In this paper a comprehensive residential Energy Management in python, rEMpy, is presented. The framework has a modular structure and the Optimal Scheduler, featuring a task scheduling logic and a configuration structure to represent different subsystems, is the core. A dynamic configuration of the system and data visualization is allowed by the Web Interface. The required forecasts are delegated to the Prediction module. Moreover, the real-time validation of the controlled systems and devices is supported thought the Fault Diagnosis and Overload Manager modules. The cooperation among the modules and the manager capabilities are validated by performing evaluations on both tasks scheduling and storage management on real-case data.
rEMpy: a comprehensive software framework for residential energy management / Fagiani, M.; Severini, M.; Valenti, M.; Ferracuti, F.; Ciabattoni, L.; Squartini, S.. - In: ENERGY AND BUILDINGS. - ISSN 0378-7788. - 171:(2018), pp. 131-143. [10.1016/j.enbuild.2018.04.023]
rEMpy: a comprehensive software framework for residential energy management
Fagiani, M.
;Severini, M.;Valenti, M.;Ferracuti, F.;Ciabattoni, L.;Squartini, S.
2018-01-01
Abstract
In this paper a comprehensive residential Energy Management in python, rEMpy, is presented. The framework has a modular structure and the Optimal Scheduler, featuring a task scheduling logic and a configuration structure to represent different subsystems, is the core. A dynamic configuration of the system and data visualization is allowed by the Web Interface. The required forecasts are delegated to the Prediction module. Moreover, the real-time validation of the controlled systems and devices is supported thought the Fault Diagnosis and Overload Manager modules. The cooperation among the modules and the manager capabilities are validated by performing evaluations on both tasks scheduling and storage management on real-case data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
