This paper presents a direct load control based demand side management (DSM) algorithm that performs peak shaving considering time-varying renewable generation, and thermal comfort of the buildings. The demand side operator of the microgrid (MG) uses the DSM algorithm for peak-shaving, and reducing the energy costs. The DSM controller has a hierarchical control architecture, wherein there is a central controller (CC) and numerous local controllers (LCs). The CC uses information on demand and renewable generation to compute the load to be curtailed. The LCs that supply the consumers, reduce the demand by curtailing heating loads in buildings without breaching thermal comfort limits. Building models, information on comfort margins, and an optimization routine are used by the LCs to implement the DSM algorithm. As the algorithm guarantees thermal comfort, reluctance among consumers to employ direct load control based DSM algorithm is eliminated. Further, in the proposed algorithm demand side operator controls the consumption by monitoring the temperature, therefore need to instal smart thermostats/controllers, and continuous monitoring of prices in buildings is eliminated. The working of the DSM algorithm is illustrated using simulations performed on data obtained from residential heating system with 50 buildings in Norwegian living lab in Steinkjer. Our results indicate that the algorithm performs peak-shaving considering information on renewable generation without breaching thermal comfort margins of the consumer.

Demand Side Management for heating controls in Microgrids

C. Del Vecchio;Glielmo L.
2016

Abstract

This paper presents a direct load control based demand side management (DSM) algorithm that performs peak shaving considering time-varying renewable generation, and thermal comfort of the buildings. The demand side operator of the microgrid (MG) uses the DSM algorithm for peak-shaving, and reducing the energy costs. The DSM controller has a hierarchical control architecture, wherein there is a central controller (CC) and numerous local controllers (LCs). The CC uses information on demand and renewable generation to compute the load to be curtailed. The LCs that supply the consumers, reduce the demand by curtailing heating loads in buildings without breaching thermal comfort limits. Building models, information on comfort margins, and an optimization routine are used by the LCs to implement the DSM algorithm. As the algorithm guarantees thermal comfort, reluctance among consumers to employ direct load control based DSM algorithm is eliminated. Further, in the proposed algorithm demand side operator controls the consumption by monitoring the temperature, therefore need to instal smart thermostats/controllers, and continuous monitoring of prices in buildings is eliminated. The working of the DSM algorithm is illustrated using simulations performed on data obtained from residential heating system with 50 buildings in Norwegian living lab in Steinkjer. Our results indicate that the algorithm performs peak-shaving considering information on renewable generation without breaching thermal comfort margins of the consumer.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12070/11749
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