Power and Energy

Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink


The dataset contains fundamental approaches regarding modeling individual photovoltaic (PV) solar cells, panels and combines into array and how to use experimental test data as typical curves to generate a mathematical model for a PV solar panel or array.

 

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Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Wed, 03/28/2018 - 10:52
DOI:
10.21227/H2463S
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[1] , "Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2463S. Accessed: Apr. 23, 2018.
@data{h2463s-17,
doi = {10.21227/H2463S},
url = {http://dx.doi.org/10.21227/H2463S},
author = { },
publisher = {IEEE Dataport},
title = {Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink},
year = {2017} }
TY - DATA
T1 - Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2463S
ER -
. (2017). Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink. IEEE Dataport. http://dx.doi.org/10.21227/H2463S
, 2017. Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink. Available at: http://dx.doi.org/10.21227/H2463S.
. (2017). "Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink." Web.
1. . Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2463S
. "Modeling and Simulation of Photovoltaic Arrays in Matlab and Simulink." doi: 10.21227/H2463S

Study on Three-Phase Photovoltaic Systems under Grid Faults


The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.

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Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Wed, 03/28/2018 - 10:53
DOI:
10.21227/H25633
Data Format:
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[1] , "Study on Three-Phase Photovoltaic Systems under Grid Faults", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H25633. Accessed: Apr. 23, 2018.
@data{h25633-17,
doi = {10.21227/H25633},
url = {http://dx.doi.org/10.21227/H25633},
author = { },
publisher = {IEEE Dataport},
title = {Study on Three-Phase Photovoltaic Systems under Grid Faults},
year = {2017} }
TY - DATA
T1 - Study on Three-Phase Photovoltaic Systems under Grid Faults
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H25633
ER -
. (2017). Study on Three-Phase Photovoltaic Systems under Grid Faults. IEEE Dataport. http://dx.doi.org/10.21227/H25633
, 2017. Study on Three-Phase Photovoltaic Systems under Grid Faults. Available at: http://dx.doi.org/10.21227/H25633.
. (2017). "Study on Three-Phase Photovoltaic Systems under Grid Faults." Web.
1. . Study on Three-Phase Photovoltaic Systems under Grid Faults [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H25633
. "Study on Three-Phase Photovoltaic Systems under Grid Faults." doi: 10.21227/H25633

Real-life Power Quality Sags


The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.

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Dataset Details

Citation Author(s):
Submitted by:
Juan Jose Gonza...
Last updated:
Wed, 03/28/2018 - 10:54
DOI:
10.21227/H2K88D
Data Format:
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[1] , "Real-life Power Quality Sags ", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2K88D. Accessed: Apr. 23, 2018.
@data{h2k88d-17,
doi = {10.21227/H2K88D},
url = {http://dx.doi.org/10.21227/H2K88D},
author = { },
publisher = {IEEE Dataport},
title = {Real-life Power Quality Sags },
year = {2017} }
TY - DATA
T1 - Real-life Power Quality Sags
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2K88D
ER -
. (2017). Real-life Power Quality Sags . IEEE Dataport. http://dx.doi.org/10.21227/H2K88D
, 2017. Real-life Power Quality Sags . Available at: http://dx.doi.org/10.21227/H2K88D.
. (2017). "Real-life Power Quality Sags ." Web.
1. . Real-life Power Quality Sags [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2K88D
. "Real-life Power Quality Sags ." doi: 10.21227/H2K88D

A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing


Cloud computing is a technique proposed based on the distribution of processing and storage resources across various multiple servers. The user can easily access the services and applications of cloud at any location and moment in this infrastructure. Although these capabilities have made the cloud services more flexible and available, issues such as scheduling and load balancing for optimal use of resources, have always been the main challenges in this infrastructure.

