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A Reinforcement Learning Embedded Surrogate Lagrangian Relaxation Method for Fast Solving Unit Commitment Problems

IEEE Transactions on power Systems 2025年

作者： Zhu, Yuhang Cui, Gaochen Liu, Anbang Jia, Qing-Shan Guan, Xiaohong Zhai, Qiaozhu Guo, Qi Guo, Xianping BNRist CFINS Department of Automation Tsinghua University Beijing100084 China Xi'an Jiaotong University MOEKLINNS Laboratory Xi'an710049 China Xi'an Jiaotong University MOEKLINNS Lab Systems Engineering Institute Xi'an710049 China China Southern Power Grid Electric Power Research Institute Guangdong Guangzhou510630 China Sun Yat-Sen University School of Mathematics Guangzhou510275 China

Unit commitment problems are operation optimization problems solved by independent system operators (ISOs). These problems generally need to be solved within a limited time, and the quality of the solution can significantly impact the benefit of the power system. Due to the combinatorial complexities, quickly solving large-scale UC problems is particularly challenging and proposing an efficient solution methodology is crucial. In this paper, to accelerate solving speed, we embed reinforcement learning (RL) within the surrogate Lagrangian relaxation (SLR) framework. This approach leverages decomposition and machine learning to reduce the complexity of solving UC problems. By relaxing coupling constraints, the entire problem is decomposed into a set of sub-problems, each associated with a unit and significantly reduced in complexity. These sub-problems are then novelly formulated as Markov decision processes (MDPs), and a novel RL algorithm is used to rapidly generate high-quality feasible solutions. Our method substantially improves the overall speed of SLR and is applicable for solving large-scale UC problems. Numerical experiments on the IEEE 118-bus system and the 10K-bus system demonstrate that our method can obtain near-optimal solutions with no more than 3% performance degradation while achieving a speedup of 25 ∼ 110 times compared to Gurobi, the state-of-the-practice solver. © 1969-2012 IEEE.

关键词： Markov processes

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Short-term wind power forecast with turning weather based on DBSCAN-RFE-LightGBM

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Renewable Energy 2025年 251卷

作者： Wu, Zhenlong Fan, Xinyu Bian, Guibin Liu, Yanhong Zhang, Xiaoke Chen, YangQuan School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Zhengzhou University Luoyang471000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Electric Power Research Institute of State Grid Henan Electric Power Company Zhengzhou450052 China Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

At present, the wind power prediction technology is becoming more and more mature, however, the turning weather brings a decrease in prediction accuracy due to its suddenness and instability. In this paper, a wind power prediction method considering the turning period and non-turning period respectively is proposed to weaken the adverse effects caused by turning weather. Firstly, the prediction effects of multiple models are compared, density-based spatial clustering of applications with noise (DBSCAN) is selected as the outlier processing method, recursive feature elimination (RFE) is used as the feature selection method, and Light gradient boosting machine (LightGBM) is used for prediction. The combined prediction method based on DBSCAN-RFE-LightGBM can reduce the influence of abnormal data and redundant features and improve the prediction effect. Then, the sliding window is set to detect the turning period. Considering that the turning weather is an emergency and does not happen frequently, the amount of data is small, which leads to the inability to train the model well. Generative adversarial networks (GAN) are applied to expand the turning period data. The LightGBM is trained and predicted by using the expended turning period data. Finally, the time-division prediction results are merged. Using the data collected from wind farms for short-term power prediction experiments, the time-segment prediction method proposed in this paper with GAN reduces MAE by 1.913 and RMSE by 3.351 on a single unit compared with the non-differentiated period. © 2025 Elsevier Ltd

关键词： Merging

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Robust fault-sensitive synchronization of a class of nonlinear systems

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Chinese Physics B 2011年第2期20卷 148-157页

作者：徐式蕴杨莹刘仙汤涌孙华东 China Electric Power Research Institute State Key Lab for Turbulence and Complex Systems Department of Mechanics and Aerospace EngineeringCollege of EngineeringPeking University Department of Automation Yanshan University

Aiming at enhancing the quality as well as the reliability of synchronization, this paper is concerned with the fault detection issue within the synchronization process for a class of nonlinear systems in the existence of external disturbances. To handle such problems, the concept of robust fault-sensitive （RFS） synchronization is proposed, and a method of determining such a kind of syncbronization is developed. Under the framework of RFS synchronization, the master and the slave systems are robustly synchronized, and at the same time, sensitive to possible faults based on a mixed H_/H~ performance. The design of desired output feedback controller is realized by solving a linear matrix inequality, and the fault sensitivity H index can be optimized via a convex optimization algorithm. A master-slave configuration composed of identical Chua＇s circuits is adopted as a numerical example to demonstrate the effectiveness and applicability of the analytical results.

