Stochastic optimisation for investment analysis of flow battery storage systems

Y. Tohidi, M. Gibescu

Research output: Contribution to journalArticleAcademicpeer-review


In this study, a stochastic optimisation model is proposed to investigate revenue streams for flow batteries type of energy storage (ES) in a set-up consisting of photovoltaic (PV) solar plant and load. Revenue streams investigated are (i) arbitrage in electricity markets between day-ahead market (DAM) and imbalance market (IM) and (ii) self-consumption of local PV production via storage for supplying the peak load. Stochastic parameters are represented by a set of scenarios and include DAM and IM prices of electricity, solar irradiation and load level. Scenarios are generated by analysing the historical data of the stochastic parameters. A stopping criterion based on the relative change of the revenue is proposed in order to reach a sufficient number of scenarios. The simulation is done on the Dutch DAM and IM electricity prices and for two residential and office load profiles with 107 kW average load and ∼30% PV production. The candidate flow batteries investigated are based on hydrogen-bromine chemistry with different power and energy capacities. The results reveal the potential for a positive business case both for ES stand-alone generation revenue just through arbitrage and also for ES added to PV-load set-up generation revenue through arbitrage and self-consumption.
Original languageEnglish
Pages (from-to)555-562
JournalIET Renewable Power Generation
Issue number4
Publication statusPublished - 2019


Dive into the research topics of 'Stochastic optimisation for investment analysis of flow battery storage systems'. Together they form a unique fingerprint.

Cite this