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Model Predictive control for systems with Limited State Variables

Russian Electrical engineering 2023年第2期94卷 77-83页

作者： Bogdanov, A.N. Anuchin, A.S. Demidova, G.L. Department of Electric Drive Moscow Power Engineering Institute Moscow111250 Russia Faculty of Control System and Robotics ITMO University St. Petersburg197101 Russia

Abstract: Model predictive control are actively used in industry in high-power electric drives, in which it is permissible to use expensive programmable logic matrices that provide calculations with a prediction horizon of up to ten epochs and a forecast tree of several million variants. However, the computing power of microcontrollers is not enough to implement such systems in a low-power electric drive. The development of microcontrollers is following the path of increasing not only computing power, but also memory, which makes it possible to implement model predictive control systems in practice using lookup table methods for calculating control actions for all combinations of state variables and control actions. The paper shows the possibility of designing control with prediction for two types of electric drives—a DC electric drive and a switched reluctance electric drive—as objects with a small number of state variables, which allows one to fit the precalculated lookup tables of control actions in the memory of the microcontroller. Studies on mathematical models have shown that model predictive control with a finite control set and a single prediction horizon has disadvantages due to variable switching frequency, and control with a continuous control set implemented by the lookup table method allows one to perform control calculations immediately before the start of the next pulse width modulation period, reducing the algorithm execution time by hundreds of times. © 2023, Allerton Press, Inc.

关键词： Forecasting

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Mechanism of contact electrification-induced microscale breakdown between separating electrodes

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Physical Review Applied 2025年第5期23卷 054059-054059页

作者： Jiandong Chen Yangyang Fu Department of Electrical Engineering Tsinghua University Beijing 100084 China State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing 100084 China Sichuan Energy Internet Research Institute Tsinghua University Sichuan 610213 China

Since the 1990s, there has been a debate on whether the contact electrification (CE)-induced discharge mode is continuous or intermittent, and the understanding of the relationship between the electrode potential and Paschen’s curve remains controversial. In the present work, we demonstrate CE-induced microscale breakdown between two separating metal electrodes without an external voltage source and successfully reveal that continuous and intermittent discharge modes can both be realized by adjusting the electrode separation velocity. The CE-induced initial charge, electrode separation velocity, and breakdown time delay are identified as key factors, and their combined effects explicitly determine the breakdown mode. Further, it is found that in continuous breakdown mode with a sufficiently high initial charge, the electrode potential versus gap distance exactly follows the modified Paschen’s curve, which incorporates the field emission regime. This discovery suggests that a microscale breakdown curve can be determined based on a single characterization of the separating electrode potential without the need to perform redundant repeated experiments. The results of this study elucidate microscale breakdown physics with moving electrodes and inform better control and optimization of microelectromechanical devices for applications including energy harvesters, microsensors, and detectors.

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Dynamic Modeling of Key Operating Parameters for Supercritical Circulating Fluidized Bed Units based on Data-Knowledge-Driven Method

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Journal of Thermal Science 2024年第3期33卷 1216-1230页

作者： YU Haoyang GAO Mingming ZHANG Hongfu CHEN Jiyu LIU Jizhen YUE Guangxi The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing102206China CHN Energy New Energy Technology Research Institute Co. Ltd.Beijing102209China Department of Energy and Power Engineering Tsinghua UniversityBeijing100084China

To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)***,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been ***,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB *** model parameters are determined based on the operating data of the unit and continuously optimized in real ***,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam ***,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB *** model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.

关键词： circulating fluidized bed dynamic model data-knowledge-driven method deep learning power plant

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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

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Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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Numerical optimization and performance study of a photovoltaic/thermal module based on multi-stage V-type turbulators

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Renewable Energy 2025年 252卷

作者： Yong Zhang Yang Zhao Heng Zhang Chao Cheng Dan Gao Haiping Chen Jizhen Liu State Key Laboratory of New Energy Power System North China Electric Power University Beijing 102206 China School of Energy Power and Mechanical Engineering North China Electric Power University Beijing 102206 China Beijing Key Laboratory of Pollutant Monitoring and Control in Thermoelectric Production Process North China Electric Power University Beijing 102206 China National Institute of Energy Development Strategy North China Electric Power University Beijing 102206 China

