کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
263027 504062 2014 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Trial results from a model predictive control and optimisation system for commercial building HVAC
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Trial results from a model predictive control and optimisation system for commercial building HVAC
چکیده انگلیسی


• A novel predictive control system for commercial building heating ventilation and air-conditioning (HVAC).
• Multi-objective optimisation framework simultaneously considers energy, operating cost and occupant comfort.
• Online occupant comfort feedback helps to fine-tune occupant comfort satisfaction.
• Results presented from real-world trials have demonstrated energy improvement between 19 and 32% over existing control strategies.

This paper presents the results from two real-world trials of an optimised supervisory model predictive control (MPC) system for heating, ventilation and air conditioning (HVAC) in commercial buildings. The system learns a model from historical data and uses weather forecasts and a given temperature set-point profile to predict building zone conditions and thermal comfort with the aim of optimising building controls for a number of HVAC zones throughout a day. The multi-objective optimisation minimises running cost and CO2 emissions, subject to operator preferences, while constraining occupant thermal discomfort to an acceptable range to find the best zone temperature set-point schedule for the building. This schedule is then applied to the building by a feedback control loop, which balances the power supplied to each zone for heating, cooling and ventilation.A complementary online occupant comfort feedback tool was deployed to all occupant computers in the trial office buildings. This tool allows occupants to submit feedback on their thermal comfort and satisfaction at any point in time via electronic surveys, as well as allowing these surveys to be issued to occupants at scheduled times. This feedback fine-tuned the thermal comfort model used to constrain the optimisation, allowing for errors in the comfort model to be compensated. Thermal comfort feedback was also used to measure and compare relative occupant comfort levels with a baseline.This control system was trialled on two office buildings in Australia, over two winter months and results compared with the performance of the incumbent building management and control system (BMCS). An average energy reduction of 19% and 32% was achieved in the two buildings over 51 and 10 days of operation respectively without substantially affecting measured or modelled occupant thermal satisfaction levels.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 72, April 2014, Pages 271–279
نویسندگان
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