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On Machine Learning-Based Techniques for Future Sustainable and Resilient Energy Systems

https://doi.org/10.1109/tste.2022.3194728
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Machine learning for ranking day-ahead decisions in the context of short-term operation planning
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Data-driven accident consequence assessment on urban gas pipeline network based on machine learning
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Recent Developments in Machine Learning for Energy Systems Reliability Management
inferredcites →https://doi.org/10.1109/jsyst.2015.2389272openalex-snapshot
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inferredcites →https://doi.org/10.1109/jsyst.2018.2853554openalex-snapshot
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inferredcites →https://doi.org/10.1109/jsyst.2020.3017640openalex-snapshot
Development and Validation of Artificial Neural Network-Based Tools for Forecasting of Power System Inertia With Wind Farms Penetration
inferredcites →https://doi.org/10.1109/mnet.2014.6863136openalex-snapshot
Cascading effects in interdependent networks
inferredcites →https://doi.org/10.1109/mpe.2015.2397334openalex-snapshot
The Grid: Stronger, Bigger, Smarter?: Presenting a Conceptual Framework of Power System Resilience
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Toward Bulk Power System Resilience: Approaches for Regional Transmission Operators
inferredcites →https://doi.org/10.1109/mpe.2020.2985439openalex-snapshot
From Reliability to Resilience: Planning the Grid Against the Extremes
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inferredcites →https://doi.org/10.1109/pesgm41954.2020.9281506openalex-snapshot
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inferredcites →https://doi.org/10.1109/pesgm41954.2020.9281518openalex-snapshot
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inferredcites →https://doi.org/10.1109/powercon.2014.6993789openalex-snapshot
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inferredcites →https://doi.org/10.1109/rws50334.2020.9241293openalex-snapshot
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inferredcites →https://doi.org/10.1109/tcns.2021.3112764openalex-snapshot
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inferredcites →https://doi.org/10.1109/td39804.2020.9299978openalex-snapshot
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inferredcites →https://doi.org/10.1109/tii.2021.3074397openalex-snapshot
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inferredcites →https://doi.org/10.1109/tii.2021.3086080openalex-snapshot
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inferredcites →https://doi.org/10.1109/tii.2022.3166215openalex-snapshot
Hybrid Multiagent Reinforcement Learning for Electric Vehicle Resilience Control Towards a Low-Carbon Transition
inferredcites →https://doi.org/10.1109/tpas.1967.291728openalex-snapshot
The Adaptive Reliability Control System
inferredcites →https://doi.org/10.1109/tpwrd.2016.2582519openalex-snapshot
Graph Spectra Based Controlled Islanding for Low Inertia Power Systems
inferredcites →https://doi.org/10.1109/tpwrs.2004.825981openalex-snapshot
Definition and Classification of Power System Stability IEEE/CIGRE Joint Task Force on Stability Terms and Definitions
inferredcites →https://doi.org/10.1109/tpwrs.2013.2238684openalex-snapshot
Transient Instability Prediction Using Decision Tree Technique
inferredcites →https://doi.org/10.1109/tpwrs.2013.2267557openalex-snapshot
Online Static Security Assessment Module Using Artificial Neural Networks
inferredcites →https://doi.org/10.1109/tpwrs.2017.2664141openalex-snapshot
Metrics and Quantification of Operational and Infrastructure Resilience in Power Systems
inferredcites →https://doi.org/10.1109/tpwrs.2018.2842709openalex-snapshot
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inferredcites →https://doi.org/10.1109/tpwrs.2018.2881359openalex-snapshot
Data-Driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method With Continuous Action Search
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From Optimization-Based Machine Learning to Interpretable Security Rules for Operation
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inferredcites →https://doi.org/10.1109/tpwrs.2020.2973699openalex-snapshot
Resilience Assessment of Interdependent Energy Systems Under Hurricanes
inferredcites →https://doi.org/10.1109/tpwrs.2020.3041774openalex-snapshot
Definition and Classification of Power System Stability – Revisited & Extended
inferredcites →https://doi.org/10.1109/tpwrs.2021.3056543openalex-snapshot
Distribution System Resilience Under Asynchronous Information Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tpwrs.2021.3066336openalex-snapshot
Line Failure Localization of Power Networks Part I: Non-Cut Outages
inferredcites →https://doi.org/10.1109/tpwrs.2021.3078446openalex-snapshot
A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources
inferredcites →https://doi.org/10.1109/tpwrs.2021.3086031openalex-snapshot
Data-Driven Classifier for Extreme Outage Prediction Based On Bayes Decision Theory
inferredcites →https://doi.org/10.1109/tpwrs.2021.3115399openalex-snapshot
