Battery degradation significantly impacts the operational costs and profitability of hybrid power plants (HPPs) participating in the day-ahead (DA) energy market. This paper conducts a comparative analysis of the effectiveness of three battery degradation models. The models calculate the battery degradation as a function of the energy throughput (TP model), the discharge maneuvers (DM model) and based on the Rainflow cycle counting algorithm (RF model). A deterministic mixed-integer linear programming model is developed to maximize revenue of HPPs participating in the DA market considering battery degradation costs. Numerical results reveal that the TP model provides the highest profitability in the DA energy market with the lowest computational complexity, while the RF and DM models capture the battery aging with higher accuracy. This comparative analysis offers some insights useful for selecting appropriate degradation models for better operational performance and longer battery life.
Battery degradation significantly impacts the operational costs and profitability of hybrid power plants (HPPs) participating in the day-ahead (DA) energy market. This paper conducts a comparative analysis of the effectiveness of three battery degradation models. The models calculate the battery degradation as a function of the energy throughput (TP model), the discharge maneuvers (DM model) and based on the Rainflow cycle counting algorithm (RF model). A deterministic mixed-integer linear programming model is developed to maximize revenue of HPPs participating in the DA market considering battery degradation costs. Numerical results reveal that the TP model provides the highest profitability in the DA energy market with the lowest computational complexity, while the RF and DM models capture the battery aging with higher accuracy. This comparative analysis offers some insights useful for selecting appropriate degradation models for better operational performance and longer battery life. Read More
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