Article
Engineering, Multidisciplinary
Michael Abdelmalak, Mohammed Benidris
Summary: This article proposes a proactive generation redispatch strategy to enhance the operational resilience of power grids during hurricanes by minimizing load curtailments and operational costs. The strategy considers the unavailability and forced outages of renewable energy sources, as well as various constraints such as generation, transmission, and system limitations. The results show that the proactive and dynamic generation redispatch can significantly reduce load curtailments and improve power system resilience during hurricanes.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Hanchen Liu, Chong Wang, Ping Ju, Hongyu Li
Summary: This paper proposes a sequentially proactive operational strategy to enhance resilience against extreme-weather-triggered cascading failures. The use of random scenario sampling method and mixed-integer linear programming can effectively simulate and solve this problem.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Public, Environmental & Occupational Health
John George Richmond, Rowena Hill
Summary: This study explores how local resilience structures in England can be utilized to achieve a comprehensive response to extreme heat events with the participation of the whole society. Based on a literature review, the study draws insights from research on health emergency response and extreme heat events in England. The findings suggest that local resilience forums play a critical role in addressing extreme heat events by tailoring information and resources to specific target groups within communities.
Article
Engineering, Electrical & Electronic
Zhen-chen Zhou, Zhou Wu, Tao Jin
Summary: This paper proposes a model-free optimization framework based on deep reinforcement learning to improve the resilience of a distribution system by formulating the distributed generator (DG) rescheduling problem as a discrete Markov decision process. Experimental results demonstrate the effectiveness of the proposed framework in various power systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Weilong Ni, Yongtu Liang, Zhengbing Li, Qi Liao, Siya Cai, Bohong Wang, Haoran Zhang, Yi Wang
Summary: This paper proposes a method for evaluating the resilience of supply chains and applies it to demand management in the downstream oil supply chain. Through quantitative analysis and Monte Carlo simulation of multiple scenarios, it is concluded that increasing inventory and improving repair rates can enhance the resilience of the supply chain.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Review
Energy & Fuels
Ahmed Daeli, Salman Mohagheghi
Summary: Extreme weather events are a major cause of widespread power outages in distribution systems. The changing climate has increased the frequency and severity of these events, requiring a paradigm shift in grid design practices. Researchers have proposed various solutions to improve the resilience of the power grid against extreme events, but there is a lack of standard definitions and metrics for assessing resilience. This paper provides a literature review on the resilience of power grid infrastructure and identifies gaps in research and future directions.
Article
Geosciences, Multidisciplinary
Adam Chorynski, Piotr Matczak, Agnieszka Jeran, Marcin Witkowski
Summary: This study examines how small Polish municipalities endangered by extreme weather events build resilience, and finds that lack of administrative centrality in the municipality appears to be a significant factor for high local resilience, along with a combination of other factors.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Review
Computer Science, Information Systems
Francis Mujjuni, Thomas R. Betts, Richard E. Blanchard
Summary: This study reviews the assumptions and models employed in evaluating and improving the resilience of power systems, and assesses the resilience of Great Britain's transmission network against a lightning strike as a use case. The findings show that network outturn during a threat is influenced more by internal systemic maloperations than the intensity of the event. The study also highlights the threat characterization and vulnerability assessment phases as the main sources of uncertainties, which can be moderated through the development of holistic empirical fragility functions.
Article
Environmental Sciences
William J. Thompson, Varun Varma, Jonas Joerin, Solhanlle Bonilla-Duarte, Daniel P. Bebber, Wilma Blaser-Hart, Birgit Kopainsky, Leonhard Spath, Bianca Curcio, Johan Six, Pius Krutli
Summary: Extreme weather events have severe impacts on smallholders in global food value chains. Understanding the manifestations of climate shocks in food systems and developing strategies to enhance resilience are urgently needed. This study investigates the cascading impacts of consecutive hurricanes on smallholder banana farmers in the Dominican Republic and identifies factors affecting their recovery. The results highlight the importance of loyalty, collaboration, and risk-targeted training in promoting resilience in global food value chains.
Article
Energy & Fuels
Yixin Ding, Tianfeng Lu, Zhiyu Wang, Houyi Wu, Xuewen Lu
Summary: A framework for enhancing the resilience of power distribution systems to natural disasters caused by extreme weather is proposed. The framework analyzes the impact of extreme weather events on power system components and evaluates the failure probability of the components. The vulnerability model of the components is established and a multi-stage performance response curve is used to quantify the resilience level of the network. Based on this, a framework for disaster resilience enhancement before, during, and after disasters is proposed.
