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Inter-hour direct normal irradiance forecast with multiple data types and time-series

Journal of Modern Power Systems and Clean Energy 2019年第5期7卷 1319-1327页

作者： Tingting ZHU Hai ZHOU haikun wei Xin ZHAO Kanjian ZHANG Jinxia ZHANG Key Laboratory of Measurement and Control of CSE Ministry of EducationSchool of AutomationSoutheast UniversityNanjing 210096China State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems(China Electric Power Research Institute) Nanjing 210003China

Boosted by a strong solar power market,the electricity grid is exposed to risk under an increasing share of fluctuant solar *** increase the stability of the electricity grid,an accurate solar power forecast is needed to evaluate such *** terms of forecast,solar irradiance is the key factor of solar power generation,which is affected by atmospheric conditions,including surface meteorological variables and column integrated *** variables involve multiple numerical timeseries and ***,few studies have focused on the processing method of multiple data types in an interhour direct normal irradiance(DNI)*** this study,a framework for predicting the DNI for a 10-min time horizon was developed,which included the nondimensionalization of multiple data types and time-series,development of a forecast model,and transformation of the *** atmospheric variables were considered in the forecast framework,including the historical DNI,wind speed and direction,relative humidity time-series,and ground-based cloud *** were conducted to evaluate the performance of the forecast *** experimental results demonstrate that the proposed method performs well with a normalized mean bias error of 0.41%and a normalized root mean square error(n RMSE)of20.53%,and outperforms the persistent model with an improvement of 34%in the nRMSE.

关键词： Inter-hour forecast Direct normal irradiance Ground-based cloud images Multiple data types Multiple time-series

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Efficient 3D Scan Registration for Hand Modeling and Reconstruction

Efficient 3D Scan Registration for Hand Modeling and Reconst...

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第30届中国控制与决策会议

作者： Peilin Shen haikun wei Yangang Wang Southeast University Central Building

In this paper, we propose a new method for 3 D hand scan registration. This method includes two stages: liner blending skinning(LBS) and non-rigid ICP. A template hand mesh model is used to register to the 3 D hand scans, which have large pose and shape variations. To fit different types of 3 D hand scans, the template model is driven by the skeletons follow the principle of LBS to eliminate pose variations, and then non-rigid ICP is used to deform the template so that shape variations can be eliminated. Finally, template and scan model completely overlap together, and the vertices of template and scan can be matched one by one. We believe that the ability to align a template to each scan is the basis for more in-depth research in future. For example, this work can be used as basis for training pose and shape parameters. With the help of these parameters a template can be used to model any 3 D hand in real life just like SMPL[7] for human and SMAL[14] for animals.

关键词： Registration LBS Non-rigid ICP

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Genetic Algorithm-based Location and Control Strategy of Grid-connected BESS

Genetic Algorithm-based Location and Control Strategy of Gri...

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第40届中国控制会议

作者： Jilong Zhuang Jian Ge Kanjian Zhang haikun wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of AutomationSoutheast University

With the development of energy storage technology, more and more battery energy storage stations（BESSs） are connected to the power grid to restrain fluctuation and intermittency of renewable energy generation on the stability of the power grid. However, the connection with BESS will change the topology and power flow direction of the power grid. Therefore, based on the actual geographical wiring diagram and related data, this paper describes a grid model to analyze the influence of BESS connected to the power grid on power flow and node voltage. When the voltage of each node is stable, the genetic algorithm is applied to study how to select the access position and control the power of centralized or distributed BESSs to minimize the active power loss of the power grid. It provides guidance and reference for future location planning and control strategy of BESSs in the power grid.

关键词： Battery Energy Storage Station Power Flow Calculation Optimization

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A Classification Method of Photovoltaic Modules Shaded Area Based on weighted K-nn

A Classification Method of Photovoltaic Modules Shaded Area ...

