Search Results for author: Renchang Dai

Found 6 papers, 0 papers with code

Power Grid Transient Analysis via Open-Source Circuit Simulator: A Case Study of HVDC

no code implementations16 May 2023 Yongli Zhu, Xiang Zhang, Renchang Dai

This paper proposes an electronic circuit simulator-based method to accelerate the power system transient simulation, where the modeling of a generic HVDC (High Voltage Direct Current) system is focused.

Using Terminal Circuit for Power System Electromagnetic Transient Simulation

no code implementations1 Jul 2021 Yijing Liu, Xiang Zhang, Renchang Dai, Guangyi Liu

The modern power system is evolving with increasing penetration of power electronics introducing complicated electromagnetic phenomenon.

Power System Transient Modeling and Simulation using Integrated Circuit

no code implementations6 Jun 2021 Xiang Zhang, Renchang Dai, Peng Wei, Yijing Liu, Guangyi Liu, Zhiwei Wang

Transient stability analysis (TSA) plays an important role in power system analysis to investigate the stability of power system.

Numerical Integration

Autonomous Charging of Electric Vehicle Fleets to Enhance Renewable Generation Dispatchability

no code implementations22 Dec 2020 Reza Bayani, Saeed D. Manshadi, Guangyi Liu, Yawei Wang, Renchang Dai

A total 19% of generation capacity in California is offered by PV units and over some months, more than 10% of this energy is curtailed.

Decision Making

Enhancement of Power Equipment Management Using Knowledge Graph

no code implementations28 Apr 2019 Yachen Tang, Tingting Liu, Guangyi Liu, Jie Li, Renchang Dai, Chen Yuan

Because of data duplication, database decentralization, weak data relations, and sluggish data updates, the power asset management system eager to adopt a new strategy to avoid the information losses, bias, and improve the data storage efficiency and extraction process.

Asset Management Retrieval

Power Market Price Forecasting via Deep Learning

no code implementations18 Sep 2018 Yongli Zhu, Songtao Lu, Renchang Dai, Guangyi Liu, Zhiwei Wang

Then the raw input and output data are preprocessed by unit scaling, and the trained network is tested on the real price data under different input lengths, forecasting horizons and data sizes.

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