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Dr. Holger Hesse, Institute for Electrical Energy Storage (EES), Technical University Munich
Applied research on battery storage systems for stationary applications

While battery energy storage systems (BESS) decline rapidly in cost, their profitability for use in different stationary applications is frequently discussed: Recent studies investigate the applicability and economic turnover of battery systems in various applications, e.g. residential PV-home storage integration [1], the provision of ancillary services (e.g. primary and secondary control reserve) [2,3] and peak-shaving applications [4]. After a brief introduction to the most relevant stationary storage application fields, we demonstrate a techno-economical assessment of battery storage systems using a proprietary simulation tool (SimSES) as a framework model. This detailed sensitivity analysis tool allows complex scenario analyses. However, it must be reduced in complexity to allow for a time-efficient multi-parameter screening and optimization. Therefore, we present a linear optimization approach, that allows optimizing the energy capacity and power capability for storage and inverter system to find best profitability for a given storage application. The optimization model does not only take efficiency of batteries and power electronics into account, but also mimics the degradation of storage due to calendric and cyclic aging processes inherently affecting battery lifetime. For the exemplary application of storage in residential photovoltaic and industrial peak-shaving applications, the resulting cost of storage is opposed to the profit generated. We present the attainable return on invest (ROI) as a figure of merit, calculated for different storage technologies with their specific cost and degradation parameters. Namely, a lead-acid (PbA), a lithium-iron-phosphate (LFP) and a lithium-nickel-manganese-cobalt (NMC) battery are compared. As an outlook, we also discuss in brief an approach to optimize the storage dispatch operation strategy in a peak shaving application: it is aimed to optimize the storage charge and discharge behavior according to forecasts and current load and generation profiles to achieve the best compromise of peak reduction and battery dispatch and aging related expenses.

References: [1] N. Truong, M. Naumann, R. C. Karl, M. Müller, A. Jossen, H. C. Hesse "Economics of residential photovoltaic battery systems in Germany: The case of Tesla's Powerwall", batteries, 22, (2016) [2] C. Göbel, H. Hesse, M. Schimpe, A. Jossen, H. Jacobsen: "Model-based Dispatch Strategies for Lithium-Ion Battery Energy Storage applied to Pay-as-Bid Markets for Secondary Reserve", IEEE Transactions on Smart Grid 32, 6, (2017) [3] M. Müller, A. Zeh , M. Naumann, H. Hesse, A. Jossen, R. Witzmann: "Fundamentals of using Battery Energy Storage Systems for providing Primary Control Reserve", Batteries, 2, 29, (2016) [4] A. Oudalov, R. Cherkaoui, A. Beguin. "Sizing and optimal operation of battery energy storage system for peak shaving application. "Power Tech, 2007 IEEE Lausanne. IEEE (2007)

Monday, 17.07.17

13:15 h - 14:15 h

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