A cyber-physical system approach for photovoltaic array monitoring and control

Author(s):  
S. Rao ◽  
S. Katoch ◽  
P. Turaga ◽  
A. Spanias ◽  
C. Tepedelenlioglu ◽  
...  
Author(s):  
Chao Liu ◽  
Pingyu Jiang

Social factory is served as the production node of social manufacturing communities/network to make manufacturing factories shift to the internet-based ones. The social factory aims to deal with fast-changing production requirements, sharing and competing of product orders, flexible resource configuration, ubiquitous interconnections, and real-time production monitoring and control. To achieve these visions, an extended cyber-physical system-enabled social factory model is proposed by integrating current cyber-physical system with machining equipment, social sensors, and smart workpieces. Within the proposed social factory model, the system framework and runtime logic are presented, and some core concepts such as extended cyber-physical system node, social sensor, and smart workpiece are clarified. Based on that, the social factory model is implemented by developing diverse extended cyber-physical system nodes and then connecting them with humans to form a collaborative production network where humans can access and control the machines anywhere and anytime. To validate the proposed social factory framework, a flexible production line in our lab is regarded as an extended cyber-physical system-enabled social factory to demonstrate the decentralized production interaction and cooperation.


Author(s):  
Gowtham Muniraju ◽  
Sunil Rao ◽  
Sameeksha Katoch ◽  
Andreas Spanias ◽  
Cihan Tepedelenlioglu ◽  
...  

A cyber physical system approach for a utility-scale photovoltaic (PV) array monitoring and control is presented in this article. This system consists of sensors that capture voltage, current, temperature, and irradiance parameters for each solar panel which are then used to detect, predict and control the performance of the array. More specifically the article describes a customized machine-learning method for remote fault detection and a computer vision framework for cloud movement prediction. In addition, a consensus-based distributed approach is proposed for resource optimization, and a secure authentication protocol that can detect intrusions and cyber threats is presented. The proposed system leverages video analysis of skyline imagery that is used along with other measured parameters to reconfigure the solar panel connection topology and optimize power output. Additional benefits of this cyber physical approach are associated with the control of inverter transients. Preliminary results demonstrate improved efficiency and robustness in renewable energy systems using advanced cyber enabled sensory analysis and fusion devices and algorithms.


2020 ◽  
pp. 786-807 ◽  
Author(s):  
Gowtham Muniraju ◽  
Sunil Rao ◽  
Sameeksha Katoch ◽  
Andreas Spanias ◽  
Cihan Tepedelenlioglu ◽  
...  

A cyber physical system approach for a utility-scale photovoltaic (PV) array monitoring and control is presented in this article. This system consists of sensors that capture voltage, current, temperature, and irradiance parameters for each solar panel which are then used to detect, predict and control the performance of the array. More specifically the article describes a customized machine-learning method for remote fault detection and a computer vision framework for cloud movement prediction. In addition, a consensus-based distributed approach is proposed for resource optimization, and a secure authentication protocol that can detect intrusions and cyber threats is presented. The proposed system leverages video analysis of skyline imagery that is used along with other measured parameters to reconfigure the solar panel connection topology and optimize power output. Additional benefits of this cyber physical approach are associated with the control of inverter transients. Preliminary results demonstrate improved efficiency and robustness in renewable energy systems using advanced cyber enabled sensory analysis and fusion devices and algorithms.


2020 ◽  
pp. 978-1000
Author(s):  
Gowtham Muniraju ◽  
Sunil Rao ◽  
Sameeksha Katoch ◽  
Andreas Spanias ◽  
Cihan Tepedelenlioglu ◽  
...  

A cyber physical system approach for a utility-scale photovoltaic (PV) array monitoring and control is presented in this article. This system consists of sensors that capture voltage, current, temperature, and irradiance parameters for each solar panel which are then used to detect, predict and control the performance of the array. More specifically the article describes a customized machine-learning method for remote fault detection and a computer vision framework for cloud movement prediction. In addition, a consensus-based distributed approach is proposed for resource optimization, and a secure authentication protocol that can detect intrusions and cyber threats is presented. The proposed system leverages video analysis of skyline imagery that is used along with other measured parameters to reconfigure the solar panel connection topology and optimize power output. Additional benefits of this cyber physical approach are associated with the control of inverter transients. Preliminary results demonstrate improved efficiency and robustness in renewable energy systems using advanced cyber enabled sensory analysis and fusion devices and algorithms.


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