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Dataset Details

Citation Author(s):
Submitted by:
Nawzad Al-Salihi
Last updated:
Wed, 04/18/2018 - 07:25
DOI:
10.21227/H2G95P
Data Format:
 
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[1] , "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2G95P. Accessed: Apr. 23, 2018.
@data{h2g95p-18,
doi = {10.21227/H2G95P},
url = {http://dx.doi.org/10.21227/H2G95P},
author = { },
publisher = {IEEE Dataport},
title = {A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing},
year = {2018} }
TY - DATA
T1 - A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2G95P
ER -
. (2018). A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing. IEEE Dataport. http://dx.doi.org/10.21227/H2G95P
, 2018. A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing. Available at: http://dx.doi.org/10.21227/H2G95P.
. (2018). "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing." Web.
1. . A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2G95P
. "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing." doi: 10.21227/H2G95P

Optimized Power Source Integration (OPSI)


Research on Optimizing the Integration of Renewable Energy Sources into the Electrical Power Systems

In this project one model the photovoltaic and wind power sources in order to analyze how to optimally integrate them in the electrical power systems. Integration requirements like transient regimes associated with fault occurrence, identification of the electrical power systems responsible for disturbances, and optimization of the integration are focus points of the research.

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Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Thu, 03/15/2018 - 19:06
DOI:
10.21227/H2D66D
Data Format:
Links:
 
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[1] , "Optimized Power Source Integration (OPSI)", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2D66D. Accessed: Apr. 23, 2018.
@data{h2d66d-18,
doi = {10.21227/H2D66D},
url = {http://dx.doi.org/10.21227/H2D66D},
author = { },
publisher = {IEEE Dataport},
title = {Optimized Power Source Integration (OPSI)},
year = {2018} }
TY - DATA
T1 - Optimized Power Source Integration (OPSI)
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2D66D
ER -
. (2018). Optimized Power Source Integration (OPSI). IEEE Dataport. http://dx.doi.org/10.21227/H2D66D
, 2018. Optimized Power Source Integration (OPSI). Available at: http://dx.doi.org/10.21227/H2D66D.
. (2018). "Optimized Power Source Integration (OPSI)." Web.
1. . Optimized Power Source Integration (OPSI) [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2D66D
. "Optimized Power Source Integration (OPSI)." doi: 10.21227/H2D66D

joint filter approach reliable power system state estimation


This is the Smulation Data for Power System State Estimation.

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Dataset Details

Citation Author(s):
Submitted by:
Yang Yu
Last updated:
Fri, 03/09/2018 - 08:23
DOI:
10.21227/H2M634
Data Format:
 
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[1] , "joint filter approach reliable power system state estimation", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2M634. Accessed: Apr. 23, 2018.
@data{h2m634-17,
doi = {10.21227/H2M634},
url = {http://dx.doi.org/10.21227/H2M634},
author = { },
publisher = {IEEE Dataport},
title = {joint filter approach reliable power system state estimation},
year = {2017} }
TY - DATA
T1 - joint filter approach reliable power system state estimation
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2M634
ER -
. (2017). joint filter approach reliable power system state estimation. IEEE Dataport. http://dx.doi.org/10.21227/H2M634
, 2017. joint filter approach reliable power system state estimation. Available at: http://dx.doi.org/10.21227/H2M634.
. (2017). "joint filter approach reliable power system state estimation." Web.
1. . joint filter approach reliable power system state estimation [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2M634
. "joint filter approach reliable power system state estimation." doi: 10.21227/H2M634

Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems


This dataset contains the numerical results and Excel graphing used to create the results images in the main paper.

 

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Dataset Details

Citation Author(s):
Submitted by:
Andrew Roscoe
Last updated:
Tue, 03/20/2018 - 09:21
DOI:
10.21227/H20926
Data Format:
Links:
 
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[1] , "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H20926. Accessed: Apr. 23, 2018.
@data{h20926-17,
doi = {10.21227/H20926},
url = {http://dx.doi.org/10.21227/H20926},
author = { },
publisher = {IEEE Dataport},
title = {Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems},
year = {2017} }
TY - DATA
T1 - Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H20926
ER -
. (2017). Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems. IEEE Dataport. http://dx.doi.org/10.21227/H20926
, 2017. Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems. Available at: http://dx.doi.org/10.21227/H20926.
. (2017). "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems." Web.
1. . Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H20926
. "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems." doi: 10.21227/H20926

Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms


Advances in Wireless Sensor Network Technology (WSN) have provided the availability of small and low-cost sensor with capability of sensing various types of physical and environmental conditions, data processing and wireless communication. In WSN, the sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are limited. Triple Umpiring System (TUS) has already been proved its better performance on Wireless Sensor Networks. Clustering technique provides an effective way to prolong the lifetime of WSN.

