This thesis presents a control architecture and utility maximization mechanisms for a smart grid based energy community. The particular focus is upon a central server based, utility-oriented energy community which is composed of producer-consumer (prosumer) households each having a home gateway, an energy management system, smart meters, production units and appliances. To find out how such an energy community could be optimally managed from a central server, the type of intelligence required for the different nodes in the energy network has been identified. In addition, different control mechanisms that enable the energy community to make an optimal use of its energy resources are explored. Moreover, utility maximization mechanisms have been implemented on the aggregate energy profile of the energy community targeting three main objectives namely maximizing the aggregate greenness, minimizing the aggregate energy cost and maximizing the prosumers’ comfort. Maximizing the aggregate greenness aims to maximize the level of consumption of renewable energy resources using a novel mechanism that reduces the difference between the supply of and demand for renewable energy resources. Minimizing the aggregate energy cost aims to reduce the peak to average ratio of the aggregate energy profile of the energy community using direct mechanisms for energy cost minimization and a novel appliance based pricing scheme. Maximizing the prosumers’ comfort aims to preserve the schedule preference of prosumers. The mechanisms above are designed and implemented under a research setting of a renewable energy company that manages an energy community composed of central servers which control household, building and/or industrial prosumers.