Electric propulsion for commuter air transportation is a promising technology because of significant strides in battery specific energy and motor specific power. Energy storage and rapid battery recharge remain nonetheless challenging owing to the significant energy and power requirements of even small aircraft. By modifying algorithms developed in the field of scheduling theory, we propose power optimized and power-investment optimized strategies for electric aircraft battery swaps and recharges. Several aspects are considered: electric energy expenditures, capital expenditures, and flight schedule integrity. The first strategy optimizes the swaps and recharges to minimize the peak-power draw from the grid and reduce electric energy expenditures. The second strategy optimizes the swaps and recharges to minimize electricity expenditures and capital expenditures associated with battery and charger procurement. In both cases, the optimization is decomposed into two steps. The first step determines the combinations of numbers of chargers and batteries that yield a feasible recharge schedule. It is based on a network flow representation of the battery swap and recharge. The second step builds a recharge schedule for the previously determined numbers of chargers and batteries. Together, they enable the estimation of peak power demand, electric expenditures, and capital expenditures used to implement the power optimized and power-investment optimized strategies. Both strategies are applied to the operations of two commuter airlines and are contrasted with a benchmark non-optimized power-as-needed strategy. Promising results are obtained with up to 61% reduction in peak-power draw and up to 25% reduction in electricity costs.

通勤航空运输的电力推进技术是一项有前途的技术，因为它在电池单位能量和电机单位功率方面取得了长足的进步。由于即使是小型飞机的巨大能量和功率需求，能量存储和快速的电池充电仍然具有挑战性。通过修改调度理论领域开发的算法，我们提出了功率优化和功率投资优化的建议电动飞机电池交换和充电的策略。考虑了几个方面：电能支出，资本支出和航班时刻表的完整性。第一种策略优化了交换和充电，以最大程度地降低电网的峰值功率消耗并减少电能消耗。第二种策略优化了交换和充电，以最大程度地减少与电池和充电器采购相关的电力支出和资本支出。在两种情况下，优化都分解为两个步骤。第一步是确定产生可行的充电时间表的充电器和电池数量的组合。它基于电池交换和充电的网络流量表示。第二步为先前确定数量的充电器和电池建立充电时间表。功率优化和功率投资优化策略。两种策略均适用于两家通勤航空公司的运营，并与基准非优化按需供电策略进行了对比。峰值功率消耗降低多达61％，电力成本降低多达25％，获得了可喜的结果。