کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4928185 1432014 2017 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic programming and genetic algorithms to control an HVAC system: Maximizing thermal comfort and minimizing cost with PV production and storage
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Dynamic programming and genetic algorithms to control an HVAC system: Maximizing thermal comfort and minimizing cost with PV production and storage
چکیده انگلیسی
The genetic algorithm model that uses EnergyPlus to simulate indoor temperature generally achieves higher convergence to the optimal value, which also is the one that uses more electricity from the PV system to operate the HVAC. The dynamic programming performs better than the genetic algorithm (both coupled with STM). However, it is limited by the fact that uses STM, which is a less accurate model to simulate indoor temperature especially because it is not considering thermal inertia.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sustainable Cities and Society - Volume 34, October 2017, Pages 228-238
نویسندگان
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