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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Li, Hao Zhang, Hengxu Xu, Qun Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan250061 China Qingdao Power Supply Company State Grid Shandong Electric Power Company China

ISBN: (纸本)9781538614273

Micro synchronous generation unit is a laboratory scale equipment to model the realistic behavior of a real generator set, control of which determines the operating state of the simulation system directly. This paper presents an integrated control instrument for micro synchronous generator (ICIMSG). ICIMSG integrates signal processing unit and power amplifying unit, realizing control functions such as generator starting and braking, automatic frequency regulation, automatic generator-voltage control (AVR) and automatic quasi-synchronizing paralleling. Light synchronized phasor measurement unit (PMU Light) is employed to monitor the generator set. Real-time operation information including frequency, voltage phasor and current phasor can be sent from PMU Light to ICIMSG through the internet. Appropriate software was developed on server to communicate with ICIMSG in a two-way manner through WiFi network. ICIMSG's real-time control and analysis capabilities provide a platform not only for innovative research ideas, but also for teaching general power system engineering concepts to students via physical experiments. All functions of ICIMSG proposed were tested on physical micro synchronous generator sets. © 2017 IEEE.

关键词： Synchronous generators

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Short-term wind power probabilistic forecasting considering spatial correlation

Short-term wind power probabilistic forecasting considering ...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Junxiong Han, Xueshan Jiang, Jiayin Li, Wenbo Ma, Yanfei Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Shandong Electric Power Rresearch Institute Jinan China State Grid Jinan Power Supply Company Jinan China

ISBN: (纸本)9781538614273

Wind power probabilistic forecasting is of great significance to the operation and dispatch of the power system. However, most researches have focused on how to predict wind power using local information rather than spatial correlation information of multiple wind farms in a region. In this paper a short-term wind power probabilistic forecasting approach considering spatial correlation is proposed. Originally, a set of explanatory variables highly correlated with the target variable is selected by calculating mutual information. Next, the principal component analysis can help to reconstruct the data and reduce the dimension of the explanatory variables. Finally, the conditional kernel density estimation is introduced to predict the short-term wind power of the target wind farm. Case studies on the dataset of Global Energy Forecasting Competition 2014 verify that the proposed approach can achieve better performance than traditional approach. © 2017 IEEE.

关键词： Principal component analysis

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A Transformer Fault Diagnosis Method Based on Bayesian Network

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Journal of Physics: Conference Series 2019年第5期1213卷

作者： Zhang Zhe-wen Wang Yong Ying Ding Tian lei Zhou Ying-jian Key Laboratory of Power System Intelligent Dispatch and control of Ministry of Education (Shandong university) Jinan 250061 Shandong Province China +*** Key Laboratory of Power System Intelligent Dispatch and control of Ministry of Education (Shandong university) Jinan 250061 Shandong Province China State Grid of China Technology College Jinan 250002 Shandong Province China State Grid Shandong Electric Power Company Finance Department Jinan 250001 Shandong Province China

This paper summarizes the fault types and fault hazards of the transformer, and combs the corresponding relationship between the transformer fault types and the fault symptoms, which provides reference for the transformer fault diagnosis and state maintenance. Based on the analysis of the existing transformer fault diagnosis, the transformer fault diagnosis based on Bayesian network is mainly studied. Bayesian network has advantages in machine learning, data reasoning and so on. It has been widely applied in the field of fault diagnosis. In this paper, the QMR model of transformer fault diagnosis is established by using the principle of Bayesian network and the relationship between fault type and fault feature, and the model is used to diagnose the specific fault. Then the paper further analyzes the result of fault diagnosis in order to prove the correctness and validity of Bayesian network.

