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IEEE Transactions on Intelligent Vehicles 2024年 1-18页

作者： Yang, Dongsheng Yu, Lei Zhang, Yi Zhu, Fenghua Li, Qiang Cui, Huachao Ma, Qiongmin Fan, Lili Tian, Yonglin Jinan University Guangzhou China Intelligent Science & Technology Academy Limited of CASIC Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 28th Research Institute of China Electronics Technology Group Corporation Nanjing China National Key Laboratory for Complex Systems Simulation National University of Defense Technology Changsha China School of Information and Electronics Beijing Institute of Technology Beijing China

A C2 computing framework for unmanned systems to perform complex tasks is proposed using methods of system of systems engineering, which is formed by combining the macro-scale command and control (C2) process mechanism model (PREA loop) and micro-scale C2 process mechanism model (OODA loop). Guided by PREA loop and OODA loop, the computing framework is divided into four steps and three kinds of transformations. The four steps are design, construction, operation monitoring, and assessment. The three transformations are tactical feedback, campaign feedback, and strategic feedback. A C2 organization model of joint landing combat force is established against the background of a typical complex task of joint landing operation, and the C2 computing framework based on the PREA &OODA is used to implement the C2 activities of the joint landing combat force. The influence of the computing framework on the performance of unmanned systems under different task conditions is verified, including task coordination load, task efficiency and sensitivity of unmanned systems response. Authors

关键词： Feedback

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Condition Monitoring for Wind Turbine Pitch System Using Multi-parameter Health Indicator

Condition Monitoring for Wind Turbine Pitch System Using Mul...

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International Conference on power System Technology (powerCON)

作者： Cong Yang Zheng Qian Yan Pei School of Instrumentation Science and Opto-electronics Engineering Beihang University Beijing China State Key Laboratory of Operation and Control of Renewable Energy& Storage Systems China Electric Power Research Institute Beijing China

ISBN: (纸本)9781538664629;9781538664612

As one of the critical components of wind turbines, pitch system suffers the highest failure rate and downtime. Thus, it is particularly important to improve the reliability and reduce the operation and maintenance (O&M) costs of pitch system. With the development of condition monitoring (CM) technology, the condition based maintenance is often employed to reduce the O&M costs of wind turbines. This paper proposed a data-driven CM approach to identify the abnormal condition of pitch system, using supervisory control and data acquisition (SCADA) data. The result of the proposed approach could be useful for wind farm operators to improve their maintenance strategy. Firstly, the Relief algorithm is used to select the appropriated parameters as the health indicator for evaluating the condition of pitch system. Meanwhile, the correlation between the selected parameters is considered to remove the redundant variables. With the selected parameters as the model output and environment variables as the model input, then the random forest regression based model is established by only using the historical healthy SCADA data. Eventually, the distance calculated based on the residual errors between model output and monitored value is used to identify the abnormal condition of pitch system specifically. Several case studies have been analyzed to validate the feasibility of the proposed method. The results indicate that the proposed method can detect the pitch system faults earlier than the SCADA alarm system. It is applicable for the on-line CM of pitch system because of simplicity and low cost.

关键词： Wind turbines Data models Blades Monitoring Maintenance engineering Generators Temperature sensors

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Unit Commitment Considering Demand Response Behavior Based on Utility Maximization

Unit Commitment Considering Demand Response Behavior Based o...

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IEEE Conference on Energy Internet and Energy System Integration

作者： Yumin Zhang Xueshan Han Bo Xu Li Zhang Donglei Sun Xiaofeng Miao Jiayin Jiang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Economic & Technology Research Institute of State Grid Shandong Electric Power Company State Grid Shandong Electric Power Company Yantai Electric Power Company

ISBN: (纸本)9781538614280

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method.

关键词： Demand utility Decomposition coordination Electricity market Lagrangian relaxation Real-time pricing Unit commitment

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A Non-Intrusive Appliances Load Monitoring Method Based on Hourly Smart Meter Data

A Non-Intrusive Appliances Load Monitoring Method Based on H...

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作者： Chunhe Song Zhongfeng Wang Shuji Liu Libo Xu Dapeng Zhou Peng Zeng Key Laboratory of Networked Control Systems Shenyang Institute of automationChinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Grid Liaoning Electric Power Co. Ltd.