The utilization of solar energy is one of the important ways to ensure low-carbon energy transformation, and PV/T technology, as an efficient technology for utilizing solar energy, has received widespread attention in recent years. This paper proposes a photovoltaic/thermal (PV/T) module based on a multi-stage V-type turbulator, and explores the optimization design of the system through numerical simulation and experimental research. To improve thermal and electrical efficiency, the paper integrates a turbulence-enhancing V-type turbulator design and utilizes a Computational Fluid Dynamics (CFD) model for detailed system analysis. Experimental results show that the optimized PV/T system achieves a 9 %–12 % increase in electrical efficiency compared to conventional PV systems under standard solar irradiance conditions, with overall system efficiency exceeding 65 %. Through optimization using the Response Surface Methodology (RSM), the optimal turbulator design parameters were determined to be an angle α of 60°, an inclination angle β of 61.1°and a distance D of 0 mm. This article also compared three conventional channels to verify the heat transfer performance of the multi-stage V-shaped vortex generator PV/T.

关键词： Heat transfer performance

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International Collaboration in Synchronized Measurement Experiment in Russia

International Collaboration in Synchronized Measurement Expe...

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power systems Conference on Advanced Metering, Protection, control, Communication and Distributed Resources

作者： Grobovoy, Andrey Bondareva, Natalia Stepanov, Vladimir Atienza, Edsel Power System Emergency Control Laboratory Ltd Siberian Electric Power Research Institute Russian Federation ABB Automation Schweitzer Engineering Laboratories Inc. United States

ISBN: (纸本)9781424408542

The paper discusses the results of the synchronized measurement experiment recently conducted in the Russian Far East Interconnected power system. An international team of experts conducted a set of unique tests in the bulk power system. The tests used five devices for synchronized phasor measurement. In conjunction with digital fault recorders (DFRs), the phasor measurement units (PMUs) were able to demonstrate the feasibility of using PMUs to monitor and control the Russian Far East Interconnected power system.

关键词： Phasor measurement units

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A novel two-stage Dissolved Gas Analysis fault diagnosis system based semi-supervised learning

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High Voltage 2022年第4期7卷 676-691页

作者： Xuemin Tan Chao Guo Ke Wang Fu Wan College of Control Engineering Chengdu University of Information TechnologyChengduChina State Grid Chengdu Power Supply Company ChengduChina China Electric Power Research Institute BeijingChina State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina

Dissolved Gas Analysis(DGA)is an important method for oil-immersed transformer fault ***,collecting labelled DGA data is difficult because the determi-nation of the transformer fault is time-consuming and expensive in the transformer substation,but DGA data without labels is easier to ***,the paper pro-posed a semi-supervised two-stage diagnostic system based DGA by using less labelled *** two-stage system includes a novel semi-supervised feature selection based Genetic Algorithm(GA)and Support Vector Machine(SVM)model(SSL-FS-GASVM)for selecting optimal features and a novel semi-supervised transformer fault diagnosis model based improved Artificial Fish Swarm Algorithm(AFSA)and SVM(SSL-IAFSA-SVM)for optimising the SVM ***,the performances of SSL-FS-GASVM and SSL-IAFSA-SVM models are tested and compared with traditional supervised diagnostic models combined with other optimisation methods,*** results show that the proposed two-stage system works in optimising features and parameters and has strong robustness in solving small sample classification problems.

