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CPS: Synergy: Image Modeling and Machine Learning Algorithms for Utility-Scale Solar Panel Monitoring

CPS: Synergy: Image Modeling and Machine Learning Algorithms for Utility-Scale Solar Panel Monitoring
CPS:协同:用于公用事业规模太阳能电池板监控的图像建模和机器学习算法
批准号:
1646542
负责人:
Andreas Spanias
金额:
$60.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-10-01 至 2021-09-30

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中文摘要
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英文摘要
The aim of this collaborative project is to increase the efficiency of utility scale solar arrays using sensors, machine learning and signal processing methods to detect faults and optimize power. New cyber-computing strategies, that rely on sensor data and imaging methods to predict solar panel shading, are used to improve efficiency. A programmable 18kW testbed that consists of 104 panels equipped with sensors, actuators and cameras is used to validate all theoretical results and test new approaches for using solar analytics to optimize power generation. Machine learning and dynamic image modeling algorithms are used to control each individual panel and change connection topologies to optimize power for different cloud, load, and fault conditions.Outcomes of the CPS project include advances in: a) cloud movement modeling and shading prediction using computer vision algorithms, b) PV fault detection and optimization methods that will switch array topologies dynamically while limiting PV inverter transients, d) experimental (testbed) validation of all array monitoring methods, and e) secure wireless sensor and data fusion. Theoretical and experimental research which enables real-time analytics and remote connection topology control may influence PV array standards and smart grid initiatives. The project tasks also include: education activities, outreach at high schools, and engagement with several organizations including minority and HBCU institutions to enhance diversity.
期刊论文(2)
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会议论文
DOI: 10.1109/iisa.2017.8316458
发表时间: 2017-08
期刊: 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA)
影响因子: --
作者: [Sunil Rao;Sameeksha Katoch;P. Turaga;A. Spanias;C. Tepedelenlioğlu;R. Ayyanar;Henry Braun;Jongmin Lee;U. Shanthamallu;M. Banavar;Devarajan Srinivasan]
通讯作者: Sunil Rao;Sameeksha Katoch;P. Turaga;A. Spanias;C. Tepedelenlioğlu;R. Ayyanar;Henry Braun;Jongmin Lee;U. Shanthamallu;M. Banavar;Devarajan Srinivasan
Solar energy management as an Internet of Things (IoT) application
作为物联网 (IoT) 应用的太阳能管理
DOI: 10.1109/iisa.2017.8316460
发表时间: 2017
期刊: Systems & Applications (IISA
影响因子: --
作者: [Spanias, Andreas S.]
通讯作者: Spanias, Andreas S.
REU Site: Quantum Machine Learning Algorithm Design and Implementation
  • 批准号:
    2349567
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.79万
  • 财政年份:
    2024
  • 负责人:
    Andreas Spanias
  • 依托单位:
Quantum Machine Learning Online Materials and Software Modules for Undergraduate Education
  • 批准号:
    2215998
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2022
  • 负责人:
    Andreas Spanias
  • 依托单位:
MRI: Development of a Sensors and Machine Learning Instrument Suite for Solar Array Monitoring
  • 批准号:
    2019068
  • 项目类别:
    Standard Grant
  • 资助金额:
    $34.99万
  • 财政年份:
    2020
  • 负责人:
    Andreas Spanias
  • 依托单位:
RET Site: Sensor, Signal and Information Processing Algorithms and Software
  • 批准号:
    1953745
  • 项目类别:
    Standard Grant
  • 资助金额:
    $56.0万
  • 财政年份:
    2020
  • 负责人:
    Andreas Spanias
  • 依托单位:
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