With the increased share of renewables in power generation, end users play a key role in keