Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †
Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 Munich, Germany
Energy Research Institute @ NTU, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore 637371, Singapore
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Energy Technology Unit, Vlaamse Instelling voor Technologisch Onderzoek (VITO), Boeretang 200, 2400 Mol, Belgium
Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore
School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in IEEE 18th International Conference on Environment and Electrical Engineering and 2nd Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Palermo, Italy, 2018.
These authors contributed equally to this work.
Received: 15 January 2019 / Revised: 6 March 2019 / Accepted: 7 March 2019 / Published: 14 March 2019
To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh
installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh
installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.
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Hesse, H.C.; Kumtepeli, V.; Schimpe, M.; Reniers, J.; Howey, D.A.; Tripathi, A.; Wang, Y.; Jossen, A. Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †. Energies 2019, 12, 999.
Hesse HC, Kumtepeli V, Schimpe M, Reniers J, Howey DA, Tripathi A, Wang Y, Jossen A. Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †. Energies. 2019; 12(6):999.
Hesse, Holger C.; Kumtepeli, Volkan; Schimpe, Michael; Reniers, Jorn; Howey, David A.; Tripathi, Anshuman; Wang, Youyi; Jossen, Andreas. 2019. "Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †." Energies 12, no. 6: 999.
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