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检索条件"机构=State Key Laboratory of Operation and Control of Renewable Energy& Storage Systems"

共 607 条记录，以下是121-130 订阅

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Two-level Day-ahead Optimal Scheduling of Distributed energy storage System 4

Two-level Day-ahead Optimal Scheduling of Distributed Energy...

引用

4th IEEE China International Electrical and energy Conference, CIEEC 2021

作者： Wang, Maochun Li, Pai Sang, Zhencheng Fan, Yue Li, Qing Zhou, Wei State Grid Qinghai Electric Power Company QingHai China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy Storage Systems Beijing China

ISBN: (纸本)9781728171494

Stochastic characteristics of wind and photovoltaic (PV) power causes great challenge for power system operations. Distributed energy storage system (DESS) can mediate the intermittent renewable energy. This paper proposes a two-level optimization method for DESS scheduling. Firstly, DESSs are aggregated in a virtual power plan (VPP) and participates the power scheduling as a whole, the power schedules of DESSs are obtained with the proposed two-level optimization method. Secondly, in the upper-level optimization model, a two-stage stochastic unit commitment model is established with considering power uncertainties, and thermal units as well as VPP of DESS are optimized to maximize the power generation of renewable energy. And then, in the lower-level optimization model, an optimization model is proposed to schedule each DESS in order to minimize the total life loss cost of DESSs. Case studies are inducted based on actual data of a provincial power grid. The effectiveness and practicability of the proposed method is verified by the testing results. © 2021 IEEE.

关键词： Stochastic systems

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Short-Term Wind Power Forecasting for Multiple Farms with Alternating Temporal and Graph Convolutional Networks

Short-Term Wind Power Forecasting for Multiple Farms with Al...

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Electrical Engineering and Green energy (CEEGE), International Conference on

作者： Guoqing Li Jianfeng Che Dagui Liu State Grid Xinjiang Electric Power Corporation Urumqi PR China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing PR China

Accurate wind power forecasting (WPF) is very important for stable and reliable power grid integration. Existing WPF approaches make predictions based on numerical weather prediction (NWP) of a single wind farm, where the spatial and temporal correlations among geographically adjacent wind farms are not considered. In this paper, we propose a novel WPF approach for multiple farms by integrating temporal convolution networks (TCN) and graph convolution networks (GCN). Abstracting the set of multiple wind farms into a graph, spatial information is aggregated with GCN on the irregular non-Euclidean mesh defined by the graph. For each farm, temporal information is fused via TCN. With alternating temporal and graph convolution layers, features are extracted from inputs and integrated for forecasting. As demonstrated by experimental results on data from a set of wind farms in Ningxia, China, the proposed WPF for multiple farms performs much better than existing approaches for a single farm.

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Data Processing Technology of Power Grid Measurement Based on Error Correction

Data Processing Technology of Power Grid Measurement Based o...

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International Conference on Multi-modal Information Analytics, MMIA 2021

作者： Dong, Weijie Luo, Kui Shi, Guanghui He, Guoqing Sun, Wenwen State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems China Electric Power Research Institute Beijing China Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9783030748135

This paper deduces the basic formula of the measured data, obtains the formula of the static data expressed by the measured data, and analyzes the principle of the random error of parameter estimation caused by the measured data. Then through the method of mean value error correction, the mean value verification and matching transformation of the measured data are carried out, and the simulation results show that the proposed method can accurately complete the estimation of power line parameters. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Parameter estimation

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Optimal operation of Flexible Interconnected Distribution Networks

Optimal Operation of Flexible Interconnected Distribution Ne...

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2021 International Conference on Advanced Electrical Equipment and Reliable operation, AEERO 2021

作者： Qi, Qi Xie, Hongbin Qi, Buyang Xu, Yanping Li, Pai China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy Storage Systems Beijing China Tsinghua University Department of Electrical Engineering Beijing China

ISBN: (纸本)9781665402644

With large-scale distributed generation (DG) being integrated into distribution networks, the idea of using power electronic devices to improve distribution network operation have attracted increasing attentions. The transition of distribution networks into flexible interconnected ones, which contain considerable penetrations of AC/DC converters and soft open points (SOPs) is foreseen. In this paper, an optimization framework to improve the operation of the new form of distribution networks is proposed, where a novel searching technique is developed to determine the optimal set-points of the power electronic devices with increased efficiency. A generic power flow algorithm considering different modes of the controllable devices is presented, where the power flow problem is formulated into a set of nonlinear equations, and a globally convergent Newton-trust region method is adopted to solve it. Results of the case study demonstrate the feasibility and efficiency of the proposed method. © 2021 IEEE.

