This paper discusses decentralized real-time energy management for multiple-source hybrid energy systems (HESs), which adapts to the sudden change in system configuration, such as due to failure of certain devices. An engine-generator/battery/ultracapacitor (UC) HES is chosen as a case study facilitating the following theoretical discussion. The energy management problem is first modeled as a noncooperative game, in which the different preferences of the energy sources (engine-generator, battery pack, and UC pack) in actual operation are quantified through their individual utility functions. The Nash equilibrium is iteratively reached at each control instant via a learning algorithm. Under the game theory based control, each source or player tends to maximize its own preference. However, its satisfaction level also depends on decisions of others. This real-time interaction in decision making provides the proposed energy management a capability to autonomously adapt to the reconfigured HES. A tuning procedure of weight coefficients in the utility functions also helps to further improve the adaptiveness of the decentralized energy management. Both the simulation and real-time implementation show that the game theory based energy management strategy has a comparable performance to the classical centralized benchmarking strategy. Meanwhile, the decentralized strategy demonstrates an obvious flexibility handling the cases when the configuration of the HES varies both statically and dynamically.