This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions. This toolbox serv...
详细信息
ISBN:
(纸本)9781509041688
This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions. This toolbox serves as a developer platform that includes a graphical user interface, a model database, a computational engine, and an input-output database. The model database consists of home appliance models, energy storage models, baseload models, roof-top photovoltaic models, as well as typical weather profiles. The graphical interface allows the users to select different inputs such as utility rate structure, customer comfort settings, solar profiles, and outdoor temperature profiles. The HEM algorithms serve as the computational engines to power the virtual house so that the performance of those algorithms can be evaluated fairly using the same set of inputs and models. Simulation results have demonstrated the effectiveness of the modeling platform when developing HEM algorithms.
This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions. This toolbox serv...
详细信息
ISBN:
(纸本)9781509041695
This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions. This toolbox serves as a developer platform that includes a graphical user interface, a model database, a computational engine, and an input-output database. The model database consists of home appliance models, energy storage models, baseload models, roof-top photovoltaic models, as well as typical weather profiles. The graphical interface allows the users to select different inputs such as utility rate structure, customer comfort settings, solar profiles, and outdoor temperature profiles. The HEM algorithms serve as the computational engines to power the virtual house so that the performance of those algorithms can be evaluated fairly using the same set of inputs and models. Simulation results have demonstrated the effectiveness of the modeling platform when developing HEM algorithms.
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