Energy storage systems emerge as key elements in optimizing sustainable resource use, ensuring a steady flow of energy even when primary sources, such as sun or wind, are intermittent. In this scenario, the techno-economic integration of storage technologies becomes a key building block in the transition to a more resilient and efficient energy system. In this paper, we considered the possibility of using the electricity storage as a business, buying electric energy from the Italian electric dayahead market when prices are low, and selling it back when prices are high. The theoretical modeling and the resulting simulations show that the use of storage in the day-ahead electricity market can actually be a profitable business, by quantifying the possible revenue on each of the last five years, showing that it is highly variable over time. In particular, the recent gas prices crisis changed the framework, showing very interesting revenue opportunities. About forecasting methods, we show that simple forecasting methods (e.g., daily averages) perform adequately, while optimization-based approaches outperform heuristic methods.
Is storage a business? A test on the Italian day-ahead electricity market
Sbaraglia, Simone;Fiori Maccioni, Alessandro
;Ghiani, Emilio;Zedda, Stefano
2025-01-01
Abstract
Energy storage systems emerge as key elements in optimizing sustainable resource use, ensuring a steady flow of energy even when primary sources, such as sun or wind, are intermittent. In this scenario, the techno-economic integration of storage technologies becomes a key building block in the transition to a more resilient and efficient energy system. In this paper, we considered the possibility of using the electricity storage as a business, buying electric energy from the Italian electric dayahead market when prices are low, and selling it back when prices are high. The theoretical modeling and the resulting simulations show that the use of storage in the day-ahead electricity market can actually be a profitable business, by quantifying the possible revenue on each of the last five years, showing that it is highly variable over time. In particular, the recent gas prices crisis changed the framework, showing very interesting revenue opportunities. About forecasting methods, we show that simple forecasting methods (e.g., daily averages) perform adequately, while optimization-based approaches outperform heuristic methods.File | Dimensione | Formato | |
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