In the last years we have witnessed an increasing interest in smart buildings, in particular for what concerns optimal energy management, renewable energy sources, and smart appliances. In this paper we investigate the problem of scheduling smart appliance operation in a given time horizon with a set of energy sources and accumulators. Appliance operation is modeled in terms of uninterruptible sequential phases with a given power demand, with the goal of minimizing the energy bill fulfilling duration, energy, and user preference constraints. A Mixed Integer Linear Programming (MIP) model and a greedy heuristic algorithm are given, intended to be used in a synergic way. We show how a general purpose (off-the-shelf) MIP refining procedure can effectively be used for improving, in short computing time, the quality of the solutions provided by the initial greedy heuristic. Computational results confirm the viability of the overall approach, in terms of both solution quality and speed
Optimal scheduling of smart home appliances using mixed-integer linear programming
Sartor, Giorgio
2012/2013
Abstract
In the last years we have witnessed an increasing interest in smart buildings, in particular for what concerns optimal energy management, renewable energy sources, and smart appliances. In this paper we investigate the problem of scheduling smart appliance operation in a given time horizon with a set of energy sources and accumulators. Appliance operation is modeled in terms of uninterruptible sequential phases with a given power demand, with the goal of minimizing the energy bill fulfilling duration, energy, and user preference constraints. A Mixed Integer Linear Programming (MIP) model and a greedy heuristic algorithm are given, intended to be used in a synergic way. We show how a general purpose (off-the-shelf) MIP refining procedure can effectively be used for improving, in short computing time, the quality of the solutions provided by the initial greedy heuristic. Computational results confirm the viability of the overall approach, in terms of both solution quality and speedFile | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/16475