关键词： nonlinear system synchronization disturbance rejection fault detection

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Simultaneous Identification of Process Structure, Parameters and Time-delay Based on Non-negative Garrote

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International Journal of automation and computing 2020年第6期17卷 873-882页

作者： Jian-Guo Wang Qian-Ping Xiao Tiao Shen Shi-Wei Ma Wen-Tao Rao Yong-Jie Zhang School of Mechatronical Engineering and Automation Shanghai UniversityShanghai Key Lab of Power Station Automation TechnologyShanghai 200072China Institute of Environment and Resources Baosteel Research InstituteShanghai 201900China

In practice,the model structure,parameters and time-delay of the actual process may vary ***,the general identification methods of the 3 items are performed with separate procedures which is very inconvenient in practical *** view of the fact that variable selection procedure can ensure a compact model with robust input-output,relation and in order to explore the feasibility of variable selection algorithm for the simultaneous identification of process structure,parameters and time-delay,non-negative garrote(NNG)algorithm is introduced and applied to system identification and the corresponding procedures are *** application of NNG variable selection algorithm to the identification of single input single output(SISO)system,multiple input multiple output(MIN1O)system and Wood-Berry tower industry are *** identification accuracy and the time-series variable selection results are analyzed and compared between NNG and ordinary least square(OLS)*** derived excellent results show that the proposed NNG-based modeling algorithm can be utilized for simultaneous identification of the model structure,parameters and time-delay with high precision.

关键词： Model structure model parameter time-delay non-negative garrote variable selection.

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Data-driven Thermal Efficiency Modeling and Optimization for Reheating Furnace Based on Statistics Analysis 34

Data-driven Thermal Efficiency Modeling and Optimization for...

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第三十四届中国控制会议

作者： WANG Jian-Guo SHEN Tiao ZHAO Jing-Hui MA Shi-Wei RAO Wen-Tao ZHANG Yong-Jie School of Mechatronical Engineering and Automation Shanghai University Shanghai Key Lab of Power Station Automation Technology Institute of Environment & Resources Baosteel Research Institute

ISBN: (纸本)9781467374439

The rolling reheating furnace is widely used in the large-scale iron and steel plant and the constantly changing dynamic characteristics and the interaction effect between different heating zones become challenges to operate a reheating furnace in an efficient way. In this paper, statistics analysis methods are utilized to justify the significance of the derived variables for the thermal efficiency modeling. By employing nonnegative garrote(NNG) variable selection procedure, an adaptive scheme for thermal efficiency modeling and adjustment is proposed and virtually implemented for a rolling reheating furnace. The detail analysis results show that there is good control precision improvement and large energy-saving benefit when the furnace operation shifts from the present practice to the model-based optimization adjustment.

关键词： Reheating furnace,thermal efficiency,variable selection,data-driven,statistics analysis

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Online Performance Monitoring and Diagnosis Based on RTSID and KPLS 34

Online Performance Monitoring and Diagnosis Based on RTSID a...

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第三十四届中国控制会议

作者： WANG Jian-Guo WANG Jia-Long ZHAO Jing-Hui MA Shi-Wei RAO Wen-Tao ZHANG Yong-Jie School of Mechatronical Engineering and Automation Shanghai UniversityShanghai Key Lab of Power Station Automation Technology Institute of Environment & Resources Baosteel Research Institute

ISBN: (纸本)9781467374439

In the case that the control system performance is detected in poor state, it is desirable that the underlying cause can be found and the information can be used for the adjustment and recovery. Developing a recursive two-stage identification(RTSID) algorithm and a recursive control performance assessment algorithm with kernel partial least square(KPLS), then integrating the proposed identification algorithm into the performance diagnosis, this paper presents an online control performance monitoring and diagnosis strategy for the closed-loop system. The proposed algorithms are applied to the typical research example and the effectiveness of the strategy is validated.

关键词： Control performance monitoring,diagnosis,system identification,closed-loop,online

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A Novel Soft Switching Two-Stage Heating power Supply Topology for Silicon Growth Furnace 35

A Novel Soft Switching Two-Stage Heating Power Supply Topolo...

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第35届中国控制会议

作者： GUO Xin REN Hai-Peng LIU Ding SUO Jun PENG Shu-Tao School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Lab.of Complex System Control and Intelligent Information Processing Shaanxi Electric Power Research Institute

ISBN: (纸本)9781509009107

Mono-crystalline silicon is widely applied in the photovoltaic and the integrated circuit *** power supply,as the key element of the mono-crystalline silicon growth furnace,plays an important role in the performance of the whole *** this paper,we propose a new kind of two-stage silicon growth furnace heating power supply topology *** first stage three phase rectifier employs the compound active clamp zero voltage soft switching(CACZVS) three-phase power factor correction(PFC) converter to achieve unity power factor and DC bus voltage regulation,and the second stage DC/DC converter employs phase shifted full bridge zero voltage and zero current soft switching converter(FB-ZVZCS) to regulate the output *** with the heating power supply of non-controlled rectifier type or three-phase power factor correction circuit using hard switching,the proposed two-stage converter structure can achieve high power factor,high efficiency and more flexibility of *** simulation results show the correctness of the analysis.

