Household energy behavior in Nordic countries—an unrealized energy saving potential

Energy ◽  
1988 ◽  
Vol 13 (12) ◽  
pp. 853-859 ◽  
Author(s):  
J. Owens ◽  
H. Wilhite
Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7634
Author(s):  
Jin Zhang ◽  
Lianrui Ma ◽  
Jinkai Li

Low-carbon knowledge is seen as having a key role in interfering with household energy consumption behaviors by wide consensus from political and academic areas. Whether low-carbon publicity will help to reduce household energy consumption is still in dispute. By constructing an integrated knowledge-intention-behavior model and using 1335 detailed survey questionnaires of household energy behavior in Henan Province, the central area in China, this paper finds that in the developing area low-carbon knowledge or publicity cannot positively impact household energy-saving behavior even if mediated by energy awareness and energy-saving attitudes. Low-carbon knowledge does improve energy-saving attitude and attitude does not decrease household energy consumption directly. Familiarity with particular energy-saving knowledge would decrease the household energy consumption but not significantly in the statistics. Path analysis unfolds the reason that the heterogeneous effects of purchase-based intention and habitual intention explain energy consumption behavior. Subgroup analysis supports those economic factors of income and energy prices play key roles in explaining such household energy consumption behavior in the rapid urbanization area. This paper gives new evidence on the residential energy-saving behavior intervention among developing areas.


Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5581 ◽  
Author(s):  
Shi-Yi Song ◽  
Hong Leng

Accurate simulation and prediction of occupants’ energy use behavior are crucial in building energy consumption research. However, few studies have focused on household energy use behavior in severely cold regions that have unique energy use patterns because of the low demand of cooling in summer and the use of central heating system in winter. Thus, we developed an agent-based model to simulate the household electricity use behavior in severely cold regions, according to data for Harbin, China. The model regards apartments, residents, household appliances, and energy-management departments as agents and generates the household electricity consumption with respect to time, temperature, and energy-saving events. The simulation parameters include basic information of the residents, their energy-saving awareness, their appliance use behaviors, and the impact of energy-saving management. Electricity use patterns are described by decision-making mechanisms and probabilities obtained through a questionnaire survey. In the end, the energy-saving effects of different management strategies are evaluated. The results indicate that the model can visually present and accurately predict the dynamic energy use behavior of residents. The energy-saving potential of household electricity use in severely cold regions is mainly concentrated in lighting and standby waste, rather than cooling and heating, since the cooling demand in summer is low and the heating in winter mainly relies on central heating system of the city, not on household electricity appliances. Energy-saving promotion can significantly reduce the amount of energy waste (41.89% of lighting and 97.79% of standby energy consumption), and the best frequency of promotional events is once every four months. Residents prefer incentive policies, in which energy-saving effect is 57.7% larger than that of increasing electricity prices. This study realized the re-presentation of the changes of energy consumption in a large number of households and highlighted the particularity of household energy-saving potential in severely cold regions. The proposed model has a simple structure and high output accuracy; it can help cities in severely cold regions formulate energy-saving management policies and evaluate their effects.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 81
Author(s):  
Rongjiang Ma ◽  
Shen Yang ◽  
Xianlin Wang ◽  
Xi-Cheng Wang ◽  
Ming Shan ◽  
...  

Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method through observation, test, and identification (OTI) has several drawbacks such as time consumption and narrow focus. To overcome these problems, this study proposed a systematic method for energy-saving diagnosis in air-conditioning systems based on data mining. The method mainly includes seven steps: (1) data collection, (2) data preprocessing, (3) recognition of variable-speed equipment, (4) recognition of system operation mode, (5) regression analysis of energy consumption data, (6) constraints analysis of system running, and (7) energy-saving potential analysis. A case study with a complicated air-conditioning system coupled with an ice storage system demonstrated the effectiveness of the proposed method. Compared with the traditional OTI method, the data-mining-based method can provide a more comprehensive analysis of energy-saving potential with less time cost, although it strongly relies on data quality in all steps and lacks flexibility for diagnosing specific equipment for energy-saving potential analysis. The results can deepen the understanding of the operating data characteristics of air-conditioning systems.


2021 ◽  
Vol 293 ◽  
pp. 116854
Author(s):  
Yunyang Ye ◽  
Yan Chen ◽  
Jian Zhang ◽  
Zhihong Pang ◽  
Zheng O’Neill ◽  
...  

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