Explicit degradation modelling in optimal lead–acid battery use for photovoltaic systems

Lead–acid battery is a storage technology that is widely used in photovoltaic (PV) systems. Battery charging and discharging profiles have a direct impact on the battery degradation and battery loss of life. This study presents a new 2-model iterative approach for explicit modelling of battery degra...

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Bibliographic Details
Published in:IET generation, transmission & distribution Vol. 10; no. 4; pp. 1098 - 1106
Main Authors: Hamedi, Amir-Sina, Rajabi-Ghahnavieh, Abbas
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 10.03.2016
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ISSN:1751-8687, 1751-8695
Online Access:Get full text
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Summary:Lead–acid battery is a storage technology that is widely used in photovoltaic (PV) systems. Battery charging and discharging profiles have a direct impact on the battery degradation and battery loss of life. This study presents a new 2-model iterative approach for explicit modelling of battery degradation in the optimal operation of PV systems. The proposed approach consists of two models: namely, economic model and degradation model which are solved iteratively to reach the optimal solution. The economic model is a linear programming optimisation problem that calculates the optimal hourly battery use profile based on an assumed value of the battery degradation cost. The degradation model, in turn, gives the battery degradation cost based on the battery use profile, temperature and battery characteristics. The models are solved iteratively to finally reach to the optimal battery use considering battery degradation. The proposed approach has been applied to a 4 kWp PV system and the performance of the proposed approach were evaluated. Applicability of the proposed approach in determining the optimal storage size and the economic battery life were also shown. Advantages and the capability of the proposed approach in considering PV generation and irradiation variations were also evaluated through seasonality analysis.
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ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2015.0163