Peak load management is very important for the electric power *** paper analyzes the impact of residential swimming pool pumps(RSPPs) on the peak *** this paper analyzes the challenges of non-intrusive energy consumption estimation for ***,a novel reference based change-point(RCP) model is proposed for non-intrusive SPPs energy consumption *** advantages of the proposed RCP model are that it does not require high sampling rate data or prior information of the *** show that during pool season,under the assumption that the ratio of base loads(defined as the power consumption which is independent of the outdoor temperature) of houses with and with PPs remains the same during no pool season and pool season,6.3%of the total energy is consumed by PPs,while under the assumption that for houses with and without PPs,the ratio of base loads is equal to the ratio of the temperature-dependent power consumption during pool season,9.08% of the total energy is consumed by ***,we show that by shifting PPs activity period,under the first assumption,at least 1.27% of peak demand can be reduced,while under the second assumption,at least 4.53% of peak demand can be reduced.

关键词： Smart grid Non-intrusive Appliances Load Monitoring Peak Load

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A Comprehensive Study on Impedance Models of Grid-Tied Voltage-Source Converters

A Comprehensive Study on Impedance Models of Grid-Tied Volta...

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Annual Conference of Industrial Electronics Society

作者： Tao Xue Jing Lyu Yan Li Han Wang Xu Cai State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric power Research Institute Beijing China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

Recently, the impedance-based method is regarded as a desirable way to analyze the interactive stability between power converters and grids. However, most of the modeling processes only consider parts of control strategies and lack in the analysis of impact of control bandwidths. To fill this gap, this paper derives a thorough and explicit impedance modeling process of grid-tied voltage source converters (VSCs) by considering inner- and outer-loop controls, phase-locked loop (PLL) as well as different control strategies, which has been validated by frequency scanning method. Furthermore, the impacts of control strategies and bandwidths on the impedance characteristics are investigated. Different q-axis outer-loop controls play more significant role in shaping impedances than different d-axis outer-loop controls. Besides, changes in inductive and capacitive characteristics of VSC impedances are clarified when bandwidths of different control loops are changed. Time domain simulation indicates the effectiveness and correctness of the analysis.

关键词： Impedance Mathematical model Phase locked loops power system dynamics Voltage control Analytical models power system stability

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power Load Forecasting Based on COA-Bi-LSTM Method

Power Load Forecasting Based on COA-Bi-LSTM Method

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Electrical Engineering and control Science (IC2ECS), International Conference on

作者： Gang Chen Dian Zhang Wei Xiang Zhenqi Guan Jing Huang Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Nanan District Chongqing China Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing China

A power load forecasting method based on Coyote optimization Algorithm-Bidirectional Long short-term Memory Neural Network (COA-Bi-LSTM) model was proposed in this study to solve the problem of inaccurate power load prediction. Aiming at the problem of artificial selection of neural network hyperparameters leading to inaccurate prediction, COA was used to iteratively optimize the three hyperparameters of Bi-LSTM: learning rate, iteration times and number of hidden units. Two groups of historical load data with different characteristics in January and August 2018 were selected and compared with the proposed method using BP neural network, LSTM and Bi-LSTM, respectively. The simulation results show that the optimized prediction effect is better. The Mean Absolute Percentage Error (MAPE) in the data prediction results in January is reduced by 45.46%, 28.57%, and 24.05% respectively. Meanwhile, the MAPE in the data prediction results in August are respectively reduced by 73.71%, 44.04%, 17.57%, verifying the effectiveness of the method.

关键词： Training Load forecasting simulation Time series analysis Learning (artificial intelligence) Predictive models Prediction algorithms

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A Short-Term Regional Wind power Prediction Method Based on XGBoost and Multi-stage Features Selection

A Short-Term Regional Wind Power Prediction Method Based on ...

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IEEE Student Conference on Electric Machines and systems

作者： Wenze Li Xiaosheng Peng Kai Cheng Hongyu Wang Qiyou Xu Bo Wang Jianfeng Che School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan Hubei China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

When wind power is integrated to the grid on a large scale, the power system is greatly disturbed by wind power because of the randomness and volatility of wind power. Regional wind power prediction (WPP) is an effective measure to improve the ability of grid to absorb wind energy. A short-term regional WPP method based on XGBoost and multi-stage features selection is presented in the paper to improve the accuracy and efficiency of regional WPP. Firstly, the original features extraction of regional wind farm is performed, and high-dimensional features of regional wind farm are constructed. Then, the filtering features selection method and the embedded features selection method are applied to perform multi-stage features selection for the high-dimensional features of the constructed regional wind farm. The XGBoost short-term regional WPP method is constructed based on the results of multi-stage features selection. And the key parameters of XGBoost short-term regional WPP model are optimized. Finally, the results of the XGBoost short-term regional WPP method is compared with the four-hour regional WPP results of three models, which are regression tree, random forest and Support Vector Machine (SVM). The result is shown that compared with regression tree, random forest and SVM, Root Mean Squared Error (RMSE) of the XGBoost model is reduced about 1% in the 4-hour regional WPP.

