崔承刚｜上海电力大学｜学者主页

期刊论文

2026

孤岛微电网环境下基于物理模型引导的深度强化学习VSG频率控制方法

赵后起，邓卫，崔承刚，肖浩，裴玮

《中国电机工程学报》

2026

基于RCBF的Boost变换器安全强化学习控制策略

王想想，崔承刚，惠培峰，梁琨

《现代电子技术》

2026

Model-Free DRL Control for Power Inverters: From Policy Learning to Real-Time Implementation via Knowledge Distillation

Yang Yang, Chenggang Cui, Xitong Niu, Jiaming Liu, Chuanlin Zhang

arXiv.org

DOI

2025

基于安全强化学习的热电联产机组经济调度策略研究

王欣，崔承刚，王想想，朱平

《系统仿真学报》

DOI

2025

基于融合物理模型与数据驱动模型的电池SOH估计方法

闫淏迪，崔承刚，陈辉，章珂，陈静薇，孔巧玲

《电源技术》

2025

Research on a Two-Layer Demand Response Framework for Electric Vehicle Users and Aggregators Based on LLMs

Zhaoyi Zhang, Chenggang Cui, Ning Yang, Chuanlin Zhang

arXiv.org

DOI

2024

基于聚合时空图卷积网络的多风场超短期风速预测

徐辰晓，崔承刚，郭为民，杨宁，刘备，孟青叶

《电源学报》

2024

Substation Equipment Fault Diagnosis Based On A Multimodal Large Model

Feng Cheng, Chenggang Cui, Shi-Qing Fang

2024 6th International Conference on Electrical Engineering and Control Technologies (CEECT)

DOI

2024

Assessment of Demand Response Potential for Commercial Air Conditioning Based on Battery Energy Storage Strategy

Li Zhang, Shaodi Zhang, Chenggang Cui, Hui Chen, Pinpin Zhou

2024 6th International Conference on Electrical Engineering and Control Technologies (CEECT)

DOI

2023

基于地基云图云量特征的光伏发电功率区间预测

刘翼飞，崔承刚

《南方电网技术》

2023

基于深度强化学习的Boost变换器控制策略

戴宇轩，崔承刚

《系统仿真学报》

DOI

2022

基于深度强化学习的数据中心空调系统优化控制

丁瑞华，崔承刚，王逸轩，张少迪

《低温与超导》

2021

基于强化学习的中央空调系统温度控制与节能

李晓彤，崔承刚，杨宁，陈辉

《计算机仿真》

2021

深度强化学习应用于电力系统控制研究综述

宋鹏飞，杨宁，崔承刚，闫南，奚培锋

《数智技术研究与应用》

2020

基于多风电相关性场景生成法的配电网随机多目标无功优化

倪爽，崔承刚，郑庆荣，郝慧玲，杨宁，奚培锋

《浙江电力》

DOI

2020

考虑柔性负荷响应的综合能源系统多尺度优化调度研究

鞠文韬，崔承刚，杨锦成，奚培锋

《浙江电力》

DOI

2019

基于ARIMA LSTM组合模型的楼宇短期负荷预测方法研究

李鹏辉，崔承刚，杨宁，陈辉

《上海电力大学学报》

2019

基于深度学习的LSTM光伏预测

崔承刚，邹宇航

《上海电力大学学报》

2019

基于深度强化学习的微电网储能调度策略研究

王亚东，崔承刚，钱申晟，杨宁，陈辉，奚培锋

《可再生能源》

2018

光伏发电功率预测斜面辐射组合模型的评估研究

魏嫽嫽，崔承刚，杨宁，陈辉

《可再生能源》

2018

关于能源企业推进能源互联网建设的实施研究

杨锦成，盛晏，崔承刚

《现代商业》

2018

能源互联网储能技术应用研究

马守达，杨锦成，崔承刚，盛晏

《发电技术》

2018

Research on Operation Optimization of Integrated Energy System Based on Importance Scenario Analysis Method

Hao-Jie Zhang, Chenggang Cui, Jianli Zhao, Yuanyuan Gu, N. Yang

2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)

DOI

2017

The Kriging model based scenario generation and its application in the energy internet with high wind penetration

Xiao-dong He, Chenggang Cui, N. Yang

2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)

DOI

2016

分布式能源站三联供系统优化运行策略研究

钱虹，杨明，陈丹，崔承刚

《热能动力工程》

会议论文

2024

A Deep Reinforcement Learning Control Strategy with Integrated Droop Control for Parallel DC-DC Buck Converters with CPLs

