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Methodology

The analysis was carried out using Ember’s Battery Modelling Suite (BattMan), a comprehensive tool designed to optimise the operation and sizing of Battery Energy Storage Systems (BESS) across multiple revenue streams. At its core is the Battery Modelling Module, which performs detailed dispatch and sizing optimisation. It comprises the following key modules:

• Battery optimisation:
  For this report, we optimise BESS operation to maximise revenue through participation in the Day-Ahead Market (DAM) and SRAS-Down ancillary service. Technically, the concept can be extended across multiple market segments based on the availability of data.

• Price forecasting:
  Generates forward-looking electricity price projections using historical trends, seasonal demand-supply variations, and changes in the generation mix. These forecasts serve as essential inputs to the DAM and ancillary service market optimisation.

• Financial analysis of battery projects:
  Converts technical outputs into detailed project-level financial metrics such as IRR, payback period and discounted cash flow. This provides a comprehensive techno-economic assessment of a BESS project.

• Sensitivity analysis:
  Tests the robustness of project outcomes by analysing how ~10+ key technical, market, and financial variables affect returns—highlighting risks and resilience in different scenarios.

A detailed description of the data, methods and inputs used can be found here.

Acknowledgement

Contributors 

Special thanks to Satyadeep Jain (Ambit) for his valuable contributions to the writing of this report, and to Abhishek Jain (O2 Power) for reviewing the report and providing key feedback. Thanks to Aditya Lolla for conducting the review and providing valuable suggestions. This work was significantly improved by the contributions of Tito Das, Claire Kaelin, Chelsea Bruce-Lockhart, Jivan Zhen Thiru and Reynaldo Dizon. 

Photo  

Photo credit:  Cynthia Lee / Alamy