This work presents the application of model predictive control (MPC) for the energy management of smart buildings in microgrids. It is shown that by means of the described MPC formulation the power exchange at the point of connection of the building can be made close to a given power reference, typically available in microgrid contexts, and, therefore, more predictable. The MPC has the advantage of using in a smart way the storage, with a limited stress to the electronic power interface of the storage system. In principle, the approach is capable of exploiting all the available information about generation and absorption profiles, while minimizing operation costs. In addition, an economic meaning of the terms of the cost function is given, which allows to better appreciate the economic impact of the set control parameters. The approach is evaluated considering realistic conditions and parameters and compared with a heuristic method that operates in an instantaneous basis, that is, without considering any information on future system evolution.
Model predictive control of electrical energy storage systems for microgrids-integrated smart buildings
Mion E.;Caldognetto T.;Simmini F.;Bruschetta M.;Carli R.
2019
Abstract
This work presents the application of model predictive control (MPC) for the energy management of smart buildings in microgrids. It is shown that by means of the described MPC formulation the power exchange at the point of connection of the building can be made close to a given power reference, typically available in microgrid contexts, and, therefore, more predictable. The MPC has the advantage of using in a smart way the storage, with a limited stress to the electronic power interface of the storage system. In principle, the approach is capable of exploiting all the available information about generation and absorption profiles, while minimizing operation costs. In addition, an economic meaning of the terms of the cost function is given, which allows to better appreciate the economic impact of the set control parameters. The approach is evaluated considering realistic conditions and parameters and compared with a heuristic method that operates in an instantaneous basis, that is, without considering any information on future system evolution.Pubblicazioni consigliate
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