Deep Learning Based Model-Free Robust Load Restoration to Enhance Bulk System Resilience With Wind Power Penetration
inferredcites →https://doi.org/10.1109/tsg.2015.2397318openalex-snapshot
Resilient Operation of Multiple Energy Carrier Microgrids
inferredcites →https://doi.org/10.1109/tsg.2016.2606888openalex-snapshot
Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids
inferredcites →https://doi.org/10.1109/tsg.2018.2873001openalex-snapshot
A Deep Learning-Based Feature Extraction Framework for System Security Assessment
inferredcites →https://doi.org/10.1109/tsg.2019.2963796openalex-snapshot
Design and Validation of a Wide Area Monitoring and Control System for Fast Frequency Response
inferredcites →https://doi.org/10.1109/tsg.2020.3009401openalex-snapshot
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications
inferredcites →https://doi.org/10.1109/tste.2018.2825780openalex-snapshot
Predictive Risk Analytics for Weather-Resilient Operation of Electric Power Systems
inferredcites →https://doi.org/10.12688/digitaltwin.17435.1openalex-snapshot
Digital twins and their use in future power systems
inferredcites →https://doi.org/10.2172/1177743openalex-snapshot
Conceptual Framework for Developing Resilience Metrics for the Electricity, Oil, and Gas Sectors in the United States
inferredcites →https://doi.org/10.23919/pscc.2018.8442566openalex-snapshot
Using Machine Learning to Enable Probabilistic Reliability Assessment in Operation Planning
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Explaining and Harnessing Adversarial Examples
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A Multivariate Density Forecast Approach for Online Power System Security Assessment

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Forecasting and Optimization in Low‐Carbon Microgrids: A Hybrid LLM–Based Approach With Synthetic Data and Prophet–XGBoost Baselines
inferred← citeshttps://doi.org/10.1177/0958305x251367102openalex-snapshot
Deep learning in renewable energy forecasting: A cross-dataset evaluation of temporal and spatial models
inferred← citeshttps://doi.org/10.1177/14680874251411976openalex-snapshot
Enhancing real-time energy management in diesel-electric hybrid trains through rule-augmented deep reinforcement learning
inferred← citeshttps://doi.org/10.1177/1748006x231209810openalex-snapshot
A Novel Index for Shearer System Resilience in Underground Coal Mines Based on the Operational Environment
inferred← citeshttps://doi.org/10.1186/s42162-025-00524-6openalex-snapshot
Machine learning applications in energy systems: current trends, challenges, and research directions
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Flexible manufacturing workshop mechanical processing and product scheduling algorithm based on MES
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3399954/v1openalex-snapshot
Predicting renewable energy production outputs from climate factors: A machine learning approach
inferred← citeshttps://doi.org/10.21203/rs.3.rs-9656540/v1openalex-snapshot
Carbon-Aware Self-Healing Smart Grid Using Digital Twin and Swarm Artificial Intelligence for Sustainable Power System Resilience
inferred← citeshttps://doi.org/10.21285/1814-3520-2024-2-346-359openalex-snapshot
Smart technologies and solutions for future sustainable and resilient energy systems
inferred← citeshttps://doi.org/10.2139/ssrn.4900358openalex-snapshot
Unified Resilience Model Using Deep Learning for Assessing Power System Performance
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Enhanced Resilience and Efficiency in Multi-Energy Systems via Stochastic Gradient-Driven Robust Optimization
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A Comprehensive Review on Integrating Climate Science and Machine Learning for Power System Resilience
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Calculation method of carbon flow distribution in load-intensive regional energy centers
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Evaluation of the effectiveness of energy sustainability measures through the dynamic energy consumption model
inferred← citeshttps://doi.org/10.3390/app14209590openalex-snapshot
Classification of Faults in Power System Transmission Lines Using Deep Learning Methods with Real, Synthetic, and Public Datasets
inferred← citeshttps://doi.org/10.3390/electronics15204589openalex-snapshot
A Coordinated Active and Reactive Power Optimization Method for Integrated Energy System Based on an XGBoost Surrogate Model for Voltage Stability Margin
inferred← citeshttps://doi.org/10.3390/en18123067openalex-snapshot
A Bibliometric Assessment of AI, IoT, Blockchain, and Big Data in Renewable Energy-Oriented Power Systems
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Deployment Readiness of Artificial Neural Networks in Power Systems (2020–2024): A Bibliometric and Engineering Assessment Using a Domain-Level Evaluation Framework
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Artificial Intelligence for Resilient Integrated Energy Systems: a Review and Research Agenda for Smart Climate-Neutral Cities
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Perspective Chapter: The Role of Machine Learning in Developing Sustainable and Resilient Interconnected Infrastructure Systems
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