Search Results for author: Jiajun Duan

Found 6 papers, 0 papers with code

On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control

no code implementations11 Dec 2020 Ruisheng Diao, Di Shi, Bei Zhang, Siqi Wang, Haifeng Li, Chunlei Xu, Tu Lan, Desong Bian, Jiajun Duan

Deriving fast and effectively coordinated control actions remains a grand challenge affecting the secure and economic operation of today's large-scale power grid.

Optimization and Control Systems and Control Systems and Control

Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning

no code implementations24 Apr 2019 Ruisheng Diao, Zhiwei Wang, Di Shi, Qianyun Chang, Jiajun Duan, Xiaohu Zhang

Modern power grids are experiencing grand challenges caused by the stochastic and dynamic nature of growing renewable energy and demand response.

Probabilistic Load Forecasting via Point Forecast Feature Integration

no code implementations26 Mar 2019 Qicheng Chang, Yishen Wang, Xiao Lu, Di Shi, Haifeng Li, Jiajun Duan, Zhiwei Wang

In the first stage, all related features are utilized to train a point forecast model and also obtain the feature importance.

Feature Importance Load Forecasting

Submodular Load Clustering with Robust Principal Component Analysis

no code implementations20 Feb 2019 Yishen Wang, Xiao Lu, Yiran Xu, Di Shi, Zhehan Yi, Jiajun Duan, Zhiwei Wang

Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including photovoltaics (PV), electric vehicles (EV), and energy storage systems (ESS).

Load Forecasting

A Neural-Network-Based Optimal Control of Ultra-Capacitors with System Uncertainties

no code implementations29 Nov 2018 Jiajun Duan, Zhehan Yi, Di Shi, Hao Xu, Zhiwei Wang

Conventional control strategies usually produce large disturbances to buses during charging and discharging (C&D) processes of UCs, which significantly degrades the power quality and system performance, especially under fast C&D modes.

A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation

no code implementations29 Nov 2018 Yao Cui, Zhehan Yi, Jiajun Duan, Di Shi, Zhiwei Wang

This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN) based algorithm for Photovoltaic (PV) maximum power point tracking (MPPT).

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