relation: http://eprints.imtlucca.it/3638/
title: Optimal energy management of a small-size building via hybrid model predictive control
creator: Khakimova, Albina
creator: Kusatayeva, Aliya
creator: Shamshimova, Akmaral
creator: Sharipova, Dana
creator: Bemporad, Alberto
creator: Familiant, Yakov
creator: Shintemirov, Almas
creator: Ten, Viktor
creator: Rubagotti, Matteo
subject: QA75 Electronic computers. Computer science
description: Abstract This paper presents the design of a Model Predictive Control (MPC) scheme to optimally manage the thermal and electrical subsystems of a small-size building (“smart house”), with the objective of minimizing the expense for buying energy from the grid, while keeping the room temperature within given time-varying bounds. The system, for which an experimental prototype has been built, includes {PV} panels, solar collectors, a battery pack, an electrical heater in a thermal storage tank, and two pumps on the solar collector and radiator hydraulic circuits. The presence of binary control inputs together with continuous ones naturally leads to using a hybrid dynamical model, and the {MPC} controller solves a mixed-integer linear program at each sampling instant, relying on weather forecast data for ambient temperature and solar irradiance. The procedure for controller design is reported with focus on the specific application, and the proposed method is successfully tested on the experimental site.
publisher: Elsevier
date: 2017-04
type: Article
type: PeerReviewed
format: application/pdf
language: en
identifier: http://eprints.imtlucca.it/3638/1/energybuilding_hmpc.pdf
identifier:   Khakimova, Albina and Kusatayeva, Aliya and Shamshimova, Akmaral and Sharipova, Dana and Bemporad, Alberto and Familiant, Yakov and Shintemirov, Almas and Ten, Viktor and Rubagotti, Matteo  Optimal energy management of a small-size building via hybrid model predictive control.  Energy and Buildings, 140.  pp. 1-8.  ISSN 0378-7788      (2017)  
relation: http://www.sciencedirect.com/science/article/pii/S0378778817301652
relation: 10.1016/j.enbuild.2017.01.045