Simplistic Revenue Based BESS Sizing Tool Developed in Python Using Historical Grid Data
Lucas Tunelid, Micheal Peri, Srinath Sathyamoorthy, Hamza Shafique, Andres Rozas, Lina Bertling Tjernberg · 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) · 2022
The introduction of transmission operators enabling small-scale energy storage to participate in the frequency containment market through augmented bidding requires estimating the potential revenue gain of such instalments. Due to this, the overall goal of this study has been to develop and implement a simplistic model within Python for consumers looking into investing in such systems, capable of analyzing the potential of generating profit for a specific battery configuration through the use of historical electricity prices and grid frequency data. This paper proposes a model utilizing sets of linear and nonlinear constraints in order to represent the process of bidding on the Nordic frequency containment reserve market. Furthermore, the potential cost savings made by peak shaving and a method of estimating the cost of the degradation due to cycling the battery have been included within the model. The final result shows a software capable of identifying appropriate system sizes based on the instalment’s cost and the potential revenue.