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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Zhang, Yumin Ji, Xingquan Yu, Yixiao Xu, Bo Han, Xueshan Zhang, Lin Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Energy Research Institute Co. Beijing102209 China

ISBN: (纸本)9781728143033

Integrated energy system is composed of different multiple energy systems. When the combined heat and power (CHP) unit fails, more than one energy systems can be influenced. Therefore, it is very important to improve the reliability of CHP unit. In this paper, we propose a maintenance decision making model for CHP unit based on opportunistic maintenance strategy. Firstly, the expression of the availability of CHP unit considering opportunistic maintenance is derived. And then, in order to quantify the impact of different maintenance strategies on system operation, system operation risk is given taking electrical load loss and thermal load loss into account. Finally, maintenance decision making model of the CHP unit is established with maintenance constraints. Case studies show that the model can optimize maintenance strategies and improve the reliability of CHP unit and the overall system efficiency. © 2020 IEEE.

关键词： Decision making

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Effects of mooring line fracture on 15 MW floating offshore wind turbine under different operation strategies

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engineering Failure Analysis 2025年 179卷

作者： Li, Yan Li, Guoyan Zhu, Qiang Cui, Yiwen Feng, Yiting Su, Ouming Li, Haoran Wang, Bin Meng, Hang State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation Tianjin Key Laboratory of Port and Ocean Engineering School of Civil Engineering Tianjin University Tianjin300350 China Department of Structural Engineering University of California San Diego La JollaCA92093 United States Research Institute of Offshore Energy and Intelligent Construction Tianjin University of Technology Tianjin300384 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of New Energy North China Electric Power University Beijing102206 China

The mooring system of a floating offshore wind turbine (FOWT) may fail under operational conditions, thereby increasing the risk of capsizing and collision within the wind farm. To predict the effects of mooring line fracture, a dynamic model is established for a 15 MW semi-submersible FOWT. This method includes a hydrodynamic model based on potential flow theory, an aerodynamic model with blade element momentum (BEM) theory, and a dynamic slender structure model using finite element theory. Through time domain simulation and wavelet analysis, the motion of the foundation and the tension in the remaining cables after one mooring line is broken are studied. The results indicate that the fractured mooring line will lead to notable changes in response at both low and high frequencies. To mitigate these impacts, the performance of operation strategies such as emergency shutdown and nacelle yaw misalignment is also examined. According to these simulations, active nacelle yaw control is detrimental to the safety of the system, especially for the transverse and yaw motions. On the other hand, shutting down the generator significantly decreases the drift distance and the mooring load. However, it may affect the stability of the system. © 2025 Elsevier Ltd

关键词： Cracks

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Overview of research on modelling and parameter identification of wind power generator 16

Overview of research on modelling and parameter identificati...

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16th IET International Conference on AC and DC power Transmission, ACDC 2020

作者： Zhao, Qing Wu, Linlin Wang, Xiao Sheng, Siqing Feng, Zhenjiang State Grid Jibei Electric Poweyyr Co. Ltd. Research Institute North China Electric Power Research Institute Co. Ltd. Beijing China Grid-Connected Operation Technology Wind-Solar-Storage Hybrid System State Grid Corporation Key Laboratory Beijing China Department of Electrical and Electronic Engineering North China Electric Power University Baoding China

ISBN: (纸本)9781839533914

The calculation accuracy of the new energy power system is affected by the veracity of new energy model, of which control parameters in the wind turbine controller from different manufacturers are not easily obtained. Modelling and parameter identification of wind turbine are investigated in this paper. Firstly, the acquisition approach on the original data for parameter identification is investigated. Secondly, parameter identification methods including classical identification methods and modern identification methods are summarized, in which the application scenarios and limitations are analyzed. Finally, some suggestions on the future research direction of wind turbine parameter identification are put forward. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Wind turbines

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Research on Demand Response Strategy of Integrated Energy system Based on Hybrid Particle Swarm Optimization with Roulette Wheel Operator

Research on Demand Response Strategy of Integrated Energy Sy...

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第33届中国控制与决策会议

作者： Shuying Ren Yan Zhao Tieyan Zhang Yuri Wang Lin Tong School of Elecrtic Power Shenyang Institute of Engineering School of Renewable Energy Shenyang Institute of Engineering Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Province School of Automation and Electrical Engineering Shenyang Ligong University Huludao Power Supply Company State Grid Liaoning Electric Power Supply Co.Ltd.

As one of the core elements of the technology base of the smart energy industry,the comprehensive energy system standard plays a link and catalytic role in promoting China's energy equipment manufacturing,the safe and stable operation of power systems,and the industrialization of scientific and technological *** response can play an important role in the consumption of renewable energy in integrated energy *** paper establishes an objective function to minimize the cost of integrated energy system and optimize user power *** the multiple objective functions and constraints,the traditional single objective optimization model can no longer meet the present problem *** view of the demand response in the integrated energy system,a multi-objective optimization method,the hybrid particle swarm algorithm with roulette operator,is *** algorithm can make the game *** partial optimal solution is spread globally to find the optimal scheduling strategy.

