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Supervisory control and data acquisition for Standalone Hybrid Power Generation Systems

Authors
Lee, J.Lee, S.Cho, H.Ham, K.S.Hong, J.
Issue Date
Dec-2018
Publisher
Elsevier Inc.
Keywords
SCADA (Supervisory Control and Data Acquisition) System; IEC61850; Standalone Hybrid Power Generation System; Wave-Offshore Wind; Power Generation System
Citation
Sustainable Computing: Informatics and Systems, v.20, pp.141 - 154
Journal Title
Sustainable Computing: Informatics and Systems
Volume
20
Start Page
141
End Page
154
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/7222
DOI
10.1016/j.suscom.2017.11.003
ISSN
2210-5379
Abstract
Recently, the development of renewable energy resources has increased significantly. In particular, hybrid power combines multiple renewable resources and the next generation of systems with diverse micro-controllers and sensors has become a common trend. Since the hybrid electric power generation systems are usually located remotely and have various micro-controllers and sensors to be acquired and processed, a SCADA (supervisory control and data acquisition) system is required to monitor them remotely and control the data from the various sensors. The SCADA system collects data from distributed sensors to provide real time information for controlling micro-controllers of single or multiple turbines.In this paper, we present the design and implementation of the SCADA which is an integral part of energy operation for a standalone offshore wave-wind hybrid power generation system. The hybrid power generation system has four 2. MW-class wind turbines and twenty-four 100. KW-class wave force generators. The SCADA system is designed based on IEC61850 which is an international standard for vendor-agnostic engineering of the configuration of Intelligent Electronic Devices for electrical substation automation systems for communicating with each generator. We also show that the designed SCADA system is executed properly according to the command of the transmission system's operator in a simulation-based testing environment. © 2017 Elsevier Inc.
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