The construction of a usable, formal, and extensible modeller and simulator for Smart Energy Grids is of a paramount importance in the industrial settings. Final users are interested in deploying effective smart-home configurations able to satisfy energy requests in the most economical way. Hence, a tool able to forecast both energy consumption and related costs of a smart-home configuration is needed. In this paper, the μGRIMOIRE (micro GRId MOdelling envIRonmEnt) toolset is presented. This tool is based on the well-known model-driven paradigm and its successful applications in the generation of formal/quantitative models for complex systems. By using a Domain Specific Modelling Language, a final user can define a smart-home system configuration and energy saving logics. Then, the tool offers the possibility of evaluating the desired user metrics by translating the model into a Fluid Stochastic Petri Net model representing both discrete and continuous variables.
µGRIMOIRE: A Tool for Smart Micro Grids Modelling and Energy Profiling / Gentile, Ugo; Marrone, Stefano; Mazzocca, Nicola; Nardone, Roberto. - In: THE OPEN CYBERNETICS & SYSTEMICS JOURNAL. - ISSN 1874-110X. - 10:1(2016), pp. 263-282. [10.2174/1874110X01610010263]
µGRIMOIRE: A Tool for Smart Micro Grids Modelling and Energy Profiling
Nardone, Roberto
2016-01-01
Abstract
The construction of a usable, formal, and extensible modeller and simulator for Smart Energy Grids is of a paramount importance in the industrial settings. Final users are interested in deploying effective smart-home configurations able to satisfy energy requests in the most economical way. Hence, a tool able to forecast both energy consumption and related costs of a smart-home configuration is needed. In this paper, the μGRIMOIRE (micro GRId MOdelling envIRonmEnt) toolset is presented. This tool is based on the well-known model-driven paradigm and its successful applications in the generation of formal/quantitative models for complex systems. By using a Domain Specific Modelling Language, a final user can define a smart-home system configuration and energy saving logics. Then, the tool offers the possibility of evaluating the desired user metrics by translating the model into a Fluid Stochastic Petri Net model representing both discrete and continuous variables.File | Dimensione | Formato | |
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