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No Data files have been uploaded.

Dataset Details

Citation Author(s):
Submitted by:
GANESH SUBRAMANIAN
Last updated:
Tue, 10/24/2017 - 01:17
DOI:
10.21227/H2VP81
Data Format:
Links:
 
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[1] , "Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2VP81. Accessed: Apr. 23, 2018.
@data{h2vp81-17,
doi = {10.21227/H2VP81},
url = {http://dx.doi.org/10.21227/H2VP81},
author = { },
publisher = {IEEE Dataport},
title = {Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms},
year = {2017} }
TY - DATA
T1 - Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2VP81
ER -
. (2017). Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms. IEEE Dataport. http://dx.doi.org/10.21227/H2VP81
, 2017. Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms. Available at: http://dx.doi.org/10.21227/H2VP81.
. (2017). "Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms." Web.
1. . Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2VP81
. "Efficient and Secure Routing Protocol for Wireless Sensor Networks through SNR based Dynamic Clustering Mechanisms." doi: 10.21227/H2VP81

Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink


This work presents a novel Anti-Islanding (AI) protection of Photovoltaic (PV) Systems based on monitoring the dc-link voltage of the PV inverter. A PV System equipped with AI protection like frequency relays, a rate of change of frequency (ROCOF) relay, and respectively the proposed dc-link voltage relay is simulated under the conditions of islanding and the detection time for all these AI techniques are compared. The study shows under which conditions our proposed dc-link voltage AI relay is the most efficient.

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Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Thu, 10/19/2017 - 10:36
DOI:
10.21227/H28W5P
Data Format:
Links:
 
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[1] , "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H28W5P. Accessed: Apr. 23, 2018.
@data{h28w5p-17,
doi = {10.21227/H28W5P},
url = {http://dx.doi.org/10.21227/H28W5P},
author = { },
publisher = {IEEE Dataport},
title = {Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink},
year = {2017} }
TY - DATA
T1 - Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H28W5P
ER -
. (2017). Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink. IEEE Dataport. http://dx.doi.org/10.21227/H28W5P
, 2017. Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink. Available at: http://dx.doi.org/10.21227/H28W5P.
. (2017). "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink." Web.
1. . Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H28W5P
. "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink." doi: 10.21227/H28W5P

A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems


This work presents a Matlab/Simulink study on anti-islanding detection algorithms for a 100kW Grid-Connected Photovoltaic (PV) Array. The main focus is on the islanding phenomenon that occurs at the Point of Common Coupling (PCC) between Grid-Connected PV System and the rest of the electric power system (EPS) during various grid fault conditions. The Grid-Connected PV System is simulated under the conditions of islanding, and anti-islanding (AI) relay reaction times are measured through the simulation.

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Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Thu, 10/19/2017 - 10:32
DOI:
10.21227/H2DP80
Data Format:
Links:
 
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[1] , "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2DP80. Accessed: Apr. 23, 2018.
@data{h2dp80-17,
doi = {10.21227/H2DP80},
url = {http://dx.doi.org/10.21227/H2DP80},
author = { },
publisher = {IEEE Dataport},
title = {A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems},
year = {2017} }
TY - DATA
T1 - A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2DP80
ER -
. (2017). A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems. IEEE Dataport. http://dx.doi.org/10.21227/H2DP80
, 2017. A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems. Available at: http://dx.doi.org/10.21227/H2DP80.
. (2017). "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems." Web.
1. . A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2DP80
. "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems." doi: 10.21227/H2DP80

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