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10th renewable power Generation Conference, RPG 2021

作者： Hu, Bo Wang, He Zhou, Guiping Xu, Xiangsheng State Grid Liaoning Electric Power Co. Ltd. Shenyang China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781839536069

Optical fiber composite low-voltage cable which combines optical fiber and power cable organically plays an important role in the construction of smart grid and the development of energy internet. The change of temperature impacts the working state of the OPLC and the precision of parameter measurement. Thus, the establishment of the OPLC thermal circuit model has important practical significance. Focusing on the attributes of different kinds and various constructions of the OPLC, this paper proposes an OPLC modeling method based on the superposition principle. Firstly, the asymmetric OPLC is equivalent to several symmetric sub-models, and then each model is superimposed by superposition principle. Secondly, the particle swarm algorithm is utilized to realize the model boundary distinguishing identification, improve the accuracy of the parameters, acquire a precise thermal circuit model, and then realize the accurate calculation of temperature at different positions of OPLC. This paper establishes an OPLC thermal circuit model based on the four-cable core OPLC and proves the effectiveness of the method through simulation analysis and experimental verification. © The Institution of Engineering and technology.

关键词： Optical fibers

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Short-term power Prediction of Wind power Cluster Based on KOA-PLE

Short-term Power Prediction of Wind Power Cluster Based on K...

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IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Nan Wu Mao Yang Chenglian Ma Yunpeng Jia Guozhong Fang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China Jilin Power Supply Company of State Grid Jilin Electric Power Co. Ltd Jilin China State Gird Northeast China Branch Jilin China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

With the gradual acceleration of the world's energy transformation, the construction of new energy is becoming more and more large-scale. At the same time, the proportion of new energy in the power grid is increasing, and the high volatility of wind power poses certain challenges to the stability and reliability of the power system. Therefore, accurate large-scale wind power prediction is very necessary. This paper presents a multi-task learning predicting method for wind power clusters. Firstly, the wind power cluster is divided into subgroups with similar output characteristics, and then the different subgroup power is used to predict the multi-task targets. Meanwhile, the Kepler optimization algorithm (KOA) is used to optimize the model parameters. When the method is applied to a wind power cluster in China, RMSE and MAE are reduced by 2.07% and 1.92% compared with the traditional multi-task learning method, which proves the effectiveness of the proposed method.

关键词： Learning systems Clustering algorithms system integration Wind power generation power system stability Multitasking Prediction algorithms Stability analysis Reliability Optimization

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Damping Torque Analysis of the PLL Low-Frequency Components for Grid Following VSG

Damping Torque Analysis of the PLL Low-Frequency Components ...

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2022 International Conference on Cyber-Physical Social Intelligence, ICCSI 2022

作者： Zhou, Yichen Li, Sha Sun, Jiahui Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Electrical and Electronic Engineering North China Electric Power University Jilin China Guangdong Power Grid Corporation Dongguan Power Supply Bureau China Southern Power Grid Guangdong Dongguan China North China Electric Power University Electrical and Electronic Engineering Hebei Baoding China

ISBN: (数字)9781665498357

ISBN: (纸本)9781665498357

Phase-locked loop (PLL) is the key tool for the grid-connected inverter to track the frequency and phase of the grid voltage when synchronizing with the power grid. Therefore, the stability of PLL is particularly important. This paper proposes a damping torque analysis method to study the stability of the low-frequency component of PLL for the grid following a virtual synchronous generator (VSG). Firstly, the small signal model is established for the grid following VSG with a dual-loop structure. Secondly, the damping torque analysis method is provided especially for the stability analysis of PLL low-frequency components. And the corresponding stability criterion is constructed. Finally, significant factors that affect the stability of PLL low-frequency components are studied by the test system and the corresponding mechanism is revealed, including the influence of line reactance, PLL control parameters, and virtual damping. Results show that the stability of PLL is greatly dominated by the low-frequency component, whose stability can be improved by adopting a smaller integral coefficient of PLL, smaller virtual inertia, and larger virtual damping D. © 2022 IEEE.

关键词： Stability criteria

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Design of Dual Band Microstrip Filter Based on SIR 19

Design of Dual Band Microstrip Filter Based on SIR

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19th International Conference on Optical Communications and Networks, ICOCN 2021

作者： Zheng, Xuemei Gao, Peng Han, Yaru Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China Jilin design department China Mobile Design Institute Co. Ltd Changchun China

ISBN: (纸本)9781665424462

As the core device in the field of communication, filter is developing towards miniaturization and high frequency. In this paper, a new dual frequency filter based on step impedance resonator is proposed. The resonant frequencies of the proposed stepped impedance resonator (SIR) dual frequency filter are 2.4GHz and 5.2GHz, and the isolation is greater than 20dB. © 2021 IEEE.