Zhongyang Fan, Chenggang Cui, Tianxiao Yang, Chuanlin Zhang

Abstracts of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024 Part I

DOI

预印本

2025

Dynamic Incentive Strategies for Smart EV Charging Stations: An LLM-Driven User Digital Twin Approach

Yichen Sun, Chenggang Cui, Chuanlin Zhang, Chunyang Gong

arXiv preprint

2025

Automated Heuristic Design for Unit Commitment Using Large Language Models

Junjin Lv, Chenggang Cui, Shaodi Zhang, Hui Chen, Chunyang Gong, Jiaming Liu

arXiv preprint

2025

GenControl: Generative AI-Driven Autonomous Design of Control Algorithms

Chenggang Cui, Jiaming Liu, Peifeng Hui, Pengfeng Lin, Chuanlin Zhang

arXiv preprint

2024

On Physics-Informed Neural Network Control for Power Electronics

Peifeng Hui, Chenggang Cui, Pengfeng Lin, Amer M. Y. M. Ghias, Xitong Niu, Chuanlin Zhang

arXiv preprint

2024

Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics

Chenggang Cui, Jiaming Liu, Junkang Feng, Peifeng Hui, Amer M. Y. M. Ghias, Chuanlin Zhang

arXiv preprint

2024

Electric Vehicle User Charging Behavior Analysis Integrating Psychological and Environmental Factors: A Statistical-Driven LLM based Agent Approach

Chuanlin Zhang, Junkang Feng, Chenggang Cui, Pengfeng Lin, Hui Chen, Yan Xu, A. M. Y. M. Ghias, Qianguang Ma, Pei Zhang

arXiv preprint

2021

Transferring Reinforcement Learning for DC-DC Buck Converter Control via Duty Ratio Mapping: From Simulation to Implementation

Chenggang Cui, Tianxiao Yang, Yuxuan Dai, Chuanlin Zhang

arXiv preprint

2020

An Intelligent Control Strategy for buck DC-DC Converter via Deep Reinforcement Learning

Chenggang Cui, Nan Yan, Chuanlin Zhang

arXiv preprint

崔承刚

精选作品

期刊论文

孤岛微电网环境下基于物理模型引导的深度强化学习VSG频率控制方法

基于RCBF的Boost变换器安全强化学习控制策略

Model-Free DRL Control for Power Inverters: From Policy Learning to Real-Time Implementation via Knowledge Distillation

基于安全强化学习的热电联产机组经济调度策略研究

基于融合物理模型与数据驱动模型的电池SOH估计方法

Research on a Two-Layer Demand Response Framework for Electric Vehicle Users and Aggregators Based on LLMs

基于聚合时空图卷积网络的多风场超短期风速预测

Substation Equipment Fault Diagnosis Based On A Multimodal Large Model

Assessment of Demand Response Potential for Commercial Air Conditioning Based on Battery Energy Storage Strategy

基于地基云图云量特征的光伏发电功率区间预测

基于深度强化学习的Boost变换器控制策略

基于深度强化学习的数据中心空调系统优化控制

基于强化学习的中央空调系统温度控制与节能

深度强化学习应用于电力系统控制研究综述

基于多风电相关性场景生成法的配电网随机多目标无功优化

考虑柔性负荷响应的综合能源系统多尺度优化调度研究

基于ARIMA LSTM组合模型的楼宇短期负荷预测方法研究

基于深度学习的LSTM光伏预测

基于深度强化学习的微电网储能调度策略研究

光伏发电功率预测斜面辐射组合模型的评估研究

关于能源企业推进能源互联网建设的实施研究

能源互联网储能技术应用研究

Research on Operation Optimization of Integrated Energy System Based on Importance Scenario Analysis Method

The Kriging model based scenario generation and its application in the energy internet with high wind penetration

分布式能源站三联供系统优化运行策略研究

会议论文

A Deep Reinforcement Learning Control Strategy with Integrated Droop Control for Parallel DC-DC Buck Converters with CPLs

预印本

Dynamic Incentive Strategies for Smart EV Charging Stations: An LLM-Driven User Digital Twin Approach

Automated Heuristic Design for Unit Commitment Using Large Language Models

GenControl: Generative AI-Driven Autonomous Design of Control Algorithms

On Physics-Informed Neural Network Control for Power Electronics

Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics

Electric Vehicle User Charging Behavior Analysis Integrating Psychological and Environmental Factors: A Statistical-Driven LLM based Agent Approach

Transferring Reinforcement Learning for DC-DC Buck Converter Control via Duty Ratio Mapping: From Simulation to Implementation

An Intelligent Control Strategy for buck DC-DC Converter via Deep Reinforcement Learning

研究方向