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. A microgrid has the ability to increase energy efficiency and reduce emissions. This paper studies the microgrid environmental/economic problem, i.e. the problem of optimizing microgrid operations to fulfil a time-varying energy demand and operational constraints while achieving a tradeoff between microgrid running costs and emissions. The problem is posed as a multi-objective mixed-integer linear optimization problem, which is solved in an efficient way by using commercial solvers. A case study of a typical microgrid is investigated: simulation results show the feasibility and the effectiveness of the proposed approach.
Multi-objective Optimization for Environmental/Economic Microgrid Scheduling / Parisio, A; Glielmo, L.. - (2012). (Intervento presentato al convegno 2012 Conference on Cyber Technology in Automation, Control and Intelligent Systems tenutosi a Bangkok nel May 2012) [10.1109/CYBER.2012.6392519].
Multi-objective Optimization for Environmental/Economic Microgrid Scheduling
Glielmo L.
2012
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. A microgrid has the ability to increase energy efficiency and reduce emissions. This paper studies the microgrid environmental/economic problem, i.e. the problem of optimizing microgrid operations to fulfil a time-varying energy demand and operational constraints while achieving a tradeoff between microgrid running costs and emissions. The problem is posed as a multi-objective mixed-integer linear optimization problem, which is solved in an efficient way by using commercial solvers. A case study of a typical microgrid is investigated: simulation results show the feasibility and the effectiveness of the proposed approach.File | Dimensione | Formato | |
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