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Found 12 papers, 0 papers with code
Power grid operational risk assessment using graph neural network surrogates
The excellent accuracy of GNN-based reliability and risk assessment further suggests that GNN surrogate has the potential to be applied in real-time and hours-ahead risk quantification.
Operational risk quantification of power grids using graph neural network surrogates of the DC OPF
MC simulation necessitates solving a large number of DC OPF problems corresponding to the samples of stochastic grid variables (power demand and renewable generation), which is computationally prohibitive.
Just-In-Time Learning for Operational Risk Assessment in Power Grids
In a grid with a significant share of renewable generation, operators will need additional tools to evaluate the operational risk due to the increased volatility in load and generation.
A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives
This second paper presents a literature review of key enabling technologies of digital twins, with an emphasis on uncertainty quantification, optimization methods, open source datasets and tools, major findings, challenges, and future directions.
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies
In part two of this review, the role of uncertainty quantification and optimization are discussed, a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared.
Modeling contaminant intrusion in water distribution networks based on D numbers
To demonstrate the efficiency of the proposed method, we apply it to the water distribution networks to estimate the risk of contaminant intrusion.
D-CFPR: D numbers extended consistent fuzzy preference relations
How to express an expert's or a decision maker's preference for alternatives is an open issue.
A Physarum-Inspired Approach to Optimal Supply Chain Network Design at Minimum Total Cost with Demand Satisfaction
A supply chain is a system which moves products from a supplier to customers.
Parameter estimation based on interval-valued belief structures
Parameter estimation based on uncertain data represented as belief structures is one of the latest problems in the Dempster-Shafer theory.
A Visibility Graph Averaging Aggregation Operator
The problem of aggregation is considerable importance in many disciplines.
An Adaptive Amoeba Algorithm for Shortest Path Tree Computation in Dynamic Graphs
When the edge weight changes, the proposed algorithm can recognize the affected vertices and reconstruct them spontaneously.
Ranking basic belief assignments in decision making under uncertain environment
Dempster-Shafer theory (D-S theory) is widely used in decision making under the uncertain environment.