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Chance-constrained programming model for reference network with wind power integration

Chance-constrained programming model for reference network w...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Sun, Donglei Yang, Jinhong Han, Xueshan Wang, Junxiong Tian, Xin Yang, Bin Zhang, Lina Wang, Nan Economic and Technology Research Institute of State Grid Shandong Electric Power Company China State Grid Shandong Electric Power Maintenance Company China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University China

ISBN: (纸本)9781538614273

With the large-scale integration of volatile wind power generations, power system operation and planning face the problem of increasing injection fluctuations and uncertainties. In this paper, chance constraint expressions are used to characterize the wind power uncertainty, and then a new chance-constrained programming model for reference network with wind power integration is proposed to ensure the expected wind power utilization. In the proposed model, the objective function is minimizing total power generation cost and transmission investment cost, and the constraints are the safety operation technical requirements under intact operation state and the preconceived contingency operation state. The sample average approximation (SAA) method is used to develop a deterministic approach for the proposed model. Numerical analysis shows the potential benefit of the proposed model. © 2017 IEEE.

关键词： Wind power

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A New power Flow Algorithm for Hybrid AC/DC power grid

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Journal of Physics: Conference Series 2019年第3期1213卷 032027-032027页

作者： Li, Jiawei Han, Xueshan Li, Wenbo Jiang, Zhe Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University) Jinan China. State Grid Shandong Electric Power Research Inxititute Jinan 250003 Shandong Province China.

Aiming at the problem of grid power flow calculation with VSC (Voltage Source Converter) unit in the context of the energy internet, this paper presents a new converter equivalent model. This study introduces a novel unified power flow algorithm for hybrid AC/DC power grids. The method simplifies the converter model by means of equivalent substitution and power conversion. The model better inherits the advantages of traditional AC power flow calculation. Finally, a unified iterative method is used to calculate an IEEE-57 node.

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Single-Phase-to-Ground Fault Diagnosis Method based on Waveform Features and Association Rule Algorithm

Single-Phase-to-Ground Fault Diagnosis Method based on Wavef...

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International Conference on Renewable power Generation

作者： Linlin Zhang Kai Xu Fang Shi Yunbo Wang Shuozheng Liu The Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education (Shandong University) 17923 Jingshi Road Jinan PR China Shenhua Guoneng Shandong Construction Group Jinan P.R. China 250001 Guangxi Power Grid Company Nanning Power Supply company 43 Xingguang Road Nanning China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The single-phase-to-ground fault current of distribution network is small, which brings difficulties to fault diagnosis. A single-phase-to-ground fault diagnosis method based on synchronous waveform feature extraction and association rule mining is proposed. Firstly, features are extracted from waveform of fault recorders to describe the fault scene. Then, FP-Growth algorithm is used to mine the association rules in the fault transaction database. The effectiveness of proposed method is verified by IEEE 34-bus system. Algorithm in this paper provides a useful reference for fault diagnosis technology based on fault waveform features.

关键词： Waveform features Association rules Single-Phase-To-Ground Fault diagnosis

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Real-time synchronous data visualization for wide area power systems

Real-time synchronous data visualization for wide area power...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Li, Yi Zhang, Hengxu Zhou, Gang Liu, Gang Feng, Zhongkui Meng, Qinggang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan250061 China Zibo Power Supply Company State Grid Shandong Electric Power Company Zibo370303 China

ISBN: (纸本)9781538614273

With the construction of global energy interconnection, plenty of fluctuating renewable energy access the distribution network, power system dynamic behavior is more complex. The wide-area measurement system light (WAMS Light) records the actual variation of the grid in the distribution network with high accuracy. Exploring the value of high-density, large-scale synchronous data and comprehensive visualization can efficiently reflect the behavior of the system. An open and interactive WAMS Light data visualization platform (WAMSLVP) is built with three-tier structure. WAMSLVP is designed by analysing the function requirements in multi-information fusion, multi-angle analysis, multi-layer integration, program flexible access based on the characteristics of distribution network. And WAMSLVP integrates the frequency, voltage magnitude, angle phase and other power information with the non-power information as multiple layers to compositive display based on geographic information system (GIS), facilitating the dispatchers simultaneously capture multiple information from different analysis just by a glance. © 2017 IEEE.

