![]() ![]() Based on the actual requirements of decision-makers and using the weight method, three design schemes focusing on different performance tendencies are proposed. In this way, Pareto solutions are obtained and the value distributions of the multi-objectives and design parameters are analyzed. The NSGA-II algorithm is adopted to conduct the multi-parameter, multi-objective optimization design for rural houses in Hanzhong area, through coupling of the EnergyPlus and MOBO software. Then, the mutually restricted indices of total energy consumption and initial investment cost are taken as optimization objectives, and 17 design parameters are selected as the optimization variables. The action mechanisms of passive design parameters, including the building orientation, length–width ratio, building envelope parameters, external shading system, and window–wall ratio, on heating, cooling, and total energy consumption are analyzed, and the quantitative relationships between single-parameter and energy consumption are established. In this paper, taking Hanzhong region (Shaanxi Province, China) as an example, we establish a benchmark model based on a field survey and develop an optimization process by combining EnergyPlus simulation software, the MOBO optimization engine, and weighted sum method. ![]() To remedy this, appropriate passive design strategies should be adopted first, in order to provide a design mode with low energy consumption and low cost for rural residences under the premise of thermal comfort. The rural residences of Northwest China are characterized by a state of high energy consumption and low comfort due to the limited economic level and awareness of energy-saving compared with the urban residences. Moreover, utilizing intermittent heating is more effective than continuous heating in demonstrating the positive impacts of envelope renovation on increasing average temperature, decreasing temperature differences and lowering occupied time at low thermal comfort levels. According to the comparison results, cost-optimal solutions have significant advantages in both reductions of LCC and CO2 emissions over standard-based solutions. The LCC with intermittent heating is still 7% greater than its pre-renovation case, which may require external financial support to encourage the renovation conduction, while the LCC with continuous heating decreased by 8% after renovation. The results indicate that the cost-optimal renovation solutions with intermittent and continuous heating can cut CO2 emissions by 30% and 40%, respectively. Simulation-based multi-optimization analysis was conducted in this study using the building simulation tool IDA ICE and its integrated optimization tool AutoMOO. A single-family detached rural house in Harbin was used as a case building, illustrating the typical state of comparable houses in this climate context. This study presents the cost-optimal envelope renovation solutions with the minimized lifecycle cost (LCC) during a 20-year discount period and CO2 emissions of annual delivered energy consumptions. ![]() The intermittent operation and manual regulation of these systems result in significant temperature differences and inadequate thermal comfort. ![]() The local traditional heating methods include Chinese Kangs and coal boilers with water-based radiators. High heating expenses are observed in numerous Chinese rural houses located in severe cold regions due to the high heating demand, inferior envelope performance and low-efficiency heating equipment. ![]()
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