The authors propose a control architecture aimed at optimizing energy resources for residential prosumers in a demand response framework. The control of resources is performed in two stages. The global control functions, based on the solution of a predictive optimal control problem are ensured by a cloud-based computation platform whereas a closed-loop local controller is responsible for the management of field components and actuators. The methodology is developed for managing residential micro/nano grids comprising PV generation, battery storage and interruptible loads. Simulations are aimed at assessing how much optimality can be affected by prevision errors. Tests are carried out considering a simulated environment characterized by realistic and highly resolved demand and generation curves.
|Titolo:||Predictive control of demand and storage for residential prosumers|
|Data di pubblicazione:||2017|
|Nome del convegno:||IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017|
|Digital Object Identifier (DOI):||10.1109/ISGTEurope.2017.8260327|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|