关键词： Condition monitoring

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Optimal Consensus control of Unknown Nonlinear Multi-Agent Systems Using Adaptive Dynamic Programming via MRAC

Optimal Consensus Control of Unknown Nonlinear Multi-Agent S...

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Chinese control Conference (CCC)

作者： Hao Fu Xin Chen Wei Wang Jinbin Li Yaodong Zhang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China State Grid Hubei Electric Power Research Institute Wuhan P. R. China

This paper introduces an optimal consensus control scheme for nonlinear multi-agent systems with completely unknown dynamics. In general, it is difficult to solve the coupled Hamilton-Jacobi-Bellman (HJB) equations, which the optimal consensus control relies on in multi-agent systems, especially unknown nonlinear systems. For the purpose of solving the problem, we propose an optimal consensus control approach based on the model reference adaptive control (MRAC) and adaptive dynamic programming (ADP). Using the structure of the diagonal recurrent neural network, the identifier and controller are devised to achieve MRAC for every plant of the unknown nonlinear systems, i.e. the reference model serves as a dynamic model of each individual agent. Then, according to reference models of distributed agents, an adaptive dynamic programming (ADP) is introduced to approximate the solution of the coupled HJB equations.

关键词： Multi-agent systems Mathematical model Adaptation models Heuristic algorithms Recurrent neural networks Dynamic programming

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Effective steady-state security regions of power systems considering voltage magnitude

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IOP Conference Series: Earth and Environmental Science 2019年第1期354卷

作者： Y Zhou X L Yang M Yang Y Zhu C Wang Y F Bo P J Du Key Laboratory of Power Intelligent Dispatch and Control (Shandong University) Ministry of Education Jinan 250061 China Economic & Technology Research Institute of State Grid Shandong Electric Power Company Jinan 250021 China Pingdu Electrical Power Bureau of State Grid Shandong Electric Power Company Pingdu 266700 China

With high-level variable renewable energy integrating into power systems, the uncertainty significant challenges to the real-time dispatch (RTD). Meanwhile, the influence of voltage magnitude and reactive power on RTD always were ignored. Based on effective steady-state security regions of power systems and linear power flow model, a real-time dispatching method considering voltage magnitude and reactive power is proposed in this paper. This model has two goals, one is the security goal, the other is the economic goal, and priority of security objectives is higher than economy. Unlike previous real-time dispatch methods, all of the operation base point, reactive power output and participation factors of automatic generation control (AGC) generators are chosen as decision variables in the model. In order to ensure computational efficiency, the model is finally transformed into a deterministic linear programming (LP) problem by robust optimization and other methods. The accuracy and computational efficiency of the method are illustrated by modified IEEE 9-bus system and IEEE 118-bus system.

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Input data analysis for the thermal rating prediction of the overhead conductor

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IOP Conference Series: Earth and Environmental Science 2019年第5期371卷

作者： Li Wenbo Xing Luhua Fu Shanqiang Li Huadong Jiang Zhe Chen Bo Electric Power Research Institute State Grid Shandong Electric Power Company Jinan Shandong Province 250003 China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University) Jinan China Jining Power Supply Company State Grid Shandong Electric Power Company Jining Shandong Province 272100 China

The thermal rating of the overhead conductor is closely related to meteorological factors such as wind speed, wind direction, ambient temperature and solar radiation. Therefore, both the historical thermal ratings and meteorological data are alternative input data to predict the thermal rating of the overhead conductor. It is important to select suitable input data to improve the prediction accuracy of the prediction results. Based on the collection of micro-meteorological data from overhead line monitoring system, this paper presents a method to determine the input data for the thermal rating prediction by analysing the autocorrelation of overhead thermal ratings and the cross-correlation between thermal rating and historical micrometeorological data. The results show that the proposed method can provide reference information for the selection of predictive input quantities and prediction time domain.

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