning and used to disclose  ...  However, the traditional optimal power flow (OPF)-based total transfer capability calculation is computationally expensive for efficient total transfer capability control due to the inclusion of a large  ...  increase generation in power sending area or load in the power receiving area, and the increase direction is specified by a user or calculated to deteriorate security [10] ;  ( ) and  ( ) are algebraic  ... 
doi:10.1049/gtd2.12147 fatcat:fkciixhxafb43djjoqhxutvaum

A Survey of Real-Time Optimal Power Flow

Erfan Mohagheghi, Mansour Alramlawi, Aouss Gabash, Pu Li
2018 Energies  
The particular challenges associated with the incorporation of battery storage systems in the networks are explored, and it is concluded that the current research on RT-OPF is not sufficient, and new solution  ...  There has been a strong increase of penetration of renewable energies into power systems. However, the renewables pose new challenges for the operation of the networks.  ...  [101] developed a framework for multi-area OPF problem aiming at the independent dispatch of each individual area, while achieving the economic optimum of the whole system.  ... 
doi:10.3390/en11113142 fatcat:thhtrjenwvdmbkf7ktze3inywi

2021 Index IEEE Transactions on Power Systems Vol. 36

2021 IEEE Transactions on Power Systems  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  ., +, TPWRS Jan. 2021 4-16 Feature extraction An Integrated Transfer Learning Method for Power System Dynamic Security Assessment of Unlearned Faults With Missing Data.  ... 
doi:10.1109/tpwrs.2021.3125235 fatcat:n3ecyy2flnapzjz7clyrp7sx4a

Preface: Swarm Intelligence, Focus on Ant and Particle Swarm Optimization [chapter]

Felix T.S., Manoj Kumar
2007 Swarm Intelligence, Focus on Ant and Particle Swarm Optimization  
The local search procedure intends to explore the less-crowded area in the current archive to possibly obtain better non-dominated solutions nearby.  ...  The objective of MAEED is to dispatch the power among different areas by simultaneously minimizing the operational costs and pollutant emissions.  ... 
doi:10.5772/5121 fatcat:s5xxnkpyejbmtff2d6m3owlpma

Multi-microgrid Energy Management Systems: Architecture, Communication, and Scheduling Strategies

Bin Zhou, Jianting Zou, Chi Yung Chung, Huaizhi Wang, Nian Liu, Nikolai Voropai, Daosen Xu
2021 Journal of Modern Power Systems and Clean Energy  
His research interests include modeling of power systems, operation and dynamics performance of large power grids, emergency protection and control of power grids, reliability and security of energy systems  ...  Consequently, the multi-microgrid energy management system (MMGEMS) plays a significant role in improving energy efficiency, power quality and reliability of distribution systems, especially in enhancing  ...  An auction mechanism to enable the competition among microgrid agents for the provision of the local area frequency support is also proposed in [154] .  ... 
doi:10.35833/mpce.2019.000237 fatcat:wmuxy6fpnrbbzmnwn6rjc7vbiq

Reinforcement Learning for Decision-Making and Control in Power Systems: Tutorial, Review, and Vision [article]

Xin Chen, Guannan Qu, Yujie Tang, Steven Low, Na Li
2021 arXiv   pre-print
In this paper, we provide a tutorial on various RL techniques and how they can be applied to decision-making in power systems.  ...  With large-scale integration of renewable generation and distributed energy resources (DERs), modern power systems are confronted with new operational challenges, such as growing complexity, increasing  ...  Multi-area AGC conventionally operates based on the area control error (ACE) signal, which is defined as ACE i = β i ∆ω i + j:ij∈E ∆P ij with 8 For multi-area AGC problem, each control area is generally  ... 
arXiv:2102.01168v4 fatcat:ibjelwrjffg5bm7eg3dlw6u3ne

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids [article]

Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie
2021 arXiv   pre-print
We envision that this dataset will enable advances for ML in dynamic systems, while simultaneously allowing ML researchers to contribute towards carbon-neutral electricity and mobility.  ...  In this paper, we present PSML, a first-of-its-kind open-access multi-scale time-series dataset, to aid in the development of data-driven machine learning (ML) based approaches towards reliable operation  ...  Related work: L2RPN [49] provides an online interactive power grid simulation platform for reinforcement learning model training, which aims to aid in power system operations such as generation dispatch  ... 
arXiv:2110.06324v1 fatcat:quumrkzw6fhmhgdpcwwjrber5q

A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications [article]

Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
2020 arXiv   pre-print
To allow for a less centralized operating paradigm, consumer-end perspective and abilities should be integrated in current dispatch practices and accounted for in switching between different energy sources  ...  This ensemble control becomes a modern demand response contributor to the set of modeling tools for multi-energy infrastructure systems.  ...  Although these models have been effective in providing the required data in these application areas, their potential has not been fully explored for multienergy dispatch.  ... 
arXiv:2005.02339v1 fatcat:tkksszckjvcb7ltrg5ux6yydtu

Volt/VAR Optimization: A Survey of Classical and Heuristic Optimization Methods

H. Mataifa, S. Krishnamurthy, C. Kriger
2022 IEEE Access  
Reactive power optimization and voltage control is one of the most critical components of power system operation, impacting both the economy and security of system operation.  ...  Each optimization method is described in detail, and its strengths and shortcomings are outlined.  ...  A multi-period, multi-scenario corrective security-constrained OPF has been explored in [32] as a way of dealing with increasing penetration of variable renewable generation.  ... 
doi:10.1109/access.2022.3146366 fatcat:y5pt7ud5czgvhaw6ev24gsi3sy

Optimal dynamic economic dispatch of generation: A review

X. Xia, A.M. Elaiw
2010 Electric power systems research  
The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with  ...  The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units.  ...  In DED demand forecast advises the power system operator of the amount of power to be generated.  ... 
doi:10.1016/j.epsr.2009.12.012 fatcat:du5d6swmbfcfjl4wsontvhn65y

Smart Grid: Overview, Issues and Opportunities. Advances and Challenges in Sensing, Modeling, Simulation, Optimization and Control

S. Massoud Amin
2011 European Journal of Control  
There are even more opportunities and challenges in today's devices and systems, as well as in the emerging modern power systems -ranging from dollars, watts, emissions, standards, and more -at nearly  ...  The potential for a highly distributed system with a high penetration of intermittent sources poses opportunities and challenges.  ...  Multi-resolutional techniques where various levels of aggregation can co-exist. • Disturbance Propagation in Networks: Prediction and detection of the onset of failures both in local and global network  ... 
doi:10.3166/ejc.17.547-567 fatcat:hxmiwk4txbhllgrmzg2yihoyuq

The Quest for Energy-Efficient I$ Design in Ultra-Low-Power Clustered Many-Cores

Igor Loi, Alessandro Capotondi, Davide Rossi, Andrea Marongiu, Luca Benini
2018 IEEE Transactions on Multi-Scale Computing Systems  
The multi-port cache is suitable for sizes up to a few kB, improving performance by up to 40%, energy efficiency by up to 20%, and energy × area efficiency by up to 30% with respect to the private cache  ...  The single-port solution is more suitable for larger cache sizes (up to 16 kB), providing up to 20% better energy × area efficiency than the multi-port, and up to 30% better energy efficiency than private  ...  Data replication is the major drawback for private instruction cache multi-core systems, which leads to a degraded energy and area efficiency.  ... 
doi:10.1109/tmscs.2017.2769046 fatcat:ta644xddx5b7hjmoqsipow2aiy

A Taxonomy of Data Attacks in Power Systems [article]

Sagnik Basumallik
2020 arXiv   pre-print
This paper tracks the progress of research in power system cyber security over the last decade and presents a taxonomy of data attacks.  ...  When cyber networks in power system are compromised, time-critical data can be dropped and modified, which can impede real time operations and decision making.  ...  Switching Attacks In [78] , authors have explored coordinated multi-switch attacks.  ... 
arXiv:2002.11011v1 fatcat:qnh3li5os5b4tn2iadhy7f24ze

Lagrangian Duality for Constrained Deep Learning [article]

Ferdinando Fioretto, Pascal Van Hentenryck, Terrence WK Mak, Cuong Tran, Federico Baldo, Michele Lombardi
2020 arXiv   pre-print
This paper explores the potential of Lagrangian duality for learning applications that feature complex constraints.  ...  In energy domains, the combination of Lagrangian duality and deep learning can be used to obtain state-of-the-art results to predict optimal power flows, in energy systems, and optimal compressor settings  ...  This step is executed on all the predicted control variables: generator dispatch and voltage set points, for power systems, and compression ratios, for gas systems.  ... 
arXiv:2001.09394v2 fatcat:fecpehj2ondtrplaexwpk4pzdu

Anomaly Detection and Mitigation for Wide-Area Damping Control using Machine Learning

Gelli Ravikumar, Manimaran Govindarasu
2020 IEEE Transactions on Smart Grid  
In an interconnected multi-area power system, wide-area measurement based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power flows  ...  The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for 2-area 4-machine power system.  ...  This research is funded in part by US NSF Grant # CNS 1446831, and US DOE Grant # DE-OE0000830.  ... 
doi:10.1109/tsg.2020.2995313 fatcat:tf4umhogb5hqhhz54mwdu5uofe
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