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Voltage/VAR Control and Optimization: AI approachстатья
- Авторы: Tomin N., Kurbatsky V., Panasetsky D., Sidorov D., Zhukov A.
- Журнал: IFAC-PapersOnLine
- Том: 51
- Номер: 28
- Год издания: 2018
- Издательство: Elsevier Ltd
- Местоположение издательства: London
- DOI: 10.1016/j.ifacol.2018.11.685
- Аннотация: Volt-VAr control systems provide the optimal solution with remote automatic or manual control of the capacitor banks and tap positions on the voltage regulators. However, such control possesses inherent characteristics of complexity, nonlinearity, inaccuracy and high requirement for control speed, parts of which are hard to be described by the traditional models or to be realized by routine control methods. The artificial intelligence (AI) techniques have intelligence feature which traditional method does not bear, so special attentions are paid to the application of AI techniques in reactive voltage control and a lot of results in this field are obtained by many authors. This paper presents a hybrid Volt/VAr control approach based on AI techniques such as machine learning and multi-agent systems based models. Proposed approach enjoys high efficiency for various scenarios of modified IEEE 6-Bus and 118-Bus test systems.
- Добавил в систему: Сидоров Денис Николаевич