Open source SCADA systems for small renewable power generation

Aghenta, Lawrence Oriaghe (2020) Open source SCADA systems for small renewable power generation. Masters thesis, Memorial University of Newfoundland.

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Low cost monitoring and control is essential for small renewable power systems. While large renewable power systems can use existing commercial technology for monitoring and control, that is not cost-effective for small renewable generation. Such small assets require cost-effective, flexible, secure, and reliable real-time coordinated data monitoring and control systems. Supervisory control and data acquisition (SCADA) is the perfect technology for this task. The available commercial SCADA solutions are mostly pricey and economically unjustifiable for smaller applications. They also pose interoperability issues with the existing components which are often from multiple vendors. Therefore, an open source SCADA system represents the most flexible and the most cost-effective SCADA solution. This thesis has been done in two phases. The first phase demonstrates the design and dynamic simulation of a small hybrid power system with a renewable power generation system as a case study. In the second phase, after an extensive study of the proven commercial SCADA solutions and some open source SCADA packages, three different secure, reliable, low-cost open source SCADA options are developed using the most recent SCADA architecture, the Internet of Things. The implemented prototypes of the three open source SCADA systems were tested extensively with a small renewable power system (a solar PV system). The results show that the developed open source SCADA systems perform optimally and accurately, and could serve as viable options for smaller applications such as renewable generation that cannot afford commercial SCADA solutions.

Item Type: Thesis (Masters)
Item ID: 14333
Additional Information: Includes bibliographical references.
Keywords: Open Source SCADA, Instrumentation and Control, Renewable Energy Systems, Internet of Things, Thinger.IO
Department(s): Engineering and Applied Science, Faculty of
Date: May 2020
Date Type: Submission
Digital Object Identifier (DOI):
Library of Congress Subject Heading: Supervisory control systems; Electric power systems--Control; Small power production facilities--Equipment and supplies; Renewable energy sources--Equipment and supplies.

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