This work aims at exploring the potential contribution of the Italian residential sector in implementing load flexibility for Demand Response activities. In detail, by combining experimental and statistical approaches, a method to estimate the load profile of a dwelling cluster of 751 units has been presented. To do so, 14 dwelling archetypes have been defined and the algorithm to categorise the sample units has been built. Then, once the potential flexible loads for each archetype have been evaluated, a control strategy for applying load time shifting has been implemented. That strategy accounts for both the power demand profile and the hourly electricity price. Specifically, it has been assumed that end users access a pricing mechanism following the hourly trend of electricity economic value, which is traded day by day in the Italian spot market, instead of the current Time of Use (TOU) system. In such a way, it is possible to flatten the dwellings cluster profile, limiting undesired and unexpected results on the balancing market. In the end, monthly and yearly flexibility indexes have been defined along with the strategy effectiveness parameter. From calculations, it emerges that a dwelling cluster for the Italian residential sector is characterised by a flexibility index of 10.3% and by a strategy effectiveness equal to 34%. It is noteworthy that the highest values for flexibility purpose have been registered over the heating season (winter) for the weekends.

How the italian residential sector could contribute to load flexibility in demand response activities: A methodology for residential clustering and developing a flexibility strategy

Romano S.;
2020-01-01

Abstract

This work aims at exploring the potential contribution of the Italian residential sector in implementing load flexibility for Demand Response activities. In detail, by combining experimental and statistical approaches, a method to estimate the load profile of a dwelling cluster of 751 units has been presented. To do so, 14 dwelling archetypes have been defined and the algorithm to categorise the sample units has been built. Then, once the potential flexible loads for each archetype have been evaluated, a control strategy for applying load time shifting has been implemented. That strategy accounts for both the power demand profile and the hourly electricity price. Specifically, it has been assumed that end users access a pricing mechanism following the hourly trend of electricity economic value, which is traded day by day in the Italian spot market, instead of the current Time of Use (TOU) system. In such a way, it is possible to flatten the dwellings cluster profile, limiting undesired and unexpected results on the balancing market. In the end, monthly and yearly flexibility indexes have been defined along with the strategy effectiveness parameter. From calculations, it emerges that a dwelling cluster for the Italian residential sector is characterised by a flexibility index of 10.3% and by a strategy effectiveness equal to 34%. It is noteworthy that the highest values for flexibility purpose have been registered over the heating season (winter) for the weekends.
2020
Demand Response
Dwellings clustering
Flexible loads
Residential users
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/57547
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