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Open AccessArticle

Impacts of Responsive Loads and Energy Storage System on Frequency Response of a Multi-Machine Power System

1
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea
2
Department of Electrical Engineering, Balochistan University of Engineering and Technology, Khuzdar 89100, Pakistan
*
Author to whom correspondence should be addressed.
Machines 2019, 7(2), 34; https://doi.org/10.3390/machines7020034
Received: 27 February 2019 / Revised: 17 May 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
In recent decades, the power grid’s configuration is shifting towards a smart grid where responsive loads and energy storage systems (ESS) are finding an increased role in the power system operation. In the presented work, a mathematical formulation for frequency response analysis of a multi-machine power system is developed, considering the individual and combined roles of ESS and responsive loads. The validity of the developed model is demonstrated with the help of multiple case studies, which consider the various configurations of the power system. Moreover, different combinations of capacities of generation units, ESS and responsive loads are also simulated. With the help of mathematical model and simulation results, it is demonstrated that ESS and responsive loads may improve the economy and performance of the power system even during the failure of a certain portion of generation capacity. Though the case studies consider non-reheat turbines only, the mathematical model and conclusions are equally valid for other types of turbines as well. View Full-Text
Keywords: energy storage system; frequency response; load frequency control; multi-machine power system; responsive loads energy storage system; frequency response; load frequency control; multi-machine power system; responsive loads
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Saeed Uz Zaman, M.; Haider, R.; Bukhari, S.B.A.; Ashraf, H.M.; Kim, C.-H. Impacts of Responsive Loads and Energy Storage System on Frequency Response of a Multi-Machine Power System. Machines 2019, 7, 34.

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