Wanjun Huang
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View article: An Efficient Heuristic Algorithm for Stochastic Multi-Timescale Network Reconfiguration for Medium- and High-Voltage Distribution Networks with High Renewables
An Efficient Heuristic Algorithm for Stochastic Multi-Timescale Network Reconfiguration for Medium- and High-Voltage Distribution Networks with High Renewables Open
To handle the uncertainties brought by the increasing penetration of renewable energy sources and random loads, we design a stochastic multi-timescale distribution network reconfiguration (SMTDNR) framework to coordinate diverse scheduling…
View article: Ambient Signals based Load Modeling with Two Three-phase Induction Motors
Ambient Signals based Load Modeling with Two Three-phase Induction Motors Open
The traditional electric power system simulation and calculation are based on the simple load model including one motor and one static load. On the one hand, the power system load is getting more and more complex. On the other hand, it’s p…
View article: Deep-Learning-Aided Voltage-Stability-Enhancing Stochastic Distribution Network Reconfiguration
Deep-Learning-Aided Voltage-Stability-Enhancing Stochastic Distribution Network Reconfiguration Open
Power distribution networks are approaching their voltage stability boundaries due to the severe voltage violations and the inadequate reactive power reserves caused by the increasing renewable generations and dynamic loads. In the broad e…
View article: DeepOPF-AL: Augmented Learning for Solving AC-OPF Problems with Multiple Load-Solution Mappings
DeepOPF-AL: Augmented Learning for Solving AC-OPF Problems with Multiple Load-Solution Mappings Open
The existence of multiple load-solution mappings of non-convex AC-OPF problems poses a fundamental challenge to deep neural network (DNN) schemes. As the training dataset may contain a mixture of data points corresponding to different load…
View article: Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration
Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration Open
We propose an improved successive branch reduction (SBR) method to solve stochastic distribution network reconfiguration (SDNR), a mixed-integer program that is known to be computationally challenging. First, for a special distribution net…
View article: Type Classification and Engineering Stability Evaluation of Permafrost Wetlands on the Qinghai–Tibet Plateau
Type Classification and Engineering Stability Evaluation of Permafrost Wetlands on the Qinghai–Tibet Plateau Open
On the Qinghai–Tibet Plateau area, the permafrost and the wetlands are interdependent to form a symbiotic system, called permafrost wetlands (PWs). Due to the extremely complex hydrothermal conditions, the PWs greatly impact road stability…
View article: DeepOPF-V: Solving AC-OPF Problems Efficiently
DeepOPF-V: Solving AC-OPF Problems Efficiently Open
AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future to maintain stable and economic power system operation. To tackle this challenge, a deep neural network-based voltage-constrained approach (DeepOPF-V) …
View article: DeepOPF-V: Solving AC-OPF Problems Efficiently
DeepOPF-V: Solving AC-OPF Problems Efficiently Open
AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future to maintain stable and economic power system operation. To tackle this challenge, a deep neural network-based voltage-constrained approach (DeepOPF-V) …
View article: Parameters of tested sub-transmission system
Parameters of tested sub-transmission system Open
It contains parameters of the tested sub-transmission systems with 9, 14, 15,16,17,18,20,24 buses, respectively.
View article: Modified 69-bus distribution system
Modified 69-bus distribution system Open
This file provides the line and load data of modified 69-bus system.
View article: Supplementary Materials for "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach"
Supplementary Materials for "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach" Open
This file provides supplementary materials for the paper titled "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach"
View article: Line and load data for the modified 69-bus distribution system and Shandong Power Grid
Line and load data for the modified 69-bus distribution system and Shandong Power Grid Open
This file provides the line and load data of modified 69-bus distribution system and a practical large-scale distribution system from Shandong Power Grid.
View article: Dataset of DeepOPF-V: Modified IEEE 300-bus system with real-time load data
Dataset of DeepOPF-V: Modified IEEE 300-bus system with real-time load data Open
This dataset was generated for the case study in modified IEEE 300-bus system using real-time load data in [1].[1] W. Huang, X. Pan, M. Chen, and S. H. Low, "DeepOPF-V: Solving AC-OPF Problems Efficiently," arXiv preprint arXiv:2103.11793,…
View article: Supplementary Materials for "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach"
Supplementary Materials for "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach" Open
This file provides supplementary materials for the paper titled "Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach".
View article: Parameters of 30-bus,118-bus and 300-bus test systems
Parameters of 30-bus,118-bus and 300-bus test systems Open
Details of the three files are as below: 1. case30_ieee.m: Power flow data for IEEE 30-bus test case from IEEE PES Power Grid Library - Optimal Power Flow - v20.07 (https://github.com/power-grid-lib/pglib-opf). 2. case118_ieee_modified.m: …
View article: Historical data sets and parameters of the two-area system
Historical data sets and parameters of the two-area system Open
The zip file contains the generated historical data of DG output and load demand of the two-area system in numerical tests. The PDF file contains the parameters of the two-area system.
View article: IEEE 33-bus system and 337-bus practical system
IEEE 33-bus system and 337-bus practical system Open
Base case three-phase load profiles and branch parameters for the IEEE 33-bus distribution system and 337-bus practical system.
View article: Historical_data_set and parameters of a two-area system
Historical_data_set and parameters of a two-area system Open
The dataset contains the generated historical data of DG output and load demand for the two-area system in the study.
View article: IEEE 33-bus system and 337-bus practical system
IEEE 33-bus system and 337-bus practical system Open
Base case three-phase load profiles and branch parameters for the IEEE 33-bus distribution system and 337-bus practical system.
View article: Historical data sets and parameters of the two-area system
Historical data sets and parameters of the two-area system Open
The zip file contains the generated historical data of DG output and load demand of the two-area system in numerical tests. The PDF file contains the parameters of the two-area system.
View article: Historical_data_set.zip
Historical_data_set.zip Open
The dataset contains the generated historical data of DG output and load demand for the two-area system in the study.
View article: Historical_data_set and parameters of a two-area system
Historical_data_set and parameters of a two-area system Open
The dataset contains the generated historical data of DG output and load demand for the two-area system in the study.
View article: Historical_data_set.zip
Historical_data_set.zip Open
The dataset contains the generated historical data of DG output and load demand of the two-area system in the study.
View article: Supplementary Materials(Data of IEEE 33-bus and 123-bus test systems)
Supplementary Materials(Data of IEEE 33-bus and 123-bus test systems) Open
Bus and branch data for IEEE 33-bus and 123-bus test systems.
View article: Historical_data_set.zip
Historical_data_set.zip Open
It contains the generated historical data for the two-area system in the study.