A Model-Aware Comprehensive Tool for Battery Energy Storage System Sizing

Matteo Spiller, Giuliano Rancilio, Filippo Bovera, Giacomo Gorni, Stefano Mandelli, Federico Bresciani and Marco Merlo ()
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Matteo Spiller: Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy
Giuliano Rancilio: Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy
Filippo Bovera: Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy
Giacomo Gorni: Eni S.p.A., Renewable, New Energies and Material Science Research Center, Via Fauser 4, 28100 Novara, Italy
Stefano Mandelli: Plenitude, Via Giuseppe Ripamonti 85, 20141 Milano, Italy
Federico Bresciani: Eni S.p.A., Renewable, New Energies and Material Science Research Center, Via Fauser 4, 28100 Novara, Italy
Marco Merlo: Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy

Energies, 2023, vol. 16, issue 18, 1-24

Abstract: This paper presents a parametric procedure to size a hybrid system consisting of renewable generation (wind turbines and photovoltaic panels) and Battery Energy Storage Systems (BESS). To cope with the increasing installation of grid-scale BESS, an innovative, fast and flexible procedure for evaluating an efficient size for this asset has been developed. The tool exploits a high-fidelity empirical model to assess stand-alone BESS or hybrid power plants under different service stacking configurations. The economic performance has been evaluated considering the revenue stacking that occurs when participating in up to four distinct energy markets and the degradation of the BESS performances due to both cycle- and calendar-aging. The parametric nature of the tool enables the investigation of a wide range of system parameters, including novel BESS control logic, market prices, and energy production. The presented outcomes detail the techno-economic performances of a hybrid system over a 20-year scenario, proposing a sensitivity analysis of both technical and economic parameters. The case study results highlight the necessity of steering BESS investment towards the coupling of RES and accurate planning of the service stacking. Indeed, the implementation of a storage system in an energy district improves the internal rate of return of the project by up to 10% in the best-case scenario. Moreover, accurate service stacking has shown a boost in revenues by up to 44% with the same degradation.

Keywords: battery energy storage system; renewables; market service stacking (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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