关键词： Distributed power generation

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A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping controller for Power System with Time-delay and Packet Dropout

A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping ...

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Power and energy (PandaFPE), Panda Forum on

作者： Di Cao Guozhou Zhang Jiaxiang Hu Weihao Hu Yuehui Huang Zhe Chen State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China Department of Energy Technology Aalborg University Aalborg Denmark

This paper proposes a deep reinforcement learning (DRL) based adaptive sparsity promoting wide-area damping controller for power system. Different from traditional fixed wide-area control structure, the proposed method employs DRL algorithm to identify the optimal sparsity promoting control structure and obtain corresponding parameter settings under different operating conditions considering the time-delay and packet drop. Simulation are carried out on 10-machine 39-bus system to demonstrate the effectiveness of the proposed approach.

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Research on Early Warning of Continuous Commutation Failure of HVDC Transmission Line Based on Machine Learning Methods 10

Research on Early Warning of Continuous Commutation Failure ...

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10th renewable Power Generation Conference, RPG 2021

作者： Wang, Bin Sheng, Yibo Liu, Chao Li, Yan State Key Laboratory of Operation and Control of Renewable Energy and Storage System Beijing China Dept. of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9781839536069

High-voltage direct current (HVDC) transmission systems have developed rapidly in recent years. Continuous commutation failure is a serious malfunction in HVDC transmission systems, which results in the blockage of the converter station. Though commutation failure is inevitable when serious AC side faults occur, continuous commutation failure can be prevented by control methods based on a sensitive and accurate forecast. However, the HVDC transmission systems are complex and nonlinear when commutation failure occurs. Thus, analytical methods are limited. Hence, a new forecasting method based on machine learning is introduced. First, this paper analyses the physical process of commutation failures. Commutation voltage, direct current, and advancing firing angle are the main factors that affect the commutation failure of HVDC. Second, this paper realizes the training and evaluation of the continuous commutation failure classification and probabilistic forecasting model. Data processing and feature engineering methods have significantly improved the model performance. Finally, the proposed model is tested on the CIGRE benchmark system. The proposed model can predict whether a continuous commutation failure will occur within tens of milliseconds after the first commutation failure, where the risk of continuous commutation failure is greatly reduced. © The Institution of Engineering and Technology.

关键词： Data handling

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A Common Bus Voltage Compensation Method for Microgrid Based on Voltage Drop Estimation 6

A Common Bus Voltage Compensation Method for Microgrid Based...

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6th International Conference on Power and renewable energy, ICPRE 2021

作者： Miao, Fenglin Zhang, Fan Xie, Hongbin He, Jing Li, Xinning Jia, Chunjuan China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy Storage Systems China Shandong University School of Electrical Engineering Jinan250061 China

ISBN: (纸本)9781665449618

When multiple distributed renewable energy sources with the characteristics of virtual synchronous generator are paralleled in microgrid, the power distribution of the parallel inverter is unbalanced due to the mismatch of feeder impedance, and the common bus voltage drop problem. In this paper, a mathematical model of the parallel system is established to analyze the conditions of power sharing, and the virtual impedance method is used to improve the accuracy of power sharing of the inverter. However, the virtual impedance in series will increase the voltage drop of the line and cause the voltage of the common bus to deviate from the rated value, thus affecting the power quality. Therefore, based on the theoretical analysis of the voltage drop caused by the virtual impedance method, a voltage compensation method based on the voltage drop estimation for the common bus of microgrid is proposed. Finally, using MATLAB/SIMULINK software to build a distributed sources parallel system simulation model to verify the correctness of the virtual impedance to achieve power balance distribution and common bus voltage compensation methods. © 2021 IEEE.