Article
Engineering, Multidisciplinary
Michael Abdelmalak, Mohammed Benidris
Summary: This article proposes a probabilistic proactive generation redispatch strategy to enhance the operational resilience of power grids during wildfires. The strategy uses a Markov decision process to provide generation redispatch strategies for different system states, considering component failure probabilities, wildfire spatiotemporal properties, and load variation. The results demonstrate the effectiveness of the proposed method in enhancing the resilience level of power grids during wildfires.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Proceedings Paper
Energy & Fuels
Michael Abdelmalak, Mohammed Benidris
Summary: The paper proposes a proactive generation redispatch strategy using multiobjective mixed integer linear programming to minimize load curtailments and operational costs during hurricanes. The effectiveness of the method in enhancing power grid operational resilience during hurricanes is demonstrated through validation on the IEEE 30-bus system under different impact levels.
2020 52ND NORTH AMERICAN POWER SYMPOSIUM (NAPS)
(2021)
Article
Environmental Sciences
Wenli Zhao, Biqing Zhu, Steven J. Davis, Philippe Ciais, Chaopeng Hong, Zhu Liu, Pierre Gentine
Summary: Extreme climate events caused by climate change have impacts on the power production system and renewable energy supply. During these events, carbon emissions and reliance on fossil fuels increase, while renewable energy capacity decreases. States with more renewable electricity generation are also more affected by extreme temperatures, suggesting the need for adaptation measures.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Article
Engineering, Electrical & Electronic
Dimitris N. Trakas, Nikos D. Hatziargyriou
Summary: This paper proposes a transmission resilience planning solution based on historical extreme weather events, aiming to enhance power system resilience by determining the underground placement of transmission lines to minimize load shedding.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Review
Environmental Sciences
Martin J. Siegert, Mike J. Bentley, Angus Atkinson, Thomas J. Bracegirdle, Peter Convey, Bethan Davies, Rod Downie, Anna E. Hogg, Caroline Holmes, Kevin A. Hughes, Michael P. Meredith, Neil Ross, Jane Rumble, Jeremy Wilkinson
Summary: There is increasing evidence that fossil fuel burning has led to the increased occurrence and severity of extreme environmental events. This study examines evidence for extreme events in Antarctica and the Southern Ocean and highlights the vulnerability of natural Antarctic systems. It predicts that future Antarctic extreme events will be more severe due to further heating and the need for drastic action to reduce greenhouse gas emissions.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2023)
Article
Physics, Applied
J. H. Guo, Y. Hou, J. Xia, X. Zhang, Philip W. T. Pong, Y. Zhou
Summary: The study investigates the manipulation of magnetic skyrmions using a magnetic field and spin-transfer or spin-orbit torque in a nanotrack. The effects of various parameters on skyrmion motion are explored through micromagnetic simulations, demonstrating both static and dynamic properties of the skyrmion. This research may contribute to the development of topological transport channels for spintronic devices.
JOURNAL OF APPLIED PHYSICS
(2022)
Article
Engineering, Electrical & Electronic
Wenjie Liu, Shibo Chen, Yunhe Hou, Zaiyue Yang
Summary: This paper studies a trilevel profit maximization problem for electric vehicle aggregators in the day-ahead reserve market with uncertain EV connectivity. The problem is transformed into a single-level mixed integer nonlinear program using total unimodularity property and other methods, and a sample-based algorithm is developed for solving it, with the effectiveness validated through case studies.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Dong Chen, Kaian Chen, Zhaojian Li, Tianshu Chu, Rui Yao, Feng Qiu, Kaixiang Lin
Summary: This paper proposes an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. By formulating the problem as a cooperative multi-agent reinforcement learning problem and introducing novel algorithms and communication protocols, it achieves superior performance compared to traditional control methods and other algorithms.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jianzhe Liu, Yichen Zhang, Antonio J. Conejo, Feng Qiu
Summary: DC microgrids have potential applications in renewable integration, but the negative impedance effect of constant power loads (CPLs) can lead to instability. This paper proposes an innovative control synthesis algorithm to guarantee a theoretically guaranteed region of attraction (ROA) for a general DC microgrid, covering its entire operating range.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Jiazuo Hou, Jun Wang, Yue Song, Wei Sun, Yunhe Hou
Summary: This paper proposes and investigates a stealthy false data injection cyber-attack targeting the small-signal angle stability (SSAS) of a power system. The attack misleads the optimal power flow (OPF) and compromises operation points, leading to damages to the SSAS margin. The paper establishes a novel bi-level model and formulates closed-form expressions to analyze the effects of the attack on the SSAS margin and operation cost. Simulation results demonstrate the significant damaging effects of the proposed attack and the conflict between the two attacking purposes.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Computer Science, Information Systems
Wenqian Yin, Shuanglei Feng, Jiazuo Hou, Chengchen Qian, Yunhe Hou
Summary: This article proposes a decision-dependent stochastic approach for the joint operation and maintenance of overhead transmission lines (OTLs) in order to determine the optimal maintenance sequence. By modeling the multi-period maintenance process of OTLs as a stochastic process with decision-dependent uncertainty, a two-stage stochastic model is formulated. A unique modeling transformation technique is adopted to tackle the coupling relation between decisions and uncertainty. Case studies verify the effectiveness of the proposed method for postsandstorm maintenance scheduling.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Information Systems
