Optimal energy management of a small-size building via hybrid model predictive control

被引：48

作者：

Khakimova, Albina ^{[1
]}

Kusatayeva, Aliya ^{[1
]}

Shamshimova, Akmaral ^{[1
]}

Sharipova, Dana ^{[1
]}

Bemporad, Alberto ^{[2
]}

Familiant, Yakov ^{[3
]}

Shintemirov, Almas ^{[3
]}

Ten, Viktor ^{[1
]}

Rubagotti, Matteo ^{[4
]}

机构：

[1] Natl Lab Astana, 53 Kabanbay Batyr Ave, Astana Z05H0P9, Kazakhstan

[2] IMT Inst Adv Studies, Piazza S Ponziano 6, I-55100 Lucca, Italy

[3] Nazarbayev Univ, 53 Kabanbay Batyr Ave 53, Astana Z05H0P9, Kazakhstan

[4] Univ Leicester, Univ Rd, Leicester LE1 7RH, Leics, England

来源：

ENERGY AND BUILDINGS | 2017年 / 140卷

关键词：

Model predictive control (MPC); Hybrid model predictive control (HMPC); Building control; Temperature control; Energy management systems; SYSTEMS; IMPLEMENTATION; COMFORT; MPC;

D O I：

10.1016/j.enbuild.2017.01.045

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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, arid 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. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：1 / 8

页数：8

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