This paper presents a model predictive control approach for the economic optimization of a microgrid including smart buildings, wind power production facilities and an energy storage unit. Various optimization scenarios are considered in a comprehensive and unified framework, which can be adapted to pursue different objectives at the same time, such as ensuring the electricity supply to the smart buildings, maximizing the profit from the electricity trading market, or managing the energy storage. The optimization problem can be addressed in a model predictive framework using the receding horizon approach, and ultimately formulated as a quadratic programming problem, which can be solved with reliable and efficient tools. In order to analyze a realistic scenario, the relevant data are taken from real systems (i.e., from a real wind farm and from a real commercial building, located in Italy). Simulation results show the economic advantages that can be gained through the combined usage of renewable energy generation and energy storage.
|Titolo:||MPC-based Management of Energy Resources in Smart Microgrids|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||04.1 Contributo in Atti di convegno|
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|2017 - ICINCO - DaoFerrariniPiroddi.pdf||Articolo||Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)||Accesso riservato|