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6th International Conference on HVDC, HVDC 2024

作者： Yang, Renxin Cai, Haiqing Su, Mingzhang Gu, Haohan Chen, Zhihao Cai, Xu Shanghai Jiao Tong University Key Laboratory of Control of Power Transmission and Conversion Shanghai China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guangzhou China National Energy Power Grid Technology R&d Centre China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350387759

Using modular multilevel converter-based multi-terminal high voltage direct current (MMC-MTDC) transmission to integrate large-scale renewable power into the main power grid is an important development trend in China. To cope with the stability issues under weak grid conditions, different grid-forming control strategies have been proposed for the MMC in MTDC transmission systems. These control strategies have different structures due to different control targets and are difficult to unify. To solve this problem, a novel grid-forming control structure is proposed in this paper. The MMC emulates the synchronous generator (SG), and the submodule capacitor voltage emulates the SG rotor speed. On this basis, by utilizing the modulation control degree freedom, a unified DC-side controller is proposed to realize different control targets. Finally, the simulation model of a 4-terminal MMC-MTDC transmission system with renewable power integration is established in the PSCAD/EMTDC. The effectiveness of the proposed strategy is verified by the simulation results. © 2024 IEEE.

关键词： grid-forming MMC-MTDC multi-targets control unified control structure

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Spatio-temporal Granularity Co-optimization Based Monthly Electricity Consumption Forecasting

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CSEE Journal of power and Energy systems 2023年第5期9卷 1980-1984页

作者： Kangping Li Yuqing Wang Ning Zhang Fei Wang Chunyi Huang the College of Smart Energy Shanghai Jiao Tong UniversityShanghai 200240China the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China the Department of Electrical Engineering North China Electric Power UniversityBaoding 071003China the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University) Beijing 102206China the Hebei Key Laboratory of Distributed Energy Storage and Microgrid(North China Electric Power University) Baoding 071003China the Key Laboratory of Control of Power Transmission and Conversion Ministry of Education(Shanghai Jiao Tong University)Shanghai 200240China

Monthly electricity consumption forecasting(ECF)plays an important role in power system operation and electricity market *** popularity of smart meters enables collection of fine-grained load data,which provides an opportunity for improvement of monthly ECF *** this letter,a spatio-temporal granularity co-optimization-based monthly ECF framework is proposed,which aims to find an optimal combination of temporal granularity and spatial clusters to improve monthly ECF *** framework is formulated as a nested bi-layer optimization problem.A grid search method combined with a greedy clustering method is proposed to solve the optimization *** of the proposed method has been verified on a real smart meter dataset.

关键词： Electricity consumption forecasting Greedy clustering Grid searching Spatiotemporal

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A Novel Energy-Type SVG with Grid Forming control for Grid Voltage and Inertial Support 14

A Novel Energy-Type SVG with Grid Forming Control for Grid V...

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14th IEEE International Symposium on power Electronics for Distributed Generation systems, PEDG 2023

作者： Zhang, Jiawei Zhang, Chen Shi, Xianqiang Huang, Lei Li, Xiaobing Cai, Xu Shanghai Jiao Tong Unviersity Key Laboratory of Control of Power Transmission and Conversion Shanghai China Sieyuan Electric Co. Ltd Power System Analysis Department Shanghai China R&d Center Sieyuan Electric Co. Ltd Shanghai China

ISBN: (纸本)9798350328233

Large scale renewable power plants (e.g., wind farms) are typically equipped with the cascaded H-bridge based Static Var Generator (SVG) for voltage regulation of the Point of Common Coupling (PCC). To enhance its capability in gridfriendly integration and operation of renewable power plants, this paper proposed an energy-type Static-var-generator (ESVG) with grid forming (GFM) control characteristics. First, the energy type SVG's converter typology is presented, then a new type of grid forming control utilizing the distributed energy of SVG's dc capacitor is proposed, having two main characteristics: 1) it achieves autonomous frequency response and grid voltage support similar to the majority of GFM controls;2) it has the self dc-voltage balancing capability, which does not require additional energy management control. The state-space model is also built to assess the small-signal stability of the ESVG system. Finally, an electromagnetic transient (EMT) simulation model of a typical grid-tied ESVG system is constructed in Matlab/Simulink, and simulation results show that the proposed control methods and associated characteristics are valid. © 2023 IEEE.

