Microgrids are subsystems of the distribution grid which comprises small generation capacities, storage devices and controllable loads, which can operate either connected or isolated from the utility grid. This paper studies the microgrid economic scheduling, i.e. the problem of optimize microgrid operations to fulfil a time-varying energy demand and operational constraints while minimizing the costs of internal production and imported energy from the utility grid. The problem is posed as a mixed-integer linear programming model. The key difference in the proposed modeling approach is that no complex heuristics or decompositions are used; the full model is formulated and solved in an efficient way by using commercial solvers. This leads to significant improvements in schedule quality and in computational burden. A case study of a typical microgrid is investigated: simulation results show the feasibility and the effectiveness of the proposed approach.

A Mixed Integer Linear Formulation for Microgrid Economic Scheduling

Glielmo L.
2011-01-01

Abstract

Microgrids are subsystems of the distribution grid which comprises small generation capacities, storage devices and controllable loads, which can operate either connected or isolated from the utility grid. This paper studies the microgrid economic scheduling, i.e. the problem of optimize microgrid operations to fulfil a time-varying energy demand and operational constraints while minimizing the costs of internal production and imported energy from the utility grid. The problem is posed as a mixed-integer linear programming model. The key difference in the proposed modeling approach is that no complex heuristics or decompositions are used; the full model is formulated and solved in an efficient way by using commercial solvers. This leads to significant improvements in schedule quality and in computational burden. A case study of a typical microgrid is investigated: simulation results show the feasibility and the effectiveness of the proposed approach.
2011
Energy management; Scheduling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/11561
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