Power and Energy

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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:
Sat, 06/16/2018 - 23:01
DOI:
10.21227/H2463S
Data Format:
Links:
 
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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: Jun. 22, 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:
Sat, 06/16/2018 - 23:17
DOI:
10.21227/H25633
Data Format:
Links:
 
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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: Jun. 22, 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: Jun. 22, 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

RSSI-Based Indoor Localization with the Internet of Things


RSSI-Dataset

The RSSI-Dataset provides a comprehensive set of Received Signal Strength Indication (RSSI) readings from within two indoor office buildings. Four wireless technologies were used:

  • Zigbee (IEEE 802.15.4),
  • WiFi (IEEE 802. 11),
  • Bluetooth Low Energy (BLE) and
  • Long Range Area-Wide Network (LoRaWAN).

For experimentation Arduinos Raspberry Pi, XBees, Gimbal beacons Series 10 and Dragino LoRa Shield were also used.  

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Dataset Details

Citation Author(s):
Submitted by:
PETROS SPACHOS
Last updated:
Wed, 05/30/2018 - 20:51
DOI:
10.21227/H25D5X
Data Format:
Links:
 
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[1] , "RSSI-Based Indoor Localization with the Internet of Things", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H25D5X. Accessed: Jun. 22, 2018.
@data{h25d5x-18,
doi = {10.21227/H25D5X},
url = {http://dx.doi.org/10.21227/H25D5X},
author = { },
publisher = {IEEE Dataport},
title = {RSSI-Based Indoor Localization with the Internet of Things},
year = {2018} }
TY - DATA
T1 - RSSI-Based Indoor Localization with the Internet of Things
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H25D5X
ER -
. (2018). RSSI-Based Indoor Localization with the Internet of Things. IEEE Dataport. http://dx.doi.org/10.21227/H25D5X
, 2018. RSSI-Based Indoor Localization with the Internet of Things. Available at: http://dx.doi.org/10.21227/H25D5X.
. (2018). "RSSI-Based Indoor Localization with the Internet of Things." Web.
1. . RSSI-Based Indoor Localization with the Internet of Things [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H25D5X
. "RSSI-Based Indoor Localization with the Internet of Things." doi: 10.21227/H25D5X

data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU


These data are the input data of the simulation for the paper "Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU".

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Dataset Details

Citation Author(s):
Submitted by:
Ancheng Xue
Last updated:
Tue, 05/22/2018 - 03:19
DOI:
10.21227/H2V37S
Data Format:
 
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[1] , "data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2V37S. Accessed: Jun. 22, 2018.
@data{h2v37s-18,
doi = {10.21227/H2V37S},
url = {http://dx.doi.org/10.21227/H2V37S},
author = { },
publisher = {IEEE Dataport},
title = {data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU},
year = {2018} }
TY - DATA
T1 - data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2V37S
ER -
. (2018). data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU. IEEE Dataport. http://dx.doi.org/10.21227/H2V37S
, 2018. data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU. Available at: http://dx.doi.org/10.21227/H2V37S.
. (2018). "data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU." Web.
1. . data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2V37S
. "data of the paper_Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU." doi: 10.21227/H2V37S

The normalized wavelet package transform energy in each band for the grounding current of distribution network


This is the data for the grounding current of a radial structured distribution network, when subject to a single-phase earth fault.

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Dataset Details

Citation Author(s):
Submitted by:
Ning Tong
Last updated:
Mon, 05/21/2018 - 23:57
DOI:
10.21227/H2ZW9D
 
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[1] , "The normalized wavelet package transform energy in each band for the grounding current of distribution network", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2ZW9D. Accessed: Jun. 22, 2018.
@data{h2zw9d-18,
doi = {10.21227/H2ZW9D},
url = {http://dx.doi.org/10.21227/H2ZW9D},
author = { },
publisher = {IEEE Dataport},
title = {The normalized wavelet package transform energy in each band for the grounding current of distribution network},
year = {2018} }
TY - DATA
T1 - The normalized wavelet package transform energy in each band for the grounding current of distribution network
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2ZW9D
ER -
. (2018). The normalized wavelet package transform energy in each band for the grounding current of distribution network. IEEE Dataport. http://dx.doi.org/10.21227/H2ZW9D
, 2018. The normalized wavelet package transform energy in each band for the grounding current of distribution network. Available at: http://dx.doi.org/10.21227/H2ZW9D.
. (2018). "The normalized wavelet package transform energy in each band for the grounding current of distribution network." Web.
1. . The normalized wavelet package transform energy in each band for the grounding current of distribution network [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2ZW9D
. "The normalized wavelet package transform energy in each band for the grounding current of distribution network." doi: 10.21227/H2ZW9D

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: Jun. 22, 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.

Dataset Files

No Data files have been uploaded.

OPEN ACCESS Dataset Details

Citation Author(s):
Submitted by:
Ioan Banu
Last updated:
Sat, 06/16/2018 - 22:50
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: Jun. 22, 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: Jun. 22, 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: Jun. 22, 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

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