Wenqian Yin, Yujia Li, Jiazuo Hou, Miao Miao, Yunhe Hou
Summary: The global experience in wind farm development shows that the prediction error of wind power is related to the scale of wind farms due to spatial correlation. This article proposes a coordinated planning model for large-scale wind farms and energy storage that considers decision-dependent uncertainties. The model includes a DDU model and an affine function-based solution method for capturing and handling the uncertainties in wind power predictions and decisions.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wenqian Yin, Shuanglei Feng, Yunhe Hou
Summary: This study proposes a stochastic expansion planning model for large-scale wind farms considering decision-dependent uncertainty (DDU) and investigates the coupling relationship between expansion decisions and DDU. The model is established based on the Point Estimate Method (PEM) and an iterative solution method is proposed to handle DDU. The effects of DDU on wind farm expansion schemes are analyzed and case studies validate the proposed model and solution method.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yonghong Chen, Feng Pan, Feng Qiu, Alinson S. Xavier, Tongxin Zheng, Muhammad Marwali, Bernard Knueven, Yongpei Guan, Peter B. Luh, Lei Wu, Bing Yan, Mikhail A. Bragin, Haiwang Zhong, Anthony Giacomoni, Ross Baldick, Boris Gisin, Qun Gu, Russ Philbrick, Fangxing Li
Summary: This paper summarizes the technical activities of the IEEE Task Force on Solving Large Scale Optimization Problems in Electricity Market and Power System Applications. This Task Force was established to review and analyze the current state of the security-constrained unit commitment (SCUC) business model and its solution techniques in electricity market clearing problems. It also investigates future challenges in market clearing problems and presents efforts in developing benchmark models.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Shiyi Jiang, Jianqiang Cheng, Kai Pan, Feng Qiu, Boshi Yang
Summary: The planning of distributed energy resources is challenging due to uncertainties and complexities. This paper introduces a new approach, the partial sample average approximation (PSAA), using real data to improve computational tractability.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Automation & Control Systems
Shamsun Nahar Edib, Yuzhang Lin, Vinod M. Vokkarane, Feng Qiu, Rui Yao, Bo Chen
Summary: To ensure the proper functioning of a cyber-physical power system, this article proposes the concept of cyber restoration and an optimal restoration scheme for swift recovery of system observability after massive interruptions. By formulating the cyber restoration problem as a mixed integer linear programming problem, considering various constraints, the proposed optimization method is shown to recover system observability much faster than heuristic methods, highlighting the need for systematic cyber restoration research and implementation.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Information Systems
Wenjie Liu, Yunjian Xu, Junhong Liu, Wenqian Yin, Yunhe Hou, Zaiyue Yang
Summary: In this article, we propose a data-driven distributionally robust energy and reserve sharing model considering renewable generation uncertainty and limited communication resources among different agents in electricity markets. We use data-driven distributionally robust chance constraints to determine the reserve capacity and employ an inner approximation approach to convert them into tractable linear constraints. We also develop a communication-censored consensus alternating direction method of multipliers to solve the sharing problem in a fully decentralized manner while considering the limited communication resources in the Internet of Things. Extensive simulations are conducted to verify the effectiveness of the proposed model and theoretical results.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Yongchun Li, Marcia Fampa, Jon Lee, Feng Qiu, Weijun Xie, Rui Yao
Summary: This study focuses on the D-optimal Data Fusion (DDF) problem, which involves selecting new data points to maximize the log determinant of the Fisher information matrix. We prove that the DDF problem is NP-hard and propose two convex integer-programming formulations along with complementary and Lagrangian-dual problems to solve it effectively. Our algorithms, including an exact algorithm and scalable randomized-sampling and local-search algorithms, are tested using real-world data on the placement of new phasor-measurement-units in power grids, demonstrating their efficiency and high-quality outputs.
INFORMS JOURNAL ON COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Qinfei Long, Junhong Liu, Feng Liu, Yunhe Hou
Summary: To mitigate failure risk, a dynamic thermal rating (DTR) sensor can be placed in transmission lines. This paper proposes a submodular optimization-based DTR placement model that considers Braess paradox. A model based on Markov probability and important sampling weight techniques is utilized to quantify failure risk efficiently. The risk model is then applied to analyze the conditions for Braess paradox and reformulate the risk mitigation model with estimation error. A computationally efficient algorithm is designed to solve this nonmonotone submodular optimization, providing a provable approximation guarantee.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Jianzhe Liu, Rui Yao, Feng Qiu, Yang Liu, Kai Sun
Summary: This paper presents an open-source toolbox, PowerSAS.m, which fills the gap of insufficient power system simulation software, especially in terms of implementing semi-analytical solution (SAS) methods for power system steady-state and dynamic simulations. The toolbox implements a novel SAS method, includes various heuristics and simulation techniques, and ensures enhanced computational performance.
IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY
(2023)
