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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Vydané v:Electronics (Basel) Ročník 11; číslo 2; s. 247
Hlavní autori: Setiadi, Herlambang, Shah, Rakibuzzaman, Islam, Md Rabiul, Asfani, Dimas Anton, Nasution, Tigor Hamonangan, Abdillah, Muhammad, Megantoro, Prisma, Krismanto, Awan Uji
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.01.2022
Predmet:
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
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Shrnutí: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 affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics11020247