This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochastic programming approach over a deterministic formulation.

Dealing with the stochastic prosumager problem with controllable loads

Beraldi Patrizia
Conceptualization
;
Carrozzino Gianluca
Software
2023-01-01

Abstract

This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochastic programming approach over a deterministic formulation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/330768
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