A control architecture aimed at optimizing energy resources in a demand response framework is presented. The control of available resources is performed in two stages, according to a hierarchical control structure. A cloud-based computation platform provides global control functions whereas a closed-loop local device controls all field components and actuators. The architecture has been developed for operating residential or commercial micro/nano grids equipped with PV generation, battery storage and interruptible loads. A method, based on predictive optimal control is proposed to handle different demand response schemes. Results are presented considering three typical demand response schemes, testing the robustness of the approach with regard to forecast and resolution errors. The methodology proves to be more effective in the presence of complex pricing schemes.
Optimization of residential storage and energy resources under demand response schemes / Bruno, Sergio; Giannoccaro, Giovanni; La Scala, Massimo. - ELETTRONICO. - (2018), pp. 225-230. (Intervento presentato al convegno 19th IEEE Mediterranean Electrotechnical Conference, MELECON 2018 tenutosi a Marrakech, Morocco nel May 2-7, 2018) [10.1109/MELCON.2018.8379098].
Optimization of residential storage and energy resources under demand response schemes
Bruno, Sergio;Giannoccaro, Giovanni;La Scala, Massimo
2018-01-01
Abstract
A control architecture aimed at optimizing energy resources in a demand response framework is presented. The control of available resources is performed in two stages, according to a hierarchical control structure. A cloud-based computation platform provides global control functions whereas a closed-loop local device controls all field components and actuators. The architecture has been developed for operating residential or commercial micro/nano grids equipped with PV generation, battery storage and interruptible loads. A method, based on predictive optimal control is proposed to handle different demand response schemes. Results are presented considering three typical demand response schemes, testing the robustness of the approach with regard to forecast and resolution errors. The methodology proves to be more effective in the presence of complex pricing schemes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
