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01/13/2022
The Padé matrix pencil method with spurious pole information assimilation
We present a novel method for calculating Padé approximants that is capa...
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12/23/2020
Rethink AI-based Power Grid Control: Diving Into Algorithm Design
Recently, deep reinforcement learning (DRL)-based approach has shown pro...
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11/08/2019
Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach
With the increasing complexity of modern power systems, conventional dyn...
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04/24/2019
Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning
Modern power grids are experiencing grand challenges caused by the stoch...
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03/26/2019
Probabilistic Load Forecasting via Point Forecast Feature Integration
Short-term load forecasting is a critical element of power systems energ...
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03/26/2019
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis
Short-term load forecasting (STLF) is essential for the reliable and eco...
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02/20/2019
Submodular Load Clustering with Robust Principal Component Analysis
Traditional load analysis is facing challenges with the new electricity ...
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01/31/2019
Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications
Design of an effective and reliable communication network supporting sma...
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11/29/2018
A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation
This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN...
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11/29/2018
A Neuron-Network-Based Optimal Control of Ultra-Capacitors with System Uncertainties
In this paper, a neural-network (NN)-based online optimal control method...
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08/18/2017