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In the current grid, power is available at all times, to all users, indiscriminately. This makes the grid vulnerable to sporadic demands and much effort has been invested to mitigate their effect. We offer here a digital approach to power distribution: an energy-on-demand approach in which the user initiates an energy request to the server of the energy provider before receiving the energy. Considering a micro-grid with a mix of generators (sustainable and other sources), the server optimizes the entire power network before granting the energy requests, fully or partially. The energy is packetized and is routed to the user's address by an array of switches. For example, in an office building, the energy provider may queue energy requests by some air-condition units and grant these requests later. During recovery from a blackout, pockets of instability may be isolated by their unusual energy demands. In its simplest form, this network can be realized by overlaying an auxiliary (control, or, data) network on top of an energy delivery network and coupling the two through an array of addressable digital power switches. In assessing this approach, we are concentrating in this paper on the management of energy requests by using statistical models. An energy network with a limited channel capacity and the optimal path for energy flow in a standard IEEE 39 bus are considered.