Numerical and experimental testing of predictive EMS algorithms for PV-BESS residential microgrid

This paper presents the Multi-Good MicroGrid (MGMG) experimental facility that has been built at the Department of Energy of Politecnico di Milano to test and develop new innovative predictive optimization Energy Management System (EMS) for MGMG operation. After an introduction on the current litera...

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Bibliographic Details
Published in2019 IEEE Milan PowerTech pp. 1 - 6
Main Authors Polimeni, S., Moretti, L., Manzolini, G., Leva, S., Meraldi, L., Raboni, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
Distributed power generation
Energy management
Energy storage
Generators
Load modeling
Mathematical model
Microgrids
Optimization
Prediction algorithms
Predictive optimization
Test facilities
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Summary:This paper presents the Multi-Good MicroGrid (MGMG) experimental facility that has been built at the Department of Energy of Politecnico di Milano to test and develop new innovative predictive optimization Energy Management System (EMS) for MGMG operation. After an introduction on the current literature status about EMS and microgrid (MG) test facilities, this work describes in detail this new experimental setup. The MGMG integrates different goods, generators, renewable energy sources, various types of loads and energy storage systems. A case study is discussed in the second part of the paper: a grid connected MG that manages a photovoltaic field, a Li-ion storage and an aggregated residential load is analyzed. A comparison between a heuristic control strategy and the two-layer mixed integer linear programming predictive EMS we developed is performed. Both simulation and experimental results confirm that the optimized EMS ensures superior economical performances.
DOI:10.1109/PTC.2019.8810548