The Paper entitled:
Energy Arbitrage Optimization with Battery Storage: 3D-MILP for Electro-thermal Performance and Semi-empirical Aging Models
has been published in IEEE Access as an “open access” article.
In this paper, a novel method for optimized Dispatch of battery storage systems in stationary grid applications is presented. Profitability through arbitrage trading with battery storage is strongly confined by battery degradation and dissipation losses of both battery and power electronic components. In this study, we present a novel three-dimensional mixed-integer program formulation allowing to model power, state of charge (SOC), and temperature dependence of battery dynamics simultaneously in a three dimensional space leveraging binary counting and union-jack triangulation. The inclusion of a state-of-the-art electro-thermal degradation model with its dependence on most influential physical parameters to the arbitrage revenue optimization allows to extend the battery lifetime by 2.2 years (or 40%) over a base scenario. By doing a profitability estimation over the battery’s lifetime and using 2018 historical intraday market trading prices, we have shown that profitability of the system increases by 11.14% via introducing SOC awareness and another significant 12.64% via introducing thermal sensitivity, resulting in a total 25.19% increase over the base case optimization formulation. Lastly, through the open source publication of the optimization routines described herein, an adaption and development of the code to individual needs is facilitated. This work was made possible through long term experimental testing and continuous efforts of an international collaboration of researches at Technical University of Munich and the Nanyang Technology University, Singapore.
The Paper can be found online at: