| Full text | |
| Author(s): |
Pedrino, Emerson Carlos
[1]
;
Yamada, Thiago
[1]
;
Lunardi, Thiago Reginato
[2]
;
de Melo Vieira, Jr., Jose Carlos
[2]
Total Authors: 4
|
| Affiliation: | [1] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Sao Carlos Sch Engn, Dept Elect & Comp Engn, Sao Carlos, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | APPLIED SOFT COMPUTING; v. 74, p. 206-215, JAN 2019. |
| Web of Science Citations: | 1 |
| Abstract | |
This paper proposed a new method for detecting islanding of distributed generation (DG), using Multigene Genetic Programming (MGP). Islanding has been a serious concern among power distribution utilities and distributed generation owners, because it poses risks to the safety of utilities' workers and consumers, and can cause damage to power distribution systems' equipment. Therefore, a DG must be disconnected as soon as an islanding is detected. In addition, an islanding detection method must have high degree of dependability to correctly discriminate islanding from other events, such as load switching, in order to avoid unnecessary disconnection of the distributed generator. In this context, the novelty of the proposed method is that the MGP is capable of obtaining a set of mathematical and logic functions employed to detect and classify islanding correctly. This is a new approach among the computational intelligent methods proposed for DG islanding detection. The main idea was to use local voltage measurements as input of the method, eliminating the need of complex and expensive communication infrastructure. The method has been trained with several islanding and non-islanding cases, by using a power distribution system comprising five concentrated loads, a synchronous distributed generator and a wind power plant. The results showed that the proposed method was successful in differentiating the islanding events from other disturbances, revealing its great potential to be applied in anti-islanding protection schemes for distributed generation. (C) 2018 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 15/23297-4 - System for automatic hardware generation in FPGAs by Cartesian Genetic Programming |
| Grantee: | Emerson Carlos Pedrino |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 17/26421-3 - Investigation of the use of Intelligent Systems for Efficient Mapping of Applications in Many-Core Architectures |
| Grantee: | Emerson Carlos Pedrino |
| Support Opportunities: | Scholarships abroad - Research |