Sizing of Hybrid Power System with varying current type using numerical probabilistic approach

Power Pinch Analysis is an established method to target the design parameter of a Hybrid Power System. This study aims to develop an extended tool known as Probability-Power Pinch Analysis (P-PoPA) using probability theory to simplify the process of Power Pinch Analysis in considering efficiency los...

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Bibliographic Details
Main Authors: Liu, W. H., Wan Alwi, S. R., Hashim, H., Lim, J. S., Mohammad Rozali, N. E., Ho, W. S.
Format: Article
Published: Elsevier Ltd 2016
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Online Access:http://eprints.utm.my/id/eprint/71516/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84998772611&doi=10.1016%2fj.apenergy.2016.06.035&partnerID=40&md5=c91dcdac8ae7cd70385bfbd0b305ae92
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Institution: Universiti Teknologi Malaysia
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Summary:Power Pinch Analysis is an established method to target the design parameter of a Hybrid Power System. This study aims to develop an extended tool known as Probability-Power Pinch Analysis (P-PoPA) using probability theory to simplify the process of Power Pinch Analysis in considering efficiency losses. The method targets for a Hybrid Power System with various current type from generation to demand, generation to storage, or storage to demand. The procedure of the method is illustrated using an electricity-deficit scenario where both AC–DC generation and AC–DC demand are present. The new methodology which adapts the same concept as the Stand-Alone Hybrid System Power Pinch Analysis utilizes data extracted from an ideal (considering no efficiency losses) graphical Power Pinch Analysis and Power Cascade Table and multiplying the extracted data with a probability factor to obtain an estimated target (considering efficiency losses) for the power system. In this study, three design parameters are determined for a system with 208 kW h AC source and 50 kW h DC source and 170 kW h AC demand and 98 kW h DC demand. The external energy that is needed for the system is identified as 38.93 kW h and the energy capacity of energy storage is 42.20 kW h and power capacity of energy storage is 8.79 kW. The result is then compared with the existing cascade analysis, Power Cascade Table and Storage Cascade Table. The determined sizing values have a close estimation to that from cascading analysis (considering efficiency losses), with a maximum percentage difference of 2.3%.