关键词： Frequency response

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Wet flue gas desulfurization performance of 330 MW coal-fired power unit based on computational fluid dynamics region identification of flow pattern and transfer process

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Chinese Journal of Chemical Engineering 2021年第1期34卷 13-26页

作者： Jiangyuan Qu Nana Qi Kai Zhang Lifeng Li PengchengWang Beijing Key Laboratory of Emission Surveillance and Control for Thermal Power Generation North China Electric Power UniversityBeijing 102206China Key Laboratory of Power Station Energy Transfer Conversion and System(North China Electric Power University) Ministry of EducationBeijing 102206China Shanxi Hepo Power Generation Company Limited Yangquan 045011China

Wet Flue Gas Desulfurization(WFGD)unit based upon spray scrubber has beenwidely employed to control SO_(2) emissions from flue gas in coal-fired power *** clarify the dependence of desulfurization performance on inter-phase transfer behaviors with non-ideal contacting patterns of flue gas and slurry droplets,three regions in spray scrubber are distinguished in terms of gas-slurry flow structures using CFD method in the Eulerian-Lagrangian framework.A comprehensive model is established by involving the transfer process between two phases and chemical reactions in aqueous phase,which is validatedwith the measured data froma WFGD scrubber of 330 MW coal-fired power *** results show that the overall uniformity degree of flue gas in whole scrubber is largely determined by the force-balanced droplets in the middle part of scrubber,which is dominated by counter-current *** momentum transfer behavior and SO_(2) chemical absorption process present the synchronicity with the evolution of gas-slurry flow pattern,whilst the heat transfer together with H_(2)O evaporation has little effect on overall absorption *** regions are firstly defined as Gas Inlet Region(GIR),Dominant Absorption Region(DAR)and Slurry Dispersed Region(SDR)from the bottom to top of ***_(2) is mainly scrubbed in DAR,which provides much more intensive interaction between two phases compared to GIR or SDR.A better understanding of the desulfurization process is obtained from the fundamental relationship between transport phenomena and chemical reactions based upon the complicated hydrodynamics of gas-slurry two-phase flow,which should be useful for designing and optimizing the scrubber in coal-fired power unit.

关键词： Wet flue gas desulfurization Gas-liquid flow Eulerian-Lagrangian model Flow pattern Transport processes Absorption

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An Elliptical Tangent Graph Method Based on Multi-source Information for UAV Path Planning 3rd

An Elliptical Tangent Graph Method Based on Multi-source Inf...

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Liu, Bin Tang, Qirong Huang, Wentao Jiang, Qingchao Fan, Qinqin Logistics Research Center Shanghai Maritime University Shanghai201306 China Laboratory of Robotics and Multibody System Tongji University Shanghai201804 China Key Laboratory of Control of Power Transmission and Conversion Ministry of Education of China Shanghai200240 China Key Laboratory of Smart Manufacturing in Energy Chemical Ministry of Education East China University of Science and Technology Shanghai200237 China

ISBN: (纸本)9789819711062

Path planning is one of important tasks for unmanned aerial vehicles (UAVs) to achieve autonomous flight. Moreover, the solution efficiency and solution accuracy are usually two conflicting objectives in UAV path planning problem, especially for complex static environments. To alleviate the above issue, an elliptical tangent graph method based on multi-source information (ETG-MI) is proposed in the current study. In the proposed ETG-MI algorithm, the target guidance information is first used to generate candidate waypoints via elliptical tangent graph method, and then a novel heuristic rule is utilized to select promising waypoints. Additionally, a waypoint selection method is proposed to eliminate low-quality detour waypoints. Finally, the cubic B-spline curve method is used to smooth the final obtained path for meeting the actual flight requirements of UAV. The proposed algorithm is compared with four state-of-the-art path planning methods under different scenarios. The experimental results demonstrate that the proposed ETG-MI is capable of finding an optimal feasible path for different environments with various types of obstacles. Moreover, the proposed algorithm performs better than other competitors in simple maze-like environments. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Motion planning

