Xiaoshun Zhang

Orcid: 0000-0001-7189-2040

According to our database1, Xiaoshun Zhang authored at least 13 papers between 2015 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2022
Multi-Agent Learning-Based Nearly Non-Iterative Stochastic Dynamic Transactive Energy Control of Networked Microgrids.
IEEE Trans. Smart Grid, 2022

Multi-objective Evolutionary Algorithm for Reactive Power Optimization of Distribution Network Connecting with Renewable Energies and EVs.
Proceedings of the Advances in Swarm Intelligence - 13th International Conference, 2022

2021
A Multiagent Competitive Bidding Strategy in a Pool-Based Electricity Market With Price-Maker Participants of WPPs and EV Aggregators.
IEEE Trans. Ind. Informatics, 2021

Emergency fault affected wide-area automatic generation control via large-scale deep reinforcement learning.
Eng. Appl. Artif. Intell., 2021

2019
Optimal power tracking of doubly fed induction generator-based wind turbine using swarm moth-flame optimizer.
Trans. Inst. Meas. Control, 2019

Many-Objective Optimal Power Dispatch Strategy Incorporating Temporal and Spatial Distribution Control of Multiple Air Pollutants.
IEEE Trans. Ind. Informatics, 2019

Adaptive deep dynamic programming for integrated frequency control of multi-area multi-microgrid systems.
Neurocomputing, 2019

Parallel Cyber-Physical-Social Systems Based Smart Energy Robotic Dispatcher and Knowledge Automation: Concepts, Architectures, and Challenges.
IEEE Intell. Syst., 2019

2018
Consensus Transfer Q-Learning for Decentralized Generation Command Dispatch Based on Virtual Generation Tribe.
IEEE Trans. Smart Grid, 2018

Multi-Agent Bargaining Learning for Distributed Energy Hub Economic Dispatch.
IEEE Access, 2018

Culture Evolution Learning for Optimal Carbon-Energy Combined-Flow.
IEEE Access, 2018

2017
Accelerating bio-inspired optimizer with transfer reinforcement learning for reactive power optimization.
Knowl. Based Syst., 2017

2015
Road Network Representation Method Based on Direction Link Division.
Proceedings of the Information Technology and Intelligent Transportation Systems, 2015


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