Challenging frequency control issues, such as the reliability and security of the power system, arise when increasing penetration levels of inverter-interfaced generation are imposed. As a result of the displacement of convention generation in favour of renewable energy sources, the reduction of frequency response capabilities can be seen. A promising method of overcoming the aforementioned challenges is to utilise Battery Energy Storage Systems (BESS), which provides frequency support by injecting instantaneous power to the grid and back up the conventional generation systems. However, large battery systems increase the cost while inadequate battery capacities result in poor performance. This paper, therefore, proposes an approach for finding the optimum BESS size for an islanded microgrid power system. The determination of the optimum BESS size is based on an existing case study, under which the most severe contingencies of generation loss and load loss have been accounted for, as well as different levels of penetration of renewable energy sources. As a result of using meta-heuristic optimization (Grey Wolf Optimization), the constraint optimization problem has been identified as BESS sizing. Through the use of real-time simulation DIgSILENT Power Factory software, estimated BESS size can be applied to a standalone microgrid to test the frequency of support capabilities. The simulation has made it apparent that through the selection of the optimum BESS size, the system frequency response is not only mitigated, but improved.

Item Type:	Refereed Article
Keywords:	battery energy storage, grey wolf optimisation, frequency response, renewable energy sources, stability, DigSIENT power factory
Research Division:	Engineering
Research Group:	Electrical engineering
Research Field:	Electrical engineering not elsewhere classified
Objective Division:	Energy
Objective Group:	Energy storage, distribution and supply
Objective Field:	Smart grids
UTAS Author:	El-Bidairi, KS (Mr Kutaiba El-Bidairi)
UTAS Author:	Nguyen, HD (Dr Hung Nguyen)
UTAS Author:	Mahmoud, TS (Dr Thair Mahmoud)
UTAS Author:	Jayasinghe, SDG (Dr Shantha Jayasinghe Arachchillage)
ID Code:	150848
Year Published:	2020
Web of Science® Times Cited:	56
Deposited By:	NC Maritime Engineering and Hydrodynamics
Deposited On:	2022-07-03
Last Modified:	2022-09-19
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