LIFE-CYCLE ASSESSMENT AND LIFE-CYCLE COST AS COLLABORATIVE TOOLS IN RESIDENTIAL HEATING SYSTEM SELECTION

Typically the selection of a residential heating system focuses on first costs rather than the economic or environmental life cycle consequences.The use of life cycle assessment and life cycle cost methodologies in the design phase provide additional criteria for consideration when selecting a residential heating system.A comparative case study of a gas forced air and radiant solar heating system was conducted for a 3,000 square foot house located in Fort Collins,Colo­rado,U.S.A.The initial results of an analysis of the life cycle assessment and the life cycle cost data indicated the gas forced air system was superior,both environmentally and economically.Further data analysis pinpointed solar radi­ant system components for replacement in an effort to reduce both life cycle environmental emissions and costs.This analysis resulted in a hybrid radiant system using a high-efficiency gas-fired boiler,a choice that lowered both the solar radiant system’s costs and emissions.This new system had slightly lower environmental impacts than both the gas forced air system and solar radiant system.Unfortunately the hybrid system had less impact on the life cycle cost with the hybrid system substantially more expensive then the gas-forced air alternative.

Optimal Scheduling of Residential Heating, Ventilation and Air Conditioning Based on Deep Reinforcement Learning

Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.

Test and Analysis of Indoor Thermal Environment of Urban Heating Residential Building in Hanzhong Area

By testing indoor and outdoor thermal environment of residential buildings that apply 4 mostused heating ways in Hantai District,Hanzhong City,this paper explored the indoor thermal environment conditions of different heating ways,to provide references for choosing a suitable heating way in the local area.

Feasibility of Hybrid Wind and Solar Energy System for Heating Residential Buildings in Amman-Jordan

A design of a solar-wind electrical hybrid system to supply space heating requirements for a 1,200 m^2 residential building in Amman-Jordan was implemented. The building heating requirements were estimated from existing heating building data based on traditional heating design already adopted by engineering firms in Jordan. The traditional heating load was transferred into electrical load to be supplied by hybrid system. The hybrid system consists of a 75 kW vertical axis windmill and 140 solar modules. Because of the high cost of land in residential buildings, the hybrid system is to be installed on the building roof. The hybrid system and the conventional systems＇ cost were found to be compatible in four years period when oil prices reach $100 per barrel. As the international price of oil rises above $100 per barrel, the proposed hybrid system becomes more economical than the already existing hot water heating system.