Using adaptive fuzzy inference system for voltage ranking
Lo, K.L. and Meng, Z. (2004) Using adaptive fuzzy inference system for voltage ranking. IEE Proceedings Generation Transmission and Distribution, 151 (2). pp. 183-191. ISSN 1350-2360
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Voltage ranking is an important part of power system security assessment. The commonly used performance index method with a low exponent could suffer from masking effects. This paper proposes a generic compensation factor to reduce the masking problem. An adaptive fuzzy system is used for the calculation of the generic compensation factor. A simplification of the defuzzification process is proposed for improvement of computational efficiency. Convergence analysis shows that values calculated by the adaptive fuzzy system are good approximations. The parameters would only need to be calculated offline once. They can then be applied to various systems for voltage ranking applications. To save computational efforts further, a hybrid strategy is introduced to reduce the number of fuzzy rules. A good ranking method needs an efficient method to derive voltage deviations. Besides the commonly used 1P-1Q calculation method, an alternative method is used for the calculation of voltage deviations. A new version of the ranking assessment diagram is proposed for the presentation of ranking results. Ranking results from two test power systems have been presented to verify the effectiveness of the proposed strategy.
| Author(s): | Lo, K.L. and Meng, Z. | Item type: | Article |
|---|---|
| ID code: | 3495 |
| Keywords: | adaptive systems, fuzzy systems, inference mechanisms, performance index, power system planning, power system security, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering |
| Subjects: | Technology > Electrical engineering. Electronics Nuclear engineering |
| Department: | Faculty of Engineering > Electronic and Electrical Engineering Unknown Department |
| Depositing user: | Strathprints Administrator |
| Date deposited: | 20 Jun 2007 |
| Last modified: | 08 Nov 2019 05:34 |
| URI: | https://strathprints.strath.ac.uk/id/eprint/3495 |
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