Novel probabilistic optimization model for lead-acid and vanadium redox flow batteries under real-time pricing programs

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Juan M. Lujano-Rojas (Author) Other; Ghassan Zubi (Author) Other; Rodolfo Dufo-López (Author) Other; José L. Bernal-Agustín (Author) Other; João P. S. Catalão (Author) FEUP

Journal

Title: International Journal of Electrical Power & Energy Systems

Vol. 97

Pages: 72-84

ISSN: 0142-0615

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 8 Citations

Scopus - 9 Citations

Other information

Authenticus ID: P-00N-6MB

DOI: 10.1016/j.ijepes.2017.10.037

Abstract (EN): The integration of storage systems into smart grids is being widely analysed in order to increase the flexibility of the power system and its ability to accommodate a higher share of wind and solar power. The success of this process requires a comprehensive techno-economic study of the storage technology in contrast with electricity market behaviour. The focus of this work is on lead-acid and vanadium redox flow batteries. This paper presents a novel probabilistic optimization model for managing energy storage systems. The model is able to incorporate the forecasting error of electricity prices, offering with this a near-optimal control option. Using real data from the Spanish electricity market from the year 2016, the probability distribution of forecasting error is determined. The model determines electricity price uncertainty by means of Monte Carlo Simulation and includes it in the energy arbitrage problem, which is eventually solved by using an integer-coded genetic algorithm. In this way, the probability distribution of the revenue is determined with consideration of the complex behaviours of lead acid and vanadium redox flow batteries as well as their associated operating devices such as power converters.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13