关键词： fault diagnosis system

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Correction of Time-varying PMU Phase Angle Deviation with Unknown Transmission Line Parameters

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CSEE Journal of power and Energy systems 2023年第1期9卷 315-325页

作者： Ancheng Xue He Kong Feiyang Xu Junbo Zhao Naichao Chang Joe H.Chow Haiyan Hong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ConnecticutStorrs06268USA National Electric Power Dispatching and Control Center Beijing 100031China Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Phasor measurement units(PMUs)provide useful data for real-time monitoring of the smart ***,there may be time-varying deviation in phase angle differences(PADs)between both ends of the transmission line(TL),which may deteriorate application performance based on *** address that,this paper proposes two robust methods of correcting time-varying PAD deviation with unknown parameters of TL(ParTL).First,the phenomena of time-varying PAD deviation observed from field PMU data are *** general formulations for PAD estimation are then *** simplify the formulations,estimation of PADs is converted into the optimal problem with a single ParTL as the variable,yielding a linear estimation of *** latter is used by second-order Taylor series expansion to estimate PADs *** reduce the impact of possible abnormal amplitude data in field data,the IGG(institute of Geodesy&Geophysics,Chinese Academy of Sciences)weighting function is *** using both simulated and field data verify the effectiveness and robustness of the proposed methods.

关键词： Correction line parameters parameter identification phasor measurement time-varying phase angle difference deviation

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Multi-task learning and single-task learning joint multi-energy load forecasting of integrated energy systems considering meteorological variations

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Expert systems with Applications 2025年 288卷

作者： Nantian Huang Shicheng Ren Jianfei Liu Guowei Cai Liang Zhang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 Jilin Province China School of Electrical Engineering Northeast Electric Power University Jilin 132012 Jilin Province China The Economic and Technical Research Institute of State Grid Inner Mongolia Eastern Electric Power Company Hohhot 010010 Inner Mongolia Province China

Accurate multi-energy load forecasting is pivotal for achieving supply–demand balance and enabling economic dispatch in Integrated energy systems (IES). However, prediction accuracy is significantly compromised by meteorological fluctuations, seasonal coupling variations, and multi-energy interactions affecting multi-energy loads. This study proposes a joint multi-energy load forecasting framework integrating meteorological variation rate features with multi task learning (MTL) and single task learning (STL). First, historical load variation rates and meteorological variation rates are calculated, with rapid maximal information coefficient (RapidMIC) employed to identify dominant meteorological variation rates influencing multi-load fluctuations. Subsequently, a weighted average of correlation analysis method quantifies both linear and nonlinear impacts of meteorological variation rates on load fluctuations, enabling precise screening of critical meteorological input features. Second, addressing potential accuracy degradation in MTL models caused by coupling strength disparities among multi-energy loads, a joint forecasting method based on MTL-STL is proposed to enhance prediction precision. Furthermore, a loss function optimization strategy combining homoscedastic uncertainty (HU) and dynamic weight averaging (DWA) achieves real-time weight allocation in MTL. Finally, validation through case studies on IES at Arizona State University (ASU) and an industrial park in Gansu Province, China demonstrates the model’s effectiveness and generalizability: Across all seasons, MAPE values for electricity, cool, and heating loads remain stable within 1.068%-3.022%, 1.877%-5.331%, and 1.697%-3.999% respectively.

关键词： Multi-task learning

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Inter-Provincial Transaction Model in Two-Level ElectricityMarket Considering Carbon Emission and Consumption Responsibility Weights

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Energy engineering 2023年第10期120卷 2393-2416页

作者： Chunlei Jiao HongyanHao Ming Li Rifucairen Fu Yichun Liu Shunfu Lin Ronghui Liu Electric New Power System Technology Research Institute The Electric Power Research Institute of State Grid Xinjiang Electric Power Co.Ltd.Urumqi830000China Power Dispatch Control Center State Grid Xinjiang Electric Power Co.Ltd.Urumqi830063China College of Electrical Engineering Shanghai University of Electric PowerShanghai200090China

In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading,how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key *** combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market,complete the intra-provincial consumption responsibility weight index,and consume renewable energy across provinces and *** paper combines power generation and consumption within the province,uses inter-provincial renewable energy trading tomeet the load demand within the province and completes the index of intra-provincial consumption responsibility *** intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the *** the two-level electricity market operation framework,the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility,while the lower-level model aims to minimize the inter-provincial renewable energy purchasing ***,the influence of inter-provincial transaction mechanism,risk aversion coefficient,voucher price,and responsibility weight on operating cost is *** is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index,and promote the consumption of renewable energy.

关键词： Consumption responsibility weights electricity market carbon emission transactions between provinces

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