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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Hao, Chen Yong, Sheng Yanbing, Jia Jin, Zheng Tianhao, Song Gang, Luo Dong, Xie Shanxi Key Laboratory of power system operation and control Taiyuan University of Technology Taiyuan China Shaoxing Jianyuan Power Group Co. Ltd China State Grid Zhejiang Electric Power Company Shaoxing Power Supply Company Shaoxing China

ISBN: (纸本)9781728135205

The large-scale energy storage with fast, accurate and instantaneous throughput capability undertakes automatic generation control (AGC) to provide a high-quality resource for secondary frequency regulation(FR) in each control area. In order to allocate a reasonable-scale energy storage resource to the application scenarios of different power structure features, a storage capacity allocation method using CPS (control Performance Standard) index evaluation is proposed. Firstly, for the two power supply structures based on thermal power and hydropower formed in China, a simulation model of thermal power and hydropower interconnection system is proposed. Then, through the simulation to quantify the contribution degree of energy storage, it is verified that the energy storage FR requirements of different scenes are different, and the performance extremes and economic extremes of energy storage capacity configuration in different scenarios are obtained by using CPS performance evaluation indicators and their improvement. The proposed model and research results have important guiding significance for rational planning of energy storage capacity in each control area. © 2019 IEEE.

关键词： Energy storage

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QoE-aware user association and resource allocation for mixed services in heterogeneous networks 2

QoE-aware user association and resource allocation for mixed...

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2nd International Symposium on Application of Materials Science and Energy Materials, SAMSE 2018

作者： Li, Shuxian Tang, Liangrui Yan, Jiangyu State Key Laboratory of Alternate Electrical 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

In heterogeneous networks (HetNets), user association and resource allocation (UARA) is a great challenge for radio resource management (RRM). In this paper, a novel QoE-aware UARA scheme is proposed. The delay factor is introduced to QoE metric to weight delays' effect on service transmitting. Then the UARA scheme based on QoE is formulated as an optimization problem which is a mixed integer nonlinear programming (MINLP) problem. To solve the problem, we adopt the genetic algorithm (GA) and associate the user association and the resource with population and fitness respectively. Through the evolutions of genetic algorithm, the optimal UARA scheme can be worked out. The simulation results indicate that the proposed scheme can reduce packet loss rate, and improve the system load balancing performance. © Published under licence by IOP Publishing Ltd.

关键词： Resource allocation

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Comparative Study of EKF and UKF for SOC Estimation of Lithium-ion Batteries

Comparative Study of EKF and UKF for SOC Estimation of Lithi...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Xiao, Tian Shi, Xiaohan Zhou, Boxi Wang, Xiaolei Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid of China Technology College Jinan China Huaneng Shandong Power Generation Co. Ltd Jinan China

ISBN: (纸本)9781728135205

With the expanding application of lithium-ion batteries, the state of charge (SOC) estimation based on the Kalman filter (KF) draws great attention. However, lots of KF's variants, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF) are available. In order to find the suitable KF variant for SOC estimation, this paper studies the performance of EKF and UKF in three scenarios based on the two-order RC model by elaborative simulation. The accuracy and convergence of the two filters are compared. The impact of the model deviation on the estimated results is also tested to evaluate the robustness. The test results show that EKF performs much the same as UKF in its accuracy, rate of convergence as well as robustness to model errors in most cases. © 2019 IEEE.

关键词： Extended Kalman filters

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Wind power Fluctuation Smoothing with BESS Considering Ultra-short-term Prediction

Wind Power Fluctuation Smoothing with BESS Considering Ultra...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Zhao, Yawen Shi, Xiaohan Zhou, Boxi Wang, Xiaolei Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid of China Technology College Jinan China Huaneng Shandong Power Generation Co. Ltd Jinan China

ISBN: (纸本)9781728135205

Nowadays, power system often faces the intractable problem of power fluctuation due to the intermittency and stochasticity of renewable energy, such as wind and photovoltaics, generation system. The energy storage system, such as the battery energy storage system (BESS) is an effective way to smooth the power fluctuation so as to increase the allowed penetration level of renewable energy generation in power grid. However, the cost of the energy storage system is still very high and the efficient control strategies are needed to improve the benefit of per unit energy storage as high as possible. In view of that, this paper proposed a novel control strategy for BESS based on the common moving average filter (MAF) and ultra-short-term wind power forecast. By adding future wind power data predicted into inputs of the filter, the MAF could possess the characteristic of nearly zero phase delay, which almost eliminates the low-frequency components in the load of BESS. The control strategy proposed enables BESS to focus on the compensation of the high-frequency components of the wind power, therefore obtaining better smoothing results for given BESS and improving its economic efficiency. simulation results in various scenarios verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Wind power

