Definition and Experimental Validation of a Simplified Model for a Microgrid Thermal Network and its Integration into Energy Management Systems

Andrea Bonfiglio, Massimo Brignone, Federico Delfino, Alessandro Nilberto and Renato Procopio
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Andrea Bonfiglio: Department of Naval, Electrical, and ICT Engineering, University of Genova, I-16145 Genoa, Italy
Massimo Brignone: Department of Naval, Electrical, and ICT Engineering, University of Genova, I-16145 Genoa, Italy
Federico Delfino: Department of Naval, Electrical, and ICT Engineering, University of Genova, I-16145 Genoa, Italy
Alessandro Nilberto: Mechanical, Energy, Management and Transportation Engineering Department, University of Genova, I-16145 Genoa, Italy
Renato Procopio: Department of Naval, Electrical, and ICT Engineering, University of Genova, I-16145 Genoa, Italy

Energies, 2016, vol. 9, issue 11, 1-14

Abstract: The present paper aims at defining a simplified but effective model of a thermal network that links the thermal power generation with the resulting temperature time profile in a heated or refrigerated environment. For this purpose, an equivalent electric circuit is proposed together with an experimental procedure to evaluate its input parameters. The paper also highlights the simplicity of implementation of the proposed model into a microgrid Energy Management System. This allows the optimal operation of the thermal network to be achieved on the basis of available data (desired temperature profile) instead of a less realistic basis (such as the desired thermal power profile). The validation of the proposed model is performed on the Savona Campus Smart Polygeneration Microgrid (SPM) with the following steps: (i) identification of the parameters involved in the equivalent circuit (performed by minimizing the difference between the temperature profile, as calculated with the proposed model, and the measured one in a set of training days); (ii) test of the model accuracy on a set of testing days (comparing the measured temperature profiles with the calculated ones); (iii) implementation of the model into an Energy Management System in order to optimize the thermal generation starting from a desired temperature hourly profile.

Keywords: energy management; optimization algorithm; parameter identification; smart grids; thermal network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
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