关键词： Integrated energy Demand response Particle swarm optimization Multi-objective optimization and photovoltaic power generation

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A two-stage optimization model for floating offshore wind farm layout and control

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Renewable Energy 2025年 253卷

作者： Tao, Siyu Yang, Jisheng Zheng, Gang He, Ruiyang Feijóo-Lorenzo, Andrés E. College of Automation Engineering Nanjing University of Aeronautics and Astronautics No. 29 Jiangjun Road Nanjing211106 China Department of Building Environment and Energy Engineering Hong Kong Polytechnic University No. 102 Pokfulam Road Pok Fu Lam Hong Kong 999077 China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing100084 China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Monash Biomedical Imaging Monash University Clayton VIC3800 Australia School of Engineering Cardiff University CardiffCF243AA United Kingdom Department of Electrical Engineering University of Vigo Vigo36310 Spain

The effective planning of wind turbine (WT) positions in a wind farm (WF) plays a crucial role in capturing wind energy and increasing power generation. control optimization of WT attitudes can also help reduce wake effects and increase power generation, thereby maximizing the annual electricity production (AEP) of a WF. In this paper, a two-stage optimization model is proposed for planning the stationary layout of floating offshore wind farms (FOWFs), as well as the positions and attitudes of the floating offshore wind turbines (FOWTs) via optimal control. In the first stage, a competitive particle swarm optimizer (CPSO) is employed to generate multiple FOWF layouts. In the second stage, the genetic algorithm (GA) is utilized to optimize the yaw angles and axial induction factors of the FOWTs for operation control. Unlike the existing approaches that address WT layout design and operation control sequentially and separately, the proposed method integrates these aspects to simplify the FOWTs operation and to improve their performances. Additionally, taking the movable characteristics of the FOWTs into consideration, the proposed model incorporates the positional movement of the FOWTs under varying wind conditions, making the power calculations more realistic. Case studies demonstrate that compared with the traditional layout-only optimization, the proposed two-stage optimization model can help increase the AEP of the FOWFs by 4.72 %. © 2025 Elsevier Ltd

关键词： Genetic algorithms

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Comprehensive analysis and design of LLC resonant converter with magnetic control

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CPSS Transactions on power Electronics and Applications 2019年第4期4卷 265-275页

作者： Wei, Yuqi Luo, Quanming Mantooth, Alan The State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing China The Department of Electrical Engineering University of Arkansas Fayetteville United States

Conventionally, LLC resonant converter adopts frequency control (FC) or combine FC with phase shift control (PSC) to regulate the output voltage. However, for both control strategies, a variable switching frequency operation range is required, which makes the magnetic component and driver circuit design complicated. In this paper, the magnetic control (MC) or variable inductor control is adopted for the LLC resonant converter. Thanks to MC, constant switching frequency and duty cycle can be implemented for the primary switches. A comprehensive analysis of the magnetically controlled LLC resonant converter is presented, which includes the operation principle, voltage gain, and soft switching operation. Meanwhile, a design methodology for LLC resonant converter with MC is proposed, especially the design considerations for the variable inductor are discussed. By adopting the proposed design methodology, the zero voltage switching (ZVS) operation for the primary switches and the zero current switching (ZCS) operation for the secondary rectifier can be achieved. Finally, a 200 W experimental setup is built to validate the theoretical analysis. © CPSS Transactions on power Electronics and Applications 2019. All rights reserved.

关键词： Zero current switching

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Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach

arXiv

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arXiv 2024年

作者： Zheng, Jiakang Zhang, Jiayi Du, Hongyang Zhang, Ruichen Niyato, Dusit Dobre, Octavia A. Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The College of Computing and Data Science Nanyang Technological University Singapore Faculty of Engineering and Applied Science Memorial University Canada The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free (CF) massive multiple-input multiple-output (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Rate-splitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses of both approaches. Considering imperfect channel state information (CSI) resulting from both pilot contamination and noise, we derive a closed-form expression for the sum spectral efficiency (SE) of the RS-based CF massive MIMO system under a spatially correlated Rician channel. Moreover, we propose low-complexity heuristic algorithms based on statistical CSI for power-splitting of common messages and power-control of private messages, and genetic algorithm is adopted as a solution for upper bound performance. Furthermore, we formulate a joint optimization problem, aiming to maximize the sum SE of the RS-based CF massive MIMO system by optimizing the power-splitting factor and power-control coefficient. Importantly, we improve a generative AI (GAI) algorithm to address this complex and non-convexity problem by using a diffusion model to obtain solutions. Simulation results demonstrate its effectiveness and practicality in mitigating interference, especially in dynamic environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Redesigning electrification of China’s ammonia and methanol industry to balance decarbonization with power system security

