
-
Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability
Transient stability of power systems is becoming increasingly important ...
read it
-
Multi-Agent Reinforcement Learning in Cournot Games
In this work, we study the interaction of strategic agents in continuous...
read it
-
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks
This paper focuses on finding reinforcement learning policies for contro...
read it
-
Transfer Learning for HVAC System Fault Detection
Faults in HVAC systems degrade thermal comfort and energy efficiency in ...
read it
-
Learning in Cournot Games with Limited Information Feedback
In this work, we study the interaction of strategic players in continuou...
read it
-
Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach
Probabilistic power flow (PPF) plays a critical role in the analysis of ...
read it
-
A tractable ellipsoidal approximation for voltage regulation problems
We present a machine learning approach to the solution of chance constra...
read it
-
A Capacity-Price Game for Uncertain Renewables Resources
Renewable resources are starting to constitute a growing portion of the ...
read it
-
Real-Time Prediction of the Duration of Distribution System Outages
This paper addresses the problem of predicting duration of unplanned pow...
read it
-
Bayesian Renewables Scenario Generation via Deep Generative Networks
We present a method to generate renewable scenarios using Bayesian proba...
read it
-
Uncertainty in Multi-Commodity Routing Networks: When does it help?
We study the equilibrium quality under user uncertainty in a multi-commo...
read it
-
Distribution System Voltage Control under Uncertainties
Voltage control plays an important role in the operation of electricity ...
read it
-
An Optimal Treatment Assignment Strategy to Evaluate Demand Response Effect
Demand response is designed to motivate electricity customers to modify ...
read it
-
Learning Temporal Dependence from Time-Series Data with Latent Variables
We consider the setting where a collection of time series, modeled as ra...
read it
-
Online Active Linear Regression via Thresholding
We consider the problem of online active learning to collect data for re...
read it
-
A Sparse Linear Model and Significance Test for Individual Consumption Prediction
Accurate prediction of user consumption is a key part not only in unders...
read it