Optimal Battery Planning for Microgrid Applications Considering Battery Swapping and Evolution of the SOH During Lifecycle Aging

Batteries are subject to degradation over time, which gradually reduces their capacity and operation capability when they are installed in a microgrid. Therefore, accurate estimation of the battery state of health (SOH) is essential for optimal planning of battery storage systems (BSS) in microgrids. Battery SOH is defined as the ratio between the battery capacity at a specific charge/discharge cycle and its initial rated capacity. To this end, this article proposes a novel comprehensive two-stage approach for optimal planning of BSS in a microgrid. In Stage I, the mixed-integer linear programming (MILP) optimization problem is formulated to determine the battery's optimal size and degradation factor, which determines the battery capacity degradation per charging/discharging cycle. The novel degradation factor is developed to keep track of the battery capacity degradation over time and to swap the battery before the end of its lifecycle. In Stage II, the MILP management problem is formulated for optimal scheduling and swapping of the BSS during cycle life aging considering battery salvage value. The microgrid is assumed to have two BSS, one is lead-acid and the second is lithium-ion. The proposed approach is implemented for both islanded mode and grid-connected mode of microgrid operation. Simulation results have confirmed the effectiveness of the proposed approach.

Automated summary

This article proposes a comprehensive two-stage approach for optimal planning of battery storage systems (BSS) in a microgrid. The first stage formulates a mixed-integer linear programming (MILP) problem to determine the optimal size and degradation factor of the battery. The second stage formulates an MILP management problem for optimal scheduling and swapping of the BSS.