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Article

Autonomous Operation of Stationary Battery Energy Storage Systems—Optimal Storage Design and Economic Potential

Faculty of Engineering and Science, University of Agder, Jon Lilletuns Vei 9, 4879 Grimstad, Norway
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Author to whom correspondence should be addressed.
Academic Editors: Gianfranco Chicco and Steffen Finck
Energies 2021, 14(5), 1333; https://doi.org/10.3390/en14051333
Received: 11 January 2021 / Revised: 14 February 2021 / Accepted: 20 February 2021 / Published: 1 March 2021
(This article belongs to the Special Issue Modern Computational Methods for Flexibility Control)
Global warming requires a changeover from fossil fuel based to renewable energy sources on the electrical supply side and electrification of the demand side. Due to the transient nature of renewables and fluctuating demand, buffer capacities are necessary to compensate for supply/demand imbalances. Battery energy storage systems are promising. However, the initial costs are high. Repurposing electric vehicle batteries can reduce initial costs. Further, storage design optimization could significantly improve costs. Therefore, a battery control algorithm was developed, and a simulation study was performed to identify the optimal storage design and its economic potential. The algorithm used is based on autonomous (on-site) optimization, which relies on an incentive determining the operation mode (charge, discharge, or idle). The incentive used was the historic day-ahead stock market price for electricity, and the resulting potential economic gains for different European countries were compared for the years 2015–2019. This showed that there is a correlation between economic gain, optimal storage design (capacity-to-power ratio), and the mean standard deviation, as well as the mean relative change of the different day-ahead prices. Low yearly mean standard deviations of about 0.5 Euro Cents per kWh battery capacity lead to yearly earnings of about 1 €/kWh, deviations of 1 Euro Cent to 10 €/kWh, and deviations of 2 Euro Cents to 20 €/kWh. Small yearly mean relative changes, lower than 5%, lead to capacity-to-power ratios greater than 3, relative changes around 10% to an optimal capacity-to-power between 1.5 and 3, and for relative changes greater than 10% to an optimal capacity-to-power ratios of 1. While in countries like the United Kingdom, high potential earnings are expected, the economic prospective in countries like Norway is low due to limited day-ahead price performance. View Full-Text
Keywords: fluctuating electric supply and demand; battery energy storage systems; autonomous optimization; day-ahead stock market price; optimal storage design; economic potential fluctuating electric supply and demand; battery energy storage systems; autonomous optimization; day-ahead stock market price; optimal storage design; economic potential
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MDPI and ACS Style

Faessler, B.; Bogunović Jakobsen, A. Autonomous Operation of Stationary Battery Energy Storage Systems—Optimal Storage Design and Economic Potential. Energies 2021, 14, 1333. https://doi.org/10.3390/en14051333

AMA Style

Faessler B, Bogunović Jakobsen A. Autonomous Operation of Stationary Battery Energy Storage Systems—Optimal Storage Design and Economic Potential. Energies. 2021; 14(5):1333. https://doi.org/10.3390/en14051333

Chicago/Turabian Style

Faessler, Bernhard, and Aleksander Bogunović Jakobsen. 2021. "Autonomous Operation of Stationary Battery Energy Storage Systems—Optimal Storage Design and Economic Potential" Energies 14, no. 5: 1333. https://doi.org/10.3390/en14051333

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