The use of stationary energy storage systems in the commercial and industry (C&I) sector is crucial for supporting the integration of renewable energy sources. Energy systems within the C&I sector are highly diverse, and energy storages can serve a wide array of different applications. However, the relatively high investment cost of stationary energy storage systems hinders their widespread adoption. Yet, this barrier might be removed by maximizing the earning potential by combining multiple applications within one energy storage.
While the related research clearly demonstrates that integrating multiple applications within a single storage system increases profitability, several limitations are worth noting. Firstly, the existing studies generally assume known load data for the entire simulation period, overlooking the necessity of forecasting and the uncertainties it introduces. These uncertainties can significantly affect storage control strategies and, consequently, the profitability of the storage system. Second, only Braeuer et al. validated their approach across a diverse range of load profiles, a critical factor since variations in loads significantly impact optimal storage operations.
Our work seeks to overcome these limitations by focusing on two of the most used storage applications in the commercial and industrial sector: peak shaving and self-consumption optimisation, as well as their combined application. We simulated storage usage across the 50 diverse load profiles previously analyzed by Braeuer et al. Our simulation notably includes real forecasting models within the combined application, and a comprehensive economic model of the C&I sector in Germany, thus providing a closer approximation to real-world conditions.
Consistent with contemporary research, our findings reveal that multi-use operation can significantly increase profitability. However, the discrepancy between the profitability using ideal versus realistic forecasts is considerable. Perfect forecasts could enhance the net present value (NPV) by 27%, whereas realistic forecasts resulted in a modest 5% increase. Furthermore, we delved into the specifics of self-consumption optimisation and peak shaving as standalone strategies. Our analysis indicates that while self-consumption optimisation could not be considered profitable for any of the companies analyzed, peak shaving proved lucrative if the load falls into the right tariff structure based on the annual usage hours.