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Value Stacking of Batteries for Multi-Factorial Degradation Through Iterative Quadratic Fitting

Abstract

This paper proposes a method for optimal scheduling of battery services that accounts for battery degradation from multiple factors, such as Depth of Discharge (DoD) and mean State of Charge (mSoC). The proposed method employs a convex and quadratic degradation function based on charging patterns and frequency market participation to iteratively capture the actual degradation cost. Through iterative adjustments to better represent degradation, the method identifies the optimal solution for multi-market operation and value stacking of battery services. Initial simulations demonstrate a 55 % to 70 % increase in profits from spot-price and frequency market participation compared to other methods.

Category

Academic chapter

Language

English

Affiliation

  • SINTEF Energy Research / Energy Systems

Year

2025

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

2025 IEEE PES Innovative Smart Grid Technologies Conference Europe - ISGT Europe

ISBN

9798331525033

View this publication at Norwegian Research Information Repository