Scenario-based sensitivity analysis of energy dynamic behavior in residential buildings with radiant floors
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2017Subject/s
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Abstract
This paper addresses the problem of thermal energy efficiency in domestic buildings. As opposed to classic optimal approach, a sensitivity analysis and comparison have been performed to evaluate both comfort and consumption of different heating scheduling, corresponding to different user-oriented scenarios, which allows to derive basic operating rules. Also continuous and discontinuous heating strategies are compared. The various scenarios are evaluated for different building thermal properties and different climatic conditions, under a classic mixed PID and hysteresis control scheme. The case study here considered is a house heated through a radiant floor system. A new index of assessment of user?s comfort is also proposed. This paper explores the importance of heating scheme in terms of comfort and energy saving and highlights the importance of the decision maker point of view when deciding the most appropriate heating strategy. An optimal control strategy is also implemented (model-based predictive control) for comparison.
This paper addresses the problem of thermal energy efficiency in domestic buildings. As opposed to classic optimal approach, a sensitivity analysis and comparison have been performed to evaluate both comfort and consumption of different heating scheduling, corresponding to different user-oriented scenarios, which allows to derive basic operating rules. Also continuous and discontinuous heating strategies are compared. The various scenarios are evaluated for different building thermal properties and different climatic conditions, under a classic mixed PID and hysteresis control scheme. The case study here considered is a house heated through a radiant floor system. A new index of assessment of user?s comfort is also proposed. This paper explores the importance of heating scheme in terms of comfort and energy saving and highlights the importance of the decision maker point of view when deciding the most appropriate heating strategy. An optimal control strategy is also implemented (model-based predictive control) for comparison.





