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Found 12 papers, 1 papers with code
Guaranteeing Service in Connected Microgrids: Storage Planning and Optimal Power Sharing Policy
To address this issue, battery energy sources (BESs) are being increasingly used as a promising solution to counter the uncertainty associated with RES power production.
Causal Structure Recovery of Linear Dynamical Systems: An FFT based Approach
We demonstrate that the computational complexity of recovering the causation structure for the vector auto-regressive (VAR) model is $O(Tn^3N^2)$, where $n$ is the number of nodes, $T$ is the number of samples, and $N$ is the largest time-lag in the dependency between entities.
Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
In this article, the optimal sample complexity of learning the underlying interactions or dependencies of a Linear Dynamical System (LDS) over a Directed Acyclic Graph (DAG) is studied.
Transactive Framework for Dynamic Energy Storage Allocation for Critical Load Management
Although the emerging transactive energy management techniques improve the grid reliability, the inherent uncertainty of RES poses a challenge in meeting the power demand of the critical infrastructure in the microgrid unless sufficient battery energy storage is maintained.
Topology Identification under Spatially Correlated Noise
It is shown, under the assumption that the correlations are affine in nature, such network of nodal interactions is equivalent to a network with added agents, represented by nodes that are latent, where no corresponding time-series measurements are available; however, here all exogenous excitements are spatially (that is, across agents) uncorrelated.
Hindering loads prompt clustered configurations that enhance stability during cargo transport by multiple Kinesin-1
Transport of intracellular cargo is often mediated by teams of molecular motors that function in a chaotic environment under varying conditions.
DC-DistADMM: ADMM Algorithm for Constrained Distributed Optimization over Directed Graphs
This article reports an algorithm for multi-agent distributed optimization problems with a common decision variable, local linear equality and inequality constraints and set constraints with convergence rate guarantees.
Topology Learning of Linear Dynamical Systems with Latent Nodes using Matrix Decomposition
It is shown that for a large class of systems, the unique decomposition of imaginary part of the IPSDM of observed nodes, a skew symmetric matrix, into the sparse and the low-rank components is sufficient to identify the moral graph of the observed nodes as well as the Markov Blanket of latent nodes.
Gradient-Consensus: Linearly Convergent Distributed Optimization Algorithm over Directed Graphs
The optimize then agree approach decouples the optimization step and the consensus step in a distributed optimization framework.
Physics Informed Topology Learning in Networks of Linear Dynamical Systems
Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines.
Learning the Exact Topology of Undirected Consensus Networks
In this article, we present a method to learn the interaction topology of a network of agents undergoing linear consensus updates in a non invasive manner.
Exact Topology Reconstruction of Radial Dynamical Systems with Applications to Distribution System of the Power Grid
In this article we present a method to reconstruct the interconnectedness of dynamically related stochastic processes, where the interactions are bi-directional and the underlying topology is a tree.