关键词： Electric inverters

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Short-term PV power prediction model based on weather feature clustering and Adaboost-GA-BP

Short-term PV power prediction model based on weather featur...

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第35届中国控制与决策会议

作者： Yujun Liu Xinrui He Shutong Duan Bo Wang Hongqing Wang College of Science Beijing Forestry University School of Economics & Management Beijing Forestry University State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute

Based on the weather feature clustering,an optimized algorithm called Adaboost-GA-BP is presented for solving the problem that BP neural network is easy to fall into local extremum and over-fitting in PV power short-term ***,the K-means algorithm is applied to cluster the historical data into sunny,cloudy and overcast&rainy *** is then the GA that optimize initial weights,forming the GA-BP neural *** idea of Adaboost algorithm is applied to train GA-BP as different weak predictors so that the Adaboost-GA-BP strong predictor is ***,this paper provides a detailed performances comparison of various *** AdaboostGA-BP predicts a 4.4% decrease in MAE and a 4.1% decrease in RMSE for the sunny test set,a 9.0% decrease in MAE and a13.5% decrease in RMSE for the cloudy test set,and a 2.7%decrease in MAE and a 9.1% decrease in RMSE for the rainy test set,outperforming the BP model,the GA-BP model,and the Adaboost-BP *** comparative analysis,the model has better prediction accuracy and generalization ability especially for predicting cloudy weather.

关键词： photovoltaic power short-term forecast backpropagation neural network genetic algorithm Adaboost algorithm weather clustering

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Absolute Stability Analysis of Single-Phase Grid-Tied Inverters with Open-Loop Synchronization

Absolute Stability Analysis of Single-Phase Grid-Tied Invert...

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Sustainable Power and energy Conference (iSPEC)

作者： Yu Qiao Jinming Xu Zhilei Chen Jiahua Kang Cheng Cheng College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (China Electric Power Research Institute) Beijing China

For grid-tied inverters, rapid and accurate obtainment of real-time grid phase is the basic and important function for stable operation. Among existing grid synchronization schemes, open-loop synchronization (OLS) methods have attracted much concern in recent years due to fast response and the elimination of feedback loop. It is noted that near-term studies focus on the analysis and improvement of performance of OLS itself mainly, while the stability issue of OLS-based grid-tied inverter (OLS-GTI) under non-ideal grid conditions is not analyzed deeply. Because OLS owns a strongly nonlinear structure, it is hard to apply the linearized modelling and criterion to facilitate the investigation of OLS-GTI stability. Hence, to cope with this issue, based on Sector and Circle Criterion used for the stability analysis of nonlinear system, this study analyzes the OLS-GTI stability. Firstly, by setting the voltage and current amplitude benchmark, the bounded condition of nonlinear sector is acquired. Then, the absolute stability range of OLS-GTI is obtained by the Circle Criterion. Furthermore, the impact of non-ideal conditions and OLSGTI control parameters on the system stability are analyzed. Finally, the stability of OLS-GTI is tested. Using Sector and Circle Criterion can help judge the stability of OLS-GTI intuitively and facilitate the design of inverter under complex grid conditions.

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Research on electromagnetic transient real-time simulation compensation algorithm of power system with large-scale new energy

Research on electromagnetic transient real-time simulation c...

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China International Electrical and energy Conference (CIEEC)

作者： Yang Li Xing Zhang Guoqing He Danyang Chen State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems China Electric Power Research Institute (CEPRI) Beijing China State Grid Shanxi Electric Power Research Institute Taiyuan Shanxi China

The math model of power system with large scale new energy including a large number of power electronic switch devices model, and semi physical real time simulation research of new energy integration control algorithm often uses a relatively larger simulation step size, thus this situation greatly reduces the simulation accuracy and stability of model with a large number of power electronic devices. This paper proposes a real time simulation compensation algorithm for fixed step to solve the problem. This algorithm compensates PWM waveform sampling error because of the fixed step real time simulation to improve the simulation accuracy, at the same time, it avoids the problem that the traditional algorithm increases the amount of computation with the increase of switching devices, laying the foundation for power system real-time simulation with large scale new energy.

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