Experimental and sensitivity analysis of a smart dual fuel system in a net-zero energy home

Tung, King; Yu, Danilo; Ekrami, Navid; Fung, Alan S.

doi:10.1088/1755-1315/238/1/012018

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…The refrigerant, having a low boiling point, passing through the evaporator, due to the low pressure created, boils, changing the aggregate state from liquid to gaseous. From the evaporator, the refrigerant gas enters the compressor, where it is compressed to a high pressure and its temperature rises [12]. Further, the heated refrigerant in a gaseous state enters the second heat exchanger, a condenser.…”

Section: Methodsmentioning

confidence: 99%

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Снежко

2019

E3S Web Conf.

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In the article the author considers one of the most important factors of life support – the creation of an energy-efficient and healthy microclimate country house through the use of complex engineering systems including the use of “passive” energy sources. Based on the results of the foreign and Russian market analysis of energy-efficient houses, the reasons for the low construction pace of such houses in Russia are estimated. A constructive engineering solution is proposed that can increase the efficiency using the modern heating, conditioning and humidification systems, thereby making them economically feasible and affordable for mass use.

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Section: Methodsmentioning

confidence: 99%

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Снежко

2019

E3S Web Conf.

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“…• To describe major energy consumers The building energy simulation model was developed [104] by using the data retrieved via this energy audit. In order to describe the efficiencies and COP, the tests were conducted exclusively for each of the HVAC equipment.…”

Section: Data Monitoring and Data Storagementioning

confidence: 99%

“…Furnace efficiency was estimated as 89% based on this energy audit. Because the thermal demand of the house strongly depends on various weather conditions at the house location, the load was correlated with outdoor temperature readings to calibrate and validate the simulation model [105]. ASHP was also tested individually to calculate its COP, which is based on the ambient temperature.…”

Section: Data Monitoring and Data Storagementioning

confidence: 99%

Cloud-based Smart Dual Fuel Switching System (SDFSS) of Hybrid Residential HVAC System for Simultaneous Reduction of Energy Cost and Greenhouse Gas Emission

Demirezen

2024

Preprint

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<p>A proper heating, ventilation, and air conditioning (HVAC) demand management system plays a prominent role in managing energy intake and taking a significant step towards sustainable housing with the goal of achieving net-zero emissions. Through experiments and simulations, this study investigated the viability of a recently developed adaptive cloud-based Smart Dual Fuel Switching Systems (SDFSSs) controller for residential hybrid HVAC systems. These systems consider various temporal parameters such as weather condition, building thermal demand, fuel price structure, and equipment capabilities into account to optimize space heating system operation, thereby lowering operating costs and greenhouse gas (GHG) emissions. Results show that by integrating SDFSS with existing ASHP technology, GHG emissions could be reduced by over 80 to 90% by 2030 with carbon pricing of $170/tonne. The results of this study could form a modelling and policy framework for different communities and regions. SDFSS would facilitate progressively and cost-effectively transitioning from existing fossil fuel-dominated heating systems to the low-carbon alternative of electric heat pumps powered by clean electricity. Due to the SDFSS’ responsiveness to the random and intermittent nature of renewable energy supply, hybrid heating systems equipped with SDFSS would facilitate wider penetration of renewable energy. Consequently, net-zero emissions could easily be achieved at a greatly accelerated pace before 2050.</p>

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Development and optimization of artificial neural network algorithms for the prediction of building specific local temperature for HVAC control

Demirezen

Fung

Deprez³

2020

Int J Energy Res

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Experimental and sensitivity analysis of a smart dual fuel system in a net-zero energy home

Cited by 4 publications

References 5 publications

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Cloud-based Smart Dual Fuel Switching System (SDFSS) of Hybrid Residential HVAC System for Simultaneous Reduction of Energy Cost and Greenhouse Gas Emission

Development and optimization of artificial neural network algorithms for the prediction of building specific local temperature for HVAC control

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