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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

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Energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun Ram Machlev Qianchao Wang Juri Belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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Synergistic Optimization of power & Capacity Configuration Considering control Strategy for Flywheel Energy Storage Participating in Primary Frequency Regulation

SSRN

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SSRN 2024年

作者： Liang, Lu Hong, Feng Ji, Weiming Jiang, Hui Hao, Junhong Fang, Fang Liu, Jizhen The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Key Laboratory of Power Station Energy Transfer Conversion and System Ministry of Education School of Energy Power China

The intermittent and stochastic nature of renewable energy sources poses stern challenges to the frequency stability of new power system. The flywheel energy storage system (FESS), with its rapid response and high power density, plays a pivotal role in mitigating frequency fluctuations. To improve the performance of the FESS assisting thermal power unit (TPU), a collaborative optimization methodology of the capacity configuration and control strategy for FESS is presented in this paper. Aiming to enhance the primary frequency control (PFC) performance and reduce the life-cycle cost of the FESS, this paper established a capacity configuration model based on a dynamic adaptive control strategy, in which FESS compensates for the lack of TPU frequency regulation capability and recovery SOC actively. A case study demonstrated that the optimization model proposed is suitable for different frequency scenarios. It has been verified that the control strategy which is based on the SOC of FESS and frequency regulation capability of the TPU is economically more attractive compared to traditional strategies. In addition, this study revealed that a FESS with a charge/discharge rate of 7.5 C and rated power of 7.6 MW was appropriate for assisting a 600MW TPU in PFC by the optimal capacity configuration and control strategy. © 2024, The Authors. All rights reserved.

关键词： Wheels

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Unified Grid-Forming control for MMC-MTDC systems with Renewable power Integration

Unified Grid-Forming Control for MMC-MTDC Systems with Renew...

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HVDC (HVDC), International Conference on

作者： Renxin Yang Haiqing Cai Mingzhang Su Haohan Gu Zhihao Chen Xu Cai Key Laboratory of Control of Power Transmission and Conversion Shanghai Jiao Tong University Shanghai China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China Southern Power Grid Guangzhou China

ISBN: (数字)9798350387759

ISBN: (纸本)9798350387766

关键词： Renewable energy sources Simulation HVDC transmission Capacitors Rotors Switches control systems Synchronous generators Stability analysis Grid forming

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Synergistic Optimization of power & Capacity Configuration Considering control Strategy for Flywheel Energy Storage Participating in Primary Frequency Regulation

SSRN

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SSRN 2024年

关键词： Wheels

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Intelligent Built-in Test Design of controller Module by Improved Biologically Inspired Neural Network 10

Intelligent Built-in Test Design of Controller Module by Imp...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Xie, Zhenmeng Hou, Guolian Zhang, Jianhua Huang, Congzhi School of Control and Computer Engineering North China Electric Power University Beijing102206 China Key Laboratory of Power Station Energy Transfer Conversion and System North China Electric Power University Beijing China

ISBN: (纸本)9781665424233

Built-in test (BIT) technology is widely employed in heavy-duty gas turbine control systems for fault recognition. However, it is difficult to obtain an excellent fault diagnostic ability by using the conventional BIT technology, and the false alarm rate is high. In this paper, a design of intelligent BIT based on improved biologically inspired neural network (BINN) is proposed to reduce false alarm. Firstly, massive historical measurement data of controller module is collected and used as training dataset and test dataset. Secondly, intelligent BIT based on improved BINN is designed to deal with the issue of module state identification and reduce false alarm rate. Finally, the effectiveness of proposed approach is validated by the given extensive numerical simulation results and experimental results. © 2021 IEEE.

关键词： Statistical tests

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