Comparison of optimization solvers in the model predictive control of a PV-battery-heat pump system

This paper presents a model predictive control approach for a home energy system with a heat pump, a thermal storage, a photovoltaic system and a battery. The modeling of the system in the mixed-integer linear programming framework is demonstrated and results of a one-year simulation with real measu...

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Bibliographic Details
Published inEnergy procedia Vol. 155; pp. 524 - 535
Main Authors Gelleschus, Ronny, Böttiger, Michael, Stange, Peter, Bocklisch, Thilo
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.01.2018
Subjects
Dynamic Programming
Energy Management System
Energy Storage
Genetic Algorithm
Mixed-Integer Linear Programming
Model Predivtive Control
Sector Coupling
Model Predivtive Control
Dynamic Programming
Energy Storage
Sector Coupling
Genetic Algorithm
Mixed-Integer Linear Programming
Energy Management System
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ISSN1876-6102
1876-6102
DOI10.1016/j.egypro.2018.11.028

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Summary:This paper presents a model predictive control approach for a home energy system with a heat pump, a thermal storage, a photovoltaic system and a battery. The modeling of the system in the mixed-integer linear programming framework is demonstrated and results of a one-year simulation with real measured PV and electric load data are shown. Different solution strategies for the underlying optimization problem are presented. The strategies are compared with respect to their performance and reliability. In this rather complex case branch & cut-based algorithms performed best in solving the optimization problem.
ISSN:1876-6102
1876-6102
DOI:10.1016/j.egypro.2018.11.028