Spatio-Temporal Data Analytics for Wind Energy Integration

2014 ◽  
Author(s):  
Lei Yang ◽  
Miao He ◽  
Junshan Zhang ◽  
Vijay Vittal
Keyword(s):  
Wind Energy ◽  
Data Analytics ◽  
Temporal Data ◽  
Energy Integration ◽  
Wind Energy Integration ◽  
Spatio Temporal

Impact of Wind Energy Integration in a Distribution Electric Network

2005 ◽  
Vol 1 (03) ◽  
pp. 93-98
Author(s):  
V. Rogez ◽  
◽  
H. Roisse ◽  
V. Autier ◽  
X. Guillaud
Keyword(s):  
Wind Energy ◽  
Energy Integration ◽  
Electric Network ◽  
Wind Energy Integration

scholarly journals A robust composite wide area control of a DFIG wind energy system for damping inter-area oscillations

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ayyarao S. L. V. Tummala
Keyword(s):  
Wind Energy ◽  
Sliding Mode ◽  
Energy System ◽  
Wide Area ◽  
Continuous Control ◽  
Energy Integration ◽  
Wind Energy System ◽  
Wind Energy Integration ◽  
Twisting Algorithm ◽  
Wide Area Control

AbstractThis paper presents a novel composite wide area control of a DFIG wind energy system which combines the Robust Exact Differentiator (RED) and Discontinuous Integral (DI) control to damp out inter-area oscillations. RED generates the real-time differentiation of a relative speed signal in a noisy environment while DI control, an extension to a twisting algorithm and PID control, develops a continuous control signal and hence reduces chattering. The proposed control is robust to disturbances and can enhance the overall stability of the system. The proposed composite sliding mode control is evaluated using a modified benchmark two-area power system model with wind energy integration. Simulation results under various operating scenarios show the efficacy of the proposed approach.

Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection Using WINS

2011 ◽  
Vol 24 (8) ◽  
pp. 71-87 ◽  
Author(s):  
Wei Tian ◽  
Mohammad Shahidehpour ◽  
Zuyi Li
Keyword(s):  
Wind Energy ◽  
Large Scale ◽  
Energy Integration ◽  
Wind Energy Integration

scholarly journals A Survey on Spatio-temporal Data Analytics Systems

2022 ◽  
Author(s):  
Md Mahbub Alam ◽  
Luis Torgo ◽  
Albert Bifet
Keyword(s):  
Programming Languages ◽  
Spatial Data ◽  
Data Analytics ◽  
Spatial Databases ◽  
Location Based Services ◽  
Temporal Data ◽  
Wide Range ◽  
Data Volume ◽  
Spatio Temporal ◽  
Gis Software

Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and spatio-temporal data analytics in the past decade. The main goal of existing works was to develop algorithms and technologies to capture, store, manage, analyze, and visualize spatial or spatio-temporal data. The researchers have contributed either by adding spatio-temporal support with existing systems, by developing a new system from scratch, or by implementing algorithms for processing spatio-temporal data. The existing ecosystem of spatial and spatio-temporal data analytics systems can be categorized into three groups, (1) spatial databases (SQL and NoSQL), (2) big spatial data processing infrastructures, and (3) programming languages and GIS software. Since existing surveys mostly investigated infrastructures for processing big spatial data, this survey has explored the whole ecosystem of spatial and spatio-temporal analytics. This survey also portrays the importance and future of spatial and spatio-temporal data analytics.

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