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A novel smart community: Combining a flexible heating system as electrical demand response to enhance local renewable energy integration

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International Journal of Electrical power & Energy systems 2025年 169卷

作者： Yufei Xi Yuguang Song Meng Chen Jiansheng Zhang Lin Cheng Zhe Chen State Key Laboratory of Power System Operation and Control Tsinghua University Beijing 100084 China Department of Electrical Engineering Tsinghua University Beijing 100084 China Department of Engineering University of Cambridge Cambridge CB2 1PZ UK Department of Energy and Power Engineering Tsinghua University Beijing 100084 China AAU Energy Aalborg University Aalborg 9220 Denmark

Due to ineffective coordination, energy communities integrating wind turbines (WTs) and photovoltaic/ photothermal (PV/PT) systems often fail to fully harness local renewable energy sources. To overcome this challenge, this paper proposes a novel smart community (SC) framework that incorporates a flexible heating system (HS). The proposed HS facilitates dispatchable solar power generation and responsive heat–electricity demand management by integrating medium-high-temperature photothermal (MHTPT) and ground-source heat pump (GSHP) technologies. Meanwhile, a dual-objective scheduling model is formulated to minimize the operating costs and carbon emissions of the SC system, and its effectiveness is validated through case studies. A hybrid solution architecture combining branch-and-reduce with multi-learning-task is proposed to efficiently solve the mixed-integer nonlinear programming (MINLP) model and generate multiple optimal Pareto solutions. Case studies on different system configurations validate the superior performance of the proposed SC in reducing operating costs and carbon emissions while enhancing local renewable energy integration. Additionally, the impact of varying renewable on-grid tariffs on SC system operations is analyzed.

关键词： Smart community Flexible heating system Medium-high-temperature photothermal Demand response Load shaping Renewable energy integration Dual-objective optimization

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Consensus-Based Distributed Economic Dispatch with Optimized Transition Matrix

Consensus-Based Distributed Economic Dispatch with Optimized...

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IEEE power and Energy Society General Meeting

作者： Xinfei Yan Haiwang Zhong Jianxiao Wang Zhenfei Tan State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Beijing China

With an increasing penetration of distributed energy resources (DERs) in Energy Internet, there is a surge of interest in distributed economic dispatch (DED) problems. The existing literature mainly focuses on average consensus algorithms, the convergence of which remains a bottleneck in practical applications. To improve the convergence rate of DED, this paper proposes a consensus algorithm based on optimized transition matrix (TM) of Markov chain. A DED model is firstly developed under a consensus-based information exchange architecture, in which a generator only communicates with its neighbors. Thus DED is implemented in an iterative manner with generators exchanging information according to a predefined TM. In contrast to the aver-agely weighted TM, we minimize the Frobenius norm (F-norm) of the TM in order to limit the eigenvalues that greatly influence the convergence rate of DED. Additionally, a virtual power method is introduced to meet generators' power limits by reformulating the power allocation ratio. Case studies verify the effectiveness and efficiency of the proposed algorithm.

关键词：

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The parameter design method of smoothing inductance based on MMC-MTDC with R-type superconducting fault current limiter

The parameter design method of smoothing inductance based on...

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The 16th IET International Conference on AC and DC power Transmission (ACDC 2020)

作者： P. Guo Z. Yuan G. Liu Y. Zhao Z. Shi Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing China Shenzhen Power Supply Corporation Shenzhen China Sichuan Energy Internet Research Institute Tsinghua University Chengdu China

The rapid increase of voltage sourced converter brings the great development of the multi-terminal DC technology, both in the DC transmission and DC distribution fields. However, because of the weak impedance characteristic of the VSC-HVDC system, how to suppress and clear DC fault currents becomes a challenge. Considering the stability, the response speed and the system structure, it is not possible to apply excessive inductance at the DC side, hence, the current limiting effectiveness is relatively restricted. On the one hand, with the effective properties, Resistive type Superconducting Fault Current Limiter (R-SFCL) becomes an effective device to solve the problem of VSC-HVDC system under DC faults. On the other hand, because of dynamic energy-impedance characteristics of R-SFCL, the fixed impedance selection method at a certain time to carry out dynamic current limiting analysis is no longer applicable. Therefore, the DC fault current research and R-SFCL characteristic are comprehensively analyzed firstly in this paper. Based on that, a smoothing inductance determination method is proposed to cut off the DC fault current by DC breaker and ensure the continuous operation of remaining parts. Finally, based on a multi-terminal DC system simulation, the improvement and effectiveness of the proposed method are validated.