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Nature Energy 2025年 1-12页

作者： Li, Jiarong Lin, Jin Wang, Jianxiao Lu, Xi Nielsen, Chris P. McElroy, Michael B. Song, Yonghua Song, Jie Lyu, Xuefeng Yu, Mingkai Wu, Sirui Yu, Zhipeng Department of Electrical Engineering Tsinghua University Beijing China Harvard-China Project on Energy Economy and Environment Harvard University Cambridge MA United States State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China State Key Laboratory of Regional Environment and Sustainability School of Environment Tsinghua University Beijing China Institute for Carbon Neutrality Tsinghua University Beijing China State Key Laboratory of Internet of Things for Smart City University of Macau Macao Department of Industrial Engineering and Management College of Engineering Peking University Beijing China School of Nuclear Science and Engineering North China Electric Power University Beijing China China Electric Power Research Institute Beijing China

Electrification represents a critical pathway to decarbonize the ammonia and methanol industries by reducing fossil fuel reliance. However, a greater understanding is needed of how the spatio-temporal mismatch between renewable generation and chemical load patterns may impact on power system emissions and security. Here we assess different electrification pathways across 22 Chinese provinces from 2020 to 2050. Using 2020 data, we show that reliance on grid electricity offsets CO2 reductions by increasing power system emissions, raising national emissions by 1%. Integrating co-located renewables without self-balancing flexibility exacerbates power system security risks, potentially increasing balancing requirements by 9%. To address this challenge, we propose the ‘Green Flexible Chemical Electrification’ pathway, transitioning from requirements for stringent co-located renewables to rigid temporal self flexibility. By 2030, Green Flexible Chemical Electrification demonstrates cost competitiveness nationwide, with green ammonia potentially generating 2 billion RMB in profit. Additionally, redesigning electricity pricing to incentivize chemical-side demand management further enhances power–chemical synergies. © The Author(s), under exclusive licence to Springer Nature Limited 2025.

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Distributionally robust electricity-carbon collaborative scheduling of integrated energy systems based on refined joint model of heating networks and buildings

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Renewable Energy 2025年 251卷

作者： Chen, Haipeng Song, Jianzhao Li, Zhiwei Shui, Siyuan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China Department of Electrical Engineering Northeast Electric Power University Jilin 132012 China School of Automation and Engineering Northeast Electric Power University Jilin 132012 China Northeast Electric Power University Jilin 132012 China

The rapid increase in the grid integration demand of intermittent renewable energy (RE) has raised higher requirements for the flexible regulation and energy storage capacity of integrated energy systems (IES) with combined heat and power (CHP) units. To solve the issues of efficient accommodation of high proportion RE and low-carbon economic operation of the system, this study proposes an optimal scheduling method for IES based on a refined joint model of heating networks and buildings. Firstly, a refined thermal energy transmission model integrating heating networks and buildings is established to accurately depict the dynamic thermal energy transmission process within the system. Then, this paper proposes an electricity - carbon demand response considering the dynamic carbon emission factor, guiding users to use electricity in a low-carbon way. A distributionally robust optimization (DRO) scheduling model is established to quantify the impact of RE output uncertainty, which is efficiently solved using the column and constraint generation algorithm. The simulation results show that the proposed DRO model ensures the robustness of system operation while improving low-carbon economic benefits. Notably, the RE consumption rate is increased by 9.52 % compared with traditional scheduling methods, which provides an essential reference for promoting the sustainable development of IES. © 2025

关键词： Thermal energy

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Pmu-Based Real-Time Distribution system state Estimation Considering Anomaly Detection, Discrimination and Identification

SSRN

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SSRN 2022年

作者： Popov, Marjan Veerakumar, Nidarshan Ćetenović, Dragan Kongurai, Krit Jongepier, Arjen Terzija, Vladimir Delft University of Technology Faculty of EEMCS Mekelweg 4 Delft2628CD Netherlands The Department of Electrical & Electronic Engineering The University of Manchester Manchester United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Svetog Save 65 Čačak32000 Serbia Stedin B.V. Netherlands Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

In this paper, a real-time state estimation platform for distribution grids monitored by Phasor Measurement Units (PMUs) is developed, tested, and validated using Real TimeDigital Simulator (RTDS). The developed platform serves as a proof-of-concept for potential implementation in an existing 50 kV ring network of the Dutch distribution utility Stedin medium voltage distribution grid located in the southwest (Zeeland area) of the Netherlands. To catch up with the fast sampling rates of PMUs, the platform incorporates computationally efficient techniques for state estimation and detection, discrimination and identification of anomalies like bad data and sudden load changes. Forecasting Aided state Estimation has been utilized to enable measurement innovations needed for fast anomaly detection, discrimination, and identification, whilst the Extended Kalman Filter (EKF) algorithm is selected to provide fast state forecasting and filtering. The platform has been tested under various normal and abnormal operating conditions considering different statistical properties of measurement noise as well as different bad data and sudden load change scenarios. To demonstrate advantages and disadvantages for embedding EKF into the platform, EKF is compared with Unscented Kalman Filter (UKF) in terms of estimation accuracy, computation efficiency, and compatibility with the module for anomaly detection, discrimination, and identification. The results of extensive simulations provide good hints about the feasibility of PMU-based real-time state estimation for the Stedin distribution grid. © 2022, The Authors. All rights reserved.

关键词： state estimation

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