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" Token based scheduling for energy management in building HVAC systems,"Īpplied Energy, Elsevier, vol. Radhakrishnan, Nikitha & Su, Yang & Su, Rong & Poolla, Kameshwar, 2016." Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method,"Īpplied Energy, Elsevier, vol. Kim, Wonuk & Jeon, Yongseok & Kim, Yongchan, 2016." Energy conservation in museums using different setpoint strategies: A case study for a state-of-the-art museum using building simulations,"Īpplied Energy, Elsevier, vol. In the cooling season, LSH-SPM reduced the HVAC system operating cost by 6.63%. LSHSDFSS-SPM reduced the HVAC system operating cost by 15.8%. Simulation results showed that in the heating season, the operating/energy cost of HVAC system decreased significantly (23.8%) by implementing SDFSS-SPM. The HVAC system energy demand as well as the corresponding saving on the HVAC system energy cost are analyzed in-depth numerically using each of the strategy planning models during both the heating and cooling seasons. In order to facilitate the implementation of the developed SPMs on the HVAC system of the house used in this case study, an advanced controller was designed by connecting both TRNSYS-Matlab programs. This study discusses the development of three different strategy planning models including Smart Dual Fuel Switching System (SDFSS), Load Shifting (LSH), and LSHSDFSS, a combination of load shifting and fuel switching SPMs. Thermal energy can be stored utilizing intelligent Strategy Planning Models (SPMs) which are applied in the heating, ventilating and air conditioning (HVAC) system as one of the largest energy consumer in RHs buildings. Demand management and energy cost saving can be achieved by taking advantage of RHs/buildings capabilities in storing thermal energy. Based on their structure, residential houses/buildings (RHs) can offer excellent opportunities for managing their internal energy demand and subsequently lowering their energy cost.