关键词： Microstrip filters

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Ultra-short-term power Prediction of Photovoltaic based on CNN-AM-BiLSTM

Ultra-short-term Power Prediction of Photovoltaic based on C...

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IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Junhui Li Mingxuan Du Haozheng Yu Jie Ma Youwen Zhang Jiatao Gan Xingxu Zhu Cuiping Li Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China AnYang Power Supply Company State Grid HeNan Electric Power Company AnYang China Economic and Technical Research Institute State Grid HeNan Electric Power Company ZhengZhou China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

The power of photovoltaic power generation is affected by a variety of factors such as weather, radiation and temperature, exhibit a high degree of randomness and uncertainty. To address this problem, this paper proposes a ultra-short-term photovoltaic power prediction model based on Convolutional Neural Networks (CNN) and attention mechanism and bidirectional long short-term memory (Bi-LSTM). Firstly, Pearson's correlation coefficient was used to filter out the meteorological factors which have significant influence on the historical power. Subsequently, in order to capture the spatial features of the input data, a convolutional neural network is utilized for feature extraction and an attention mechanism is introduced to strengthen the model's ability to discriminate key features. Meanwhile, the Bi-LSTM network is utilized to capture the temporal dependencies in the time series data, and finally the PV power prediction value is obtained. Finally, the validation is based on data from actual PV power plants, and the results show that the proposed Convolutional Neural Networks and attention mechanism (CA) and Bi-LSTM Ultra-short-term PV power prediction model outperforms the single model in terms of prediction accuracy, reflecting the effectiveness and superiority of the hybrid model.

关键词： Photovoltaic systems Accuracy Attention mechanisms Time series analysis Weather forecasting Predictive models Feature extraction Data models Hybrid power systems Convolutional neural networks

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Operational Optimization of Photovoltaic-Storage system Considering Demand Response

Operational Optimization of Photovoltaic-Storage System Cons...

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IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Xuefeng Gao Wenwen Qin He Wang Yiwen Yao Cuiping Li Hao Peng Xingxu Zhu Junhui Li State Grid Jilin Electric Power Company Limited Economic and Technical Research Institute Changchun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University China Songyuan Power Supply Company State Grid Jilin Electric Power Company Limited Songyuan China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

Aiming to address the stability challenges in power systems caused by the volatility and uncertainty of photovoltaic (PV) power generation, an optimization strategy for PV-storage systems incorporating demand response (DR) is proposed. Which is based on PV generation characteristics, Time-of-Use Pricing (TUP), and demand side flexibility. A multi-objective optimization model is established to balance the operational and environmental costs of PV-storage configuration. Building on dynamic adjustments at the demand side, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with dynamic inertia weighting is introduced to enhance global search capability for optimized energy storage (ES) configuration. In case study, two scenarios are designed to validate the effectiveness of the proposed model in reducing costs and improving PV utilization rates.

关键词： Photovoltaic systems Costs Uncertainty Heuristic algorithms Optimization models power system dynamics power system stability Demand response Optimization Load modeling

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Multi-objective Optimal Allocation Strategy for Distributed energy Storage in Distribution Networks Adapted to High Penetration Distributed Photovoltaics

Multi-objective Optimal Allocation Strategy for Distributed ...

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power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Cuiping Li Yanli Wang Yiming Chen Xuesong Qi Yunjing Liu Qian Fang Shengyuan Cui Yuming Wang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China Science and Technology Section State Grid Shanghai South Power Supply Company Shanghai China Power dispatching and control center Jilin Power Supply Company Jilin China Science and Technology Section Jilin Power Supply Company Jilin China Ministry of Science and Technology Jilin Power Supply Company Jilin China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

High percentage of photovoltaic gain connect to the wire line, so that the electricity grid from power distribution of the receiving end of the network into a set of production, storage, distribution of multi-source complex new network, the distribution network security operation and new energy consumption pressure increases. In response to the above, this paper puts forward the distributed ES multi-objective optimization configuration strategy of distribution network adapted to the high penetration rate distributed PV. And through a county power grid practical example to certify that the ES configuration approach proposed can effectively mitigate the impact of a high proportion of PV accessed, and it can reduce the abandonment of light.