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第40届中国控制会议

作者： Lin Xia Chenxi Li Kanjian Zhang haikun wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

In the actual operation of photovoltaic power stations,various types of shading,including leaves,bird’s droppings,and clouds,will inevitably *** shadings will affect the output power of the *** them,if a small area of shading is not removed in time,hot spots may be formed,accelerating the aging of photovoltaic modules,and not conducive to the healthy and stable operation of the overall ***,different shading objects cover different shading areas of photovoltaic modules,which cause different *** paper mainly analyzes the influence of different areas of shading on the current-voltage curve of photovoltaic modules,and proposes a classification algorithm based on weighted K-nn to classify the shading area according to the current-voltage curve characteristics of the module,which is helpful for subsequent identification of shading types and troubleshooting.

关键词： Photovoltaic Modules Shading Area K-Nearest Neighbor Classification

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Epileptic Seizure Prediction in Scalp EEG Using an Improved HIVE-COTE Model

Epileptic Seizure Prediction in Scalp EEG Using an Improved ...

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第三十九届中国控制会议

作者： Peizhen Peng haikun wei Liping Xie Yang Song Key Laboratory of Measurement and Control of CSE Ministry of EducationSchool of AutomationSoutheast University State Grid Nanjing Power Supply Company

Epileptic seizures occur as a result of a disorder of brain waves. In this study, we aim at a patient-specific model for predicting the risk of seizure paroxysm by extracting the in-depth features from continuous scalp electroencephalographic（EEG）signals. Unfortunately, the false warning rates of generalized regression prediction algorithms are relatively high on account of the complexity of the cerebral time series. Hence we set the seizure forecast problem as a time series classification（TSC）problem and a cutting-edge TSC algorithm:the Hierarchical Vote Collective of Transformation-based Ensembles（HIVE-COTE）is introduced to address the issue at the first time. In addition, we improve the structure of HIVE-COTE using a channel selection module. With the improved HIVE-COTE model, an oncoming seizure could be detected by a collective of machine-learning classifiers that identify the accurate pattern（inter-ictal or pre-ictal） of the cerebral signals. Based on 15 patients in CHB-MIT dataset, the proposed improved HIVE-COTE model achieves a sensitivity of 87.4%, an AUC of 0.859, which is a promising result. Our work significantly outperform a random predictor and other TSC algorithms.

关键词： Time Series Classification HIVE-COTE Machine Learning Scalp EEG Seizure prediction

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Sensitivity Analysis of Optimal Control Problems for Switched Systems

Sensitivity Analysis of Optimal Control Problems for Switche...

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第26届中国控制与决策会议

作者： Jinjin Liu Kanjian Zhang Xiaomei Liu haikun wei School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University

ISBN: (纸本)9781479937097

This paper investigates the problem of sensitivity analysis for switched autonomous systems involving uncertain parameters. The aim is to find switching instants which minimizes the cost function, and meanwhile makes it robust to the variation of the original objective with respect to unknown parameters. We focus on the fixed switching mode sequences and convert the sensitivity problem into a conventional optimal switched control problem, which can be solved directly using the gradient descent algorithm. The efficacy of the proposed method is illustrated via numerical example.

关键词： Switched systems Sensitivity analysis Optimal control Parameter variation

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A Tree-based Clear Sky Model for DNI Forecasting

A Tree-based Clear Sky Model for DNI Forecasting

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第30届中国控制与决策会议

作者： Yu Shen haikun wei Xin Zhao Tingting Zhu Kanjian Zhang Key Laboratory of Measurement and Control of CSE Ministry of EducationSchool of Automation Southeast University

Solar irradiance is a renewable energy that has been utilized by power plants. Direct normal irradiance（DNI）forecasting is a crucial approach to reduce the output uncertainty of solar power plants, and enhance reliability of power grids. According to statistics, the solar radiation of clear sky accounts for more than half of the total amount of radiation in a year. Hence, clear sky DNI forecasting models play a significant role in solar power systems. The existing clear sky models assume that the atmosphere is at rest and ignore the variation of aerosol optical depth in a day, which may reduce the accuracy of DNI forecasting. In this paper, a novel tree-based piecewise clear sky model is proposed to capture aerosol extinction coefficient varying with time in a day and forecast DNI when clouds are absent. Firstly, a linear model is deduced from a physical equation to represent the relationship of air mass and DNI approximately. Then, model trees with this linear mode at each leaf node are create. The database of the National Renewable Energy Laboratory（NREL）is used for experiments to evaluate the performance of the proposed model, compared with other clear sky models. The results of the experiments show that the proposed model provides more accurate forecast of DNI than other clear sky models.

