An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be...

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Vydáno v:	Electronics (Basel) Ročník 11; číslo 2; s. 247
Hlavní autoři:	Setiadi, Herlambang, Shah, Rakibuzzaman, Islam, Md Rabiul, Asfani, Dimas Anton, Nasution, Tigor Hamonangan, Abdillah, Muhammad, Megantoro, Prisma, Krismanto, Awan Uji
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.01.2022
Témata:	Algorithms Alternative energy sources Artificial neural networks Controllers Electric power grids Energy storage Inertia Machine learning Optimization Power plants Renewable resources Synchronous machines Systems stability Wind power
ISSN:	2079-9292, 2079-9292
On-line přístup:	Získat plný text
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