Deregulated electricity markets with time varying electricity prices and opportunities for consumer cost mitigation makes energy storage such as a battery an attractive proposition; users can charge the battery when prices are low and discharge the battery for activities when prices are high. Sharing a large capacity battery across a group of homes in a community, can not only alleviate the economic deterrents but also exploit the fact that users' activity patterns do not necessarily overlap. This scenario, however, induces competition for battery capacity between the users in general as they may want to maximize their own cost savings by occupying more battery capacity when the electricity price is low. A stochastic general sum game theoretical framework is proposed to capture the competitive behaviors of users sending messages to a common battery controller that manages the charging and discharging based on the received, albeit incomplete, information. With such a framework, we show that there always exists a non-stationary social optimal battery control policy - a credit based battery management scheme that ensures game theoretic equilibrium among all players. In this credit based battery management strategy, one user's access to the battery is strictly denied whenever he is found to give “abnormal” messages. This equilibrium control policy requires long time established observations and also “forces” users to share their energy demands accurately with the controller which leads to privacy concerns. We therefore, propose, a stationary suboptimal message blind battery management strategy which in the special case that the unforeseeable component of users' demands is i.i.d., we demonstrate is optimal. For the general non iid model, we demonstrate numerically using real electricity and pricing data, that such battery management strategy can provide a close performance to the optimal credit based battery management strategy using real electricity usage and pricing data.