关键词： power transmission faults HVDC power transmission superconducting fault current limiters HVDC power convertors voltage-source convertors

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Ultra-short-term Bus Load Forecasting Method Based on Multi-source Data and Hybrid Neural Network

Ultra-short-term Bus Load Forecasting Method Based on Multi-...

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

作者： Shixiong Fan Xingwei Liu Weiwei Ma Wei Zhang Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China State Key Laboratory of Advanced Power Transmission Technology Global Energy Interconnection Research Institute co.Ltd. Beijing China National Power Dispatching and Control Center State Grid Corporation of China Beijing China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

Bus load forecasting plays an important role in terms of the safety of power grid dispatching and operation and the accuracy of online analysis and decision-making. In order to improve accuracy of bus load forecasting, this paper proposes an ultra-short-term load forecasting method based on multi-type data and hybrid model. Under the background of power big data, the multi-type data such as historical bus load data, date information and weather information are firstly taken as the input features of the prediction model, which is established based on the fusion of back propagation (BP-ANN) neural network and convolutional neural network(CNN). BP-ANN is used to extract the feature vectors of numeric type and category type data, which is concatenated with feature vectors extracted by CNN from image type data. The combined features are fed to a fully connected multilayer Neural Network to predict the bus load. In this paper, the historical data of active power load at the high voltage side of a 220kV substation in a certain area of China and the corresponding weather information are used for example analysis. The analysis of experimental results shows that the proposed method can make full use of the characteristics of multi-source data to conduct ultra-short-term bus load prediction, and it has higher load prediction accuracy compared to the single model prediction of BP-ANN and CNN.

关键词： Load forecasting Neural networks Predictive models Feature extraction Data models Data mining Load modeling

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A comprehensive intention prediction method considering vehicle interaction

A comprehensive intention prediction method considering vehi...

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Conference on Vehicle control and Intelligence (CVCI)

作者： Wenqi Cai Ganglei He Jianlong Hu Haiyan Zhao Yuhai Wang Bingzhao Gao Qingdao Legee Transmission System Technology Co. Ltd Qingdao China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun China Qingdao Automotive Research Institute Jilin University Qingdao China

ISBN: (数字)9781728184975

ISBN: (纸本)9781728184982

In this paper, an interactive intention prediction method is proposed. Firstly, the Hidden Markov Model integrated with Gaussian Mixture Model is modeled for current behavior recognition and its parameters are trained through NGSIM dataset. Then, a trajectory prediction method based on Frenet frame is used to predict the future traffic situation, considering which future behavior reasoning is realized by maximum expected utility theory. The final intention prediction result is a combination of historical trajectory recognition and future behavior reasoning. The simulation results show that the proposed method has the ability of reasonably reflecting the interaction process between vehicles and the prediction performance is good.

关键词： Utility theory simulation Hidden Markov models Prediction methods Cognition Trajectory Gaussian mixture model

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Frequency Security Assessment for Receiving-end system Based on Deep Learning Method

Frequency Security Assessment for Receiving-end System Based...

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IEEE/IAS Industrial and Commercial power system Asia (I&CPS Asia)

作者： Changhui Ma Liang Wang Chenhao Gai Dong Yang Pengfei Zhang Hengxu Zhang Changgang Li State Grid Shandong Electric Power Company Electric Power Research Institute Jinan Shandong China State Grid Shandong Electrical Power Company Dispatch and Control Center Jinan Shandong China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan Shandong China State Grid International Development Limited Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

For hours-ahead assessment of power systems with a high penetration level of renewable generation, a large number of uncertain scenarios should be checked to ensure the frequency security of the system after the severe power disturbance following HVDC blocking. In this situation, the full time-domain simulation is unsuitable as a result of the heavy calculation burden. To fulfill the quick assessment of the frequency security, the online frequency security assessment framework based on deep learning is proposed in this paper. The Deep Belief Network (DBN) method is used to establish the framework. The sample generation method is researched to generate representative samples for the purposed of higher assessment accuracy. A large-scale AC-DC interconnected power grid is adopted to verify the validity of the proposed assessment method.

关键词： Industrial power systems Asia Conferences

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