Characterizing Solar PV Output Variability and Effects on the Electric System in Florida, Initial Results

Author(s):  
Rick Meeker ◽  
Alexander Domijan ◽  
Mujahidul Islam ◽  
Adedamola Omole ◽  
Arif Islam ◽  
...  

This paper shares initial results from a major collaborative project in Florida underway to study and address effects of high penetration levels of solar photovoltaic (PV) generation on the electric power system. The effort includes characterizing the variability of the solar resource in Florida, where a number of new multi-megawatt solar projects have either recently come online or are in the planning or construction stages (including the largest solar PV generating station in N. America at the time of this writing). Until now, most work on characterizing solar variability has focused on the Southwestern U.S. This paper shares initial results and insights on the variability of Solar PV generation output in Florida on different timescales and provides some preliminary insights into the implications and effects of the variability on the successful integration of increasingly higher penetration levels of solar PV, with respect to the integration technology, control systems, and the electric power system.

2012 ◽  
Vol 182-183 ◽  
pp. 768-772
Author(s):  
Jian Min Wang ◽  
Wen Yu Yan

GIS is getting more attention in the application of electric power system. This article mainly focuses on the electric GIS system based on the practical need in the electric system. This electric GIS system is composed of three subsidiary systems, among which PDA may transfer data collected by the inspectors to GIS general management and control system through GPRS, design the Geodatabase and system functional modules which accessed by multiple users simultaneously with C/S model, to achieve the automation in the information sharing and collaborative work.


Author(s):  
Le Zan'

Work provide a method for modelling and identificate parameters of electrical load to control the status of electric power system with actively adaptive networks.


2018 ◽  
Vol 138 (6) ◽  
pp. 412-415 ◽  
Author(s):  
Ryo Maeda ◽  
Takeshi Fukuoka ◽  
Yasutoshi Yoshioka ◽  
Atsushi Harada

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