NDLI: A comparative probabilistic economic analysis of selected stationary battery systems for grid applications

Content Provider	IEEE Xplore Digital Library
Author	Baumann, M. Zimmermann, B. Dura, H. Simon, B. Weil, M.
Copyright Year	2013
Description	Author affiliation: Helmholtz Inst. Ulm, Ulm, Germany (Simon, B.) \|\| Inst. of Technol. Assessment & Syst. Anal., Karlsruhe Inst. of Technol., Karlsruhe, Germany (Baumann, M.; Zimmermann, B.; Dura, H.; Weil, M.)
Abstract	This Paper focuses on a comparative probabilistic economic comparison of sodium sulfur batteries (NaS), Lithium-Iron Phosphate batteries (LFP), Vanadium Redox Flow Batteries (VRB), Lead Acid batteries (PbA) and a Pumped Hydro Storage Plant (PHS). Two cases for a load leveling and peak shaving storage application were analyzed and compared. The comparison is based on a comprehensive literature review which showed remarkable deviations within most techno-economic values. This makes it difficult to assess the technologies by a deterministic approach. Therefore, a complementary probabilistic approach was developed in form of a Monte Carlo Simulation (MCS). The results show clearly that among batteries, PbA have the best cost performance followed by NaS and VRB. LFP has the highest costs within all scenarios. However, PHS is the most cost efficient technology for load leveling. In the case of peak shaving the battery costs decrease significantly due to lower initial investment costs.
Sponsorship	IEEE Ind. Electron. Soc.
Starting Page	87
Ending Page	92
File Size	1447448
Page Count	6
File Format	PDF
ISBN	9781467344296
e-ISBN	9781467344302
DOI	10.1109/ICCEP.2013.6586972
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-11
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lithium-Ion-Battery Redox-Flow-Battery Bulk storage Electricity batteries Probabilistic logic Batteries Investment Distribution functions Energy storage
Content Type	Text
Resource Type	Article

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