NDLI: Enhancing the reliability of a microgrid through optimal size of battery ESS

Content Provider	IET Digital Library
Author	Abdulgalil, Mohammed A. Khalid, Muhammad
Abstract	Reliability is one of the most important factors to judge a power system. So, assessing reliability is an important task in power system planning. Many techniques have been developed to enhance the reliability of a power system. Some of those techniques depend on integrating new components and other techniques depend on changing some characteristics of existing components. One of the techniques depending on integrating new components is to integrate an energy storage system (ESS) with a power system. If the ESS is optimally sized to minimise the investment and operating cost, it enhances the reliability of the power system with a notable difference. This paper illustrates how to optimally size an ESS to be integrated with a grid-connected microgrid using the mixed-integer linear programming method. Moreover, load uncertainty is considered and the optimisation problem is solved using two different approaches to optimally size the ESS. Reliability indices of the microgrid are calculated before integrating it with the ESS and after integrating it to illustrate the enhancement of the reliability indices. Simulation results depict the effectiveness of the proposed approach.
Starting Page	1499
Ending Page	1508
Page Count	10
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 9, May (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5335
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-02-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Assessing Reliability Battery ESS Distributed Power Generation Energy Storage Energy Storage System Integer Programming Linear Programming Optimal Size Optimally Size Optimisation Technique Power System Planning Reliability Indices
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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