关键词： Photovoltaic systems Wires Distribution networks Production power grids Regulation Resource management

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Multi-Objective Model Predictive control Strategy in Waked Wind Farms for Optimal Fatigue Loads

SSRN

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SSRN 2023年

作者： Zhong, Cheng Ding, Yicheng Wang, Husai Chen, Jikai Wang, Jian Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Province Jilin132012 China Northeast Electric Power University College of Electrical Engineering Jilin Province Jilin132012 China

With the rapid growth of wind power penetration, wind farms (WFs) are required to implement frequency regulation that active power control to track a given power reference. Due to the wake interaction of the wind turbines (WTs), there is more than one solution to distributing power reference among the operating WTs, which can be exploited as an optimization problem for the second goal, such as fatigue load alleviation. In this paper, a multi-objective closed-loop model predictive controller is developed that minimizes the wind farm tracking errors, the dynamical fatigue load, and the load deviation from the mean value. The controller is evaluated in a medium-fidelity model. A 3*3 WTs simulation case study is used to demonstrate the control performance for different penalty factor settings. The results indicated the WF can alleviate dynamical fatigue load and have no significant impact on power tracking. However, it can bring excessive loads on the upstream WTs. By adding a trade-off between the load equalization and dynamical fatigue load, the load differences between WTs are significantly reduced and loads of the upstream WTs can be reduced, while the dynamical fatigue load slightly increases when selecting a proper penalty factor. © 2023, The Authors. All rights reserved.

关键词： Fatigue load

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Pre-configuration Method and Scheduling Strategy of Distribution Network Mobile energy Storage Vehicle Considering Intermittent Load of Rural Network

Pre-configuration Method and Scheduling Strategy of Distribu...

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Electronics and Devices, Computational Science (ICEDCS), International Conference on

作者： Xiaoming Lu Yiwen Yao Yechen Xin Dingheng Wang Xinhong Wang Xin Xu Hao Li Economic and Technological Research Institute State Grid Jilin Electric Power Co. Ltd Changchun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China State Grid Jilin Electric Power Co. Ltd Changchun China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

Aiming at the problem of heavy overload in the distribution station area during the peak period of energy consumption caused by intermittent loads such as agricultural motor wells, the mobile energy storage technology is considered to meet the agricultural power demand, and a two-stage mobile energy storage vehicle pre configuration and dynamic adjustment strategy of "Rural busy power energization" and "rural idle distributed energy storage" is proposed, taking into account the guarantee of load power demand and the efficiency and economy of energy storage. Firstly, the mathematical model of agricultural motor well load considering the time shift characteristics and the mobile energy storage vehicle model considering the power supply time constraint are established; Secondly, a multi-stage mobile energy storage configuration and scheduling strategy is established. In the Rural busy power generation stage, the mobile energy storage vehicle capacity is configured with the minimum daily power supply cost as the goal, and the power supply path is optimized with the highest charge state consistency at the completion of power supply as the goal; At the stage of distributed energy storage in rural slack, the collaborative optimization of mobile energy storage vehicles participating in multi scenario power services is carried out with the goal of maximizing the annual net income. Finally, the proposed two-stage strategy has certain economic benefits under the premise of meeting the power demand of the load, which is verified by combining the power consumption data of wells in Jilin Province and IEEE 33 bus system simulation.

关键词： energy consumption power demand Costs Distribution networks Motors Time factors Vehicle dynamics Optimization energy storage Load modeling

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Dynamic Security Assessment Method of power system Based on Improved XGBoost 3

Dynamic Security Assessment Method of Power System Based on ...

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2020 3rd International Conference on Mechanical, Electrical and Material Application, MEMA 2020

作者： Ren, Jihong Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin Jilin132012 China

With the deployment of wide-area measurement systems (WAMS) equipment, dynamic security assessment (DSA) based on artificial intelligence (AI) has more and more advantages. For the power system, the number of transient stable cases is much larger than that of unstable cases, which leads to insufficient learning of unstable cases and affects the evaluation effect of the model. In addition, during the stability assessment process of the power system, the misjudgment cost of unstable case is much higher than that of stable case. Based on the above two points, we proposed a DSA method of power system based on improved XGBoost. The proposed method introduces the weight adjustment factor into the loss function to balance the quantity variance of two type cases and the difference of misjudgment cost, which greatly reduces the misjudgment rate of unstable samples. The test results on IEEE 16-machine 68-bus test system and IEEE 50-machine 145-bus test system show that the proposed method can have higher recognition of the unstable samples and can be applied to DSA. © Published under licence by IOP Publishing Ltd.

关键词： system stability

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