关键词： Support vector machines Vegetation Wind power generation Predictive models Wind farms Feature extraction Regression tree analysis

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Numerical and Experimental Research on Electromagnetic-Thermal and Leakage Defects Characteristics of the High Voltage Cable Terminal

SSRN

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SSRN 2023年

作者： Liu, Xingmou Gu, Yan Li, Lei Yang, Yongming Cheng, Peng Jadoon, Ammad Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China State Grid Sichuan Electric Power Company Chengdu Power Supply Company Chengdu610000 China NFC-Institute of Engineering &Technology Multan Pakistan

Thermal and insulation performance of the High Voltage Cable Terminal (HVCT) could effectively improve the reliability and economy of power energy transmission. In this paper, a numerical model of the electromagnetic heat flow field was proposed to analyze the heat transfer and temperature characteristics of HVCT under oil leakage defects. This model was the first validated using operation data from the actual equipment and the relative error was less than 1.51%. The effects of oil leakage fault on the global and local temperature distribution of the HVCT were then investigated under different load currents. In addition, the local temperature rise effect of different ambient temperatures on the HVCT oil leakage defect was also considered. Finally, combined with reference indicators such as oil level, temperature, and temperature gradient, a qualitative and quantitative evaluation of the oil leakage fault of HVCT was performed. The results showed that the temperature of the core, surface, and their maximum temperature gradient were linearly related to the ambient temperature. However, the temperature of the core at the oil leak exceeded the normal temperature by up to 7.2 °C with 1000A load current, and the temperature gradient change reaches 681.3 °C/m, which indicated that the convection heat dissipation effect of the oil-deficient part was poor, and the heat accumulates near the cable core. Therefore, the numerical model and analytical results presented in this paper provided an important method for online temperature monitoring and fault analysis of HVCTs. © 2023, The Authors. All rights reserved.

关键词： Thermal gradients

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Location and capacity of distributed photovoltaic generation connected to distribution network based on multi-objective genetic algorithm

Location and capacity of distributed photovoltaic generation...

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IEEE Advanced Information Management,Communicates,Electronic and Automation control Conference (IMCEC)

作者： Song Qing Tuo Xie Qingjun Bai Pai Li Institute of Water Resources and Hydro-Electric Engineering Xi'an University of Technology Xi'an China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665479691

In order to further improve the ecological environment in desert areas and actively respond to the development of the “dual carbon” policy, numerous distributed photovoltaics have been connected to the distribution network in recent years. Network loss caused a greater impact. For the location and capacity planning of distributed photovoltaic access to the distribution network, this paper proposes a distributed photovoltaic location and capacity model that considers investment costs, distribution network losses, voltage stability, and environmental protection costs. The improved multi-objective genetic algorithm is used to solve the optimization model, which is verified by example simulation. After the optimized configuration, the power supply quality and network loss of the distribution network are significantly improved, which verifies the feasibility of the model. This research provides a certain reference and reference for the location and capacity determination of the distribution network with distributed photovoltaics.

关键词： Photovoltaic systems Costs Biological system modeling power quality Urban areas Distribution networks Stability analysis

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Recombination Behaviour of Passivated Emitter and Rear Cell (PERC) Bifacial Silicon Solar Module under Different Illuminations

Recombination Behaviour of Passivated Emitter and Rear Cell ...

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IEEE Conference on Photovoltaic Specialists

作者： Xiaoli Cheng Xiaosong Wang Yihang Yang Xianxu Jin He Wang Hong Yang Zhilei Chen Qingbin Yang MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Xi’an Jiaotong University Xi’an People’s Republic of China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing People’s Republic of China

Bifacial silicon solar module has received considerable attention in recent years due to increasing the performance of photovoltaic plants. The passivated emitter and rear cell (PERC) bifacial silicon solar cell reduces contact recombination, and improves open-circuit voltage and cell performance. In this paper, recombination behaviour of passivated emitter and rear cell (PERC) bifacial silicon solar module under different illuminations was investigated. It is found that the J 01 of bifacial PERC solar module decreases with increasing irradiance intensity, and the J 02 is nearly constant from low injection to high injection. This shows that the PERC bifacial silicon solar module has more advantage in the field compared to Al-BSF solar module.

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