Pareto-optimal power flow control in heterogeneous battery energy storage systems

This research proposes a methodological framework that effectively and efficiently identifies Pareto-optimal solutions of power flow control strategies (PFCSs) in heterogeneous battery energy storage systems (BESSs) and aims at achieving operational decision-making. The economic and ecological benefit of a BESS is strongly dependent on the efficiency of its operation. However, rapid changes in battery technology significantly impact the incorporation of an appropriate PFCS. Here, the Hyper Space Exploration (HSE) methodology is applied to the validated simulation environment of a BESS for the purpose of quantifying trade-offs in various use cases and system configurations. Simulations are carried out to analyze the target indicators performance, efficiency, and service life relating to the applied PFCS in a peak shaving application scenario. The results illustrate the correlations between the design variables, use case variables, and target indicators. A positive correlation is observed between the target indicators performance and efficiency, whereas a negative correlation is found between the criterion of service life and the other target indicators. By analyzing them systematically, the methodological framework further enhances understanding the trade-offs between the target indicators. The framework also applies to other PFCSs, use cases, and target indicators. •A methodological framework that identifies Pareto-optimal solutions of power flow control strategies is given.•The sensitivities of parametric design variables and use case variables on the target indicators are quantified.•This work develops a generic aging model by focusing on capacity fade.•It proposes a new target indicator to represent a battery’s estimated remaining life.•Several correlations were observed between the design variables, use case variables, and target indicators.