关键词： Direct Normal Irradiance Clear Sky Model Model Tree Piecewise Linear Model

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Delay-dependent H∞ Control for Lurie Type Singular Time-delay Systems

Delay-dependent H∞ Control for Lurie Type Singular Time-del...

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第26届中国控制与决策会议

作者： Xiaomei Liu Kanjian Zhang Shengtao Li Shumin Fei haikun wei Key Laboratory of Measurement and Control of CSE(School of Automation Southeast University)Ministry of Education School of Information Science & Engineering Shandong Normal University

In this paper,the design of delay-dependent H controller for a class of singular Lurie systems with state-delay is ***-dependent sufficient condition is obtained in terms of matrix inequalities to ensure the resultant closed-loop system regularity,free of impulses,global uniform asymptotically stable and a prescribed ***,an LMI based state feedback H control law is developed to guarantee robust stability for the resulting closed-loop *** example demonstrates that the proposed method is effective.

关键词： Lurie systems singular systems with state-delay H∞ control linear matrix inequalities(LMIs)

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电力储能用锂离子电池状态评估研究进展

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电源技术 2022年第3期46卷 230-232页

作者：王德顺薛金花鲁千姿魏海坤中国电力科学研究院有限公司江苏南京210009 东南大学自动化学院江苏南京210096

锂离子电池的状态评估对其充放电策略、运维管理和安全预警等都至关重要。已有文献研究主要聚焦在单体电池的状态评估,电力储能用大规模锂离子电池的装机规模和传输数据量巨大,目前研究成果相对较少。将锂离子电池的SOC和SOH状态评估方... 详细信息

锂离子电池的状态评估对其充放电策略、运维管理和安全预警等都至关重要。已有文献研究主要聚焦在单体电池的状态评估,电力储能用大规模锂离子电池的装机规模和传输数据量巨大,目前研究成果相对较少。将锂离子电池的SOC和SOH状态评估方法归纳为数学解析法、电化学模型法、等效电路法和数据驱动法,其中数据驱动法是电池状态评估研究的发展方向;进一步地,从特征选取方法、数据挖掘方法2个角度分析了电力储能用锂离子电池系统的一致性评估,前者主要采用统计学方法、数据变换法和自动提取法,后者主要采用回归方法和聚类方法,从大规模、高维度的海量复杂数据中挖掘有效的特征信息,实现电力储能用锂离子电池的状态评估。

关键词：大规模储能电池状态机器学习数据驱动聚类分析

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维普期刊数据库

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基于误差函数的自然梯度法及其在MLP学习中的应用

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东南大学学报（自然科学版） 2011年第B9期41卷 152-155页

作者：李伟令魏海坤张侃健东南大学自动化学院南京210096

在激活函数选为误差函数的条件下,给出了求Fisher信息矩阵逆的算法,并进行仿真验证.首先将自然梯度法应用于多层感知器学习中,并与BP(back-propagation)算法进行了比较,说明了自然梯度法能够加快学习速度,并且可能避免学习中出现平坦区... 详细信息

在激活函数选为误差函数的条件下,给出了求Fisher信息矩阵逆的算法,并进行仿真验证.首先将自然梯度法应用于多层感知器学习中,并与BP(back-propagation)算法进行了比较,说明了自然梯度法能够加快学习速度,并且可能避免学习中出现平坦区现象,即使出现平坦区,也不会很严重.仿真验证了自然梯度法上述良好的学习性能,并且它渐近的逼近Cramer-Rao下界,从而验证了自然梯度学习是Fisher优效的,而通常的梯度法则不是Fisher优效的.另外,仿真也证实了自然梯度对训练样本中存在的噪声具有很好的鲁棒性.

关键词：自然梯度法多层感知器 Fisher信息矩阵 Fisher优效 Cramer.Rao不等式

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