As the aviation industry works towards decreasing its carbon dioxide emissions, managing energy usage at airports is an important consideration. Our focus is on electric vehicles (EV) that add to the energy demands of an airport but can be undertaken at low peak times if the owner’s return date is known. We present different greedy algorithms for EV charging scheduling . We compare their performance to the presently used immediate algorithm and before departure charging. A key novelty is that we simulate and examine the impact of charging point failure and maintenance on the performance of the algorithms. Our simulations suggest a greedy EV scheduling algorithm will reduce the energy load at peak hours and fill valleys compared to the current immediate charging approach. The load deviation scores, which measure how well the load is balanced, are 717.1 for the greedy algorithm and 730.0 for the immediate approach. However, the greedy algorithm will not lower the satisfaction of charging demand in scenarios with no charging failure.