关键词： Silicon Growth Furnace Heating power Supply CACZVS three phase PFC converter FB-ZVZCS converter

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Hardware-in-loop simulation of real-time cyber-physical system for DC microgrids

Hardware-in-loop simulation of real-time cyber-physical syst...

引用

2020 International Exhibition and Conference for power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2020

作者： Shi, Tianling Ding, Feng Wang, Fei Ge, Zhen Zhang, Lijun Shanghai Key Lab of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Bao’shan District Shanghai China Shanghai Marine Equipment Research Institute Shanghai China

ISBN: (纸本)9783800753888

DC microgrids have the advantages of high efficiency, economy, and safety, which can reliably accommodate distributed renewable energy power generation systems, energy storage devices, and DC loads. In order to improve the test accuracy and authenticity of DC microgrids control, a hardware-in-loop (HIL) simulation platform of real-time cyber-physical system (CPS) for DC microgrids based on RT-lab and labVIEW is established in this paper. HIL simulation and multiple communication methods are adopted to realize real-time data interaction, and further increase the credibility of the entire model. Moreover, real-time host computer system is designed to realize the data monitoring and visual control. Finally, a case study is illustrated to verify the effectiveness of the proposed simulation platform. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Cyber Physical System

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Repeated Strike Process During Disconnector Operation in Ultra-High Voltage Gas-Insulated Switchgear

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Plasma Science and Technology 2016年第3期18卷 247-253页

作者：关永刚蔡元纪陈维江刘卫东李志兵岳功昌张俊民 State Key Lab of Control and Simulation of Power System and Generation Equipments Department of Electrical EngineeringTsinghua UniversityBeijing 100084China State Grid Corporation of China Beijing 100031China China Electric Power Research Institute Beijing 100192China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Very fast transient over-voltage （VFTO）, induced by disconnector operations in gas- insulated switchgears, has become the limiting dielectric stress at ultra-high voltage levels. Much work has been done to investigate single-strike waveforms of VFTO. However, little study has been carried out investigating the repeated strike process, which would influence VFTO significantly. In this paper, we carried out 450 effective experiments in an ultra-high voltage test circuit, and conducted calculations through the Monte Carlo simulation method, to investigate the repeated strike process. Firstly, the mechanism of the repeated strike process is proposed, based on the ex- perimentai results. Afterwards, statistical breakdown characteristics of disconnectors are obtained and analyzed. Finally, simulations of the repeated strike process are conducted, which indicate that the dielectric strength recovery speed and polarity effect factor have a joint effect on VFTO. This study enhances the understanding of the nature of VFTO, and may help to optimize the disconnector designed to minimize VFTO.

关键词： disconnector （DS） repeated strike process discharge statistical breakdowncharacteristics ultra-high voltage （UHV） very fast transient over-voltage （VFTO）

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Construction Pruning for Optimal Control of Process with Deadtime under Extreme High Degree of Control Difficulty 30

Construction Pruning for Optimal Control of Process with Dea...

引用

30th Chinese Control and Decision Conference, CCDC 2018

作者： Yali, Xue Guobo, Xiang Yuqiong, Zhang State Key Lab of Power System Department of Energy and Power Engineering Tsinghua University Beijing100084 China School of Automation Wuhan University of Technology Wuhan430070 China Chinese Electric Power Research Insitute Beijing100192 China

ISBN: (纸本)9781538612439

The control of process with deadtime has always been a challenging performance specification for industry process control, especially when the degree of control difficulty is high. The control of process with deadtime under extreme high degree of control difficulty is seldom touched up to now. This paper explored the load disturbance rejection control and robustness of this kind of process based on the limitation analysis and construction pruning of twice optimum control. The control simulation and analysis on the control of a first order process with deadtime under the degree of control difficulty of 50 shows that the proposed method has stronger ability of disturbance suppression and stronger robustness when the model parameters have uncertainties compared with the twice optimum control method, the PI controller with Smith Predictor and a kind of Oscillation Reduction Controller with Smith Predictor and ESO. The proposed method had the advantages of simple structure, ease of parameter tuning and good performance on the setpoint tracking, load disturbance rejection and strong robustness. © 2018 IEEE.

关键词： Process control Robustness Load modeling Optimal control Analytical models Tuning

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