A dynamic optimization-based architecture for polygeneration microgrids with tri-generation, renewables, storage systems and electrical vehicles. (15th May 2015)

• Record Type: Journal Article
• Authors: Bracco, Stefano; Delfino, Federico; Pampararo, Fabio; Robba, Michela; Rossi, Mansueto
• Is Part Of: Energy conversion and management. Volume 96(2015)
• Page Start: 511
• Page End: 520
• Publication Date: 2015-05-15
• Subjects: Smart grids -- Renewable energy -- Optimization; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2015.03.013
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: We describe two national special projects on smart grid. We developed dynamic decision model based on a MPC architecture. We developed an optimization model for microgrids, for a specific case study. Abstract: An overall architecture, or Energy Management System (EMS), based on a dynamic optimization model to minimize operating costs and CO2 emissions is formalized and applied to the University of Genova Savona Campus test-bed facilities consisting of a Smart Polygeneration Microgrid (SPM) and a Sustainable Energy Building (SEB) connected to such microgrid. The electric grid is a three phase low voltage distribution system, connecting many different technologies: three cogeneration micro gas turbines fed by natural gas, a photovoltaic field, three cogeneration Concentrating Solar Powered (CSP) systems (equipped with Stirling engines), an absorption chiller equipped with a storage tank, two types of electrical storage based on batteries technology (long term Na–Ni and short term Li-Ion ion), two electric vehicles charging stations, other electrical devices (inverters and smart metering systems), etc. The EMS can be used both for microgrids approximated as single bus bar (or one node) and for microgrids in which all buses are taken into account. The optimal operation of the microgrid is based on a central controller that receives forecasts and data from a SCADA system and that can schedule all dispatchable plants in the day ahead or in real time through an approach based on Model Predictive Control (MPC). The architecture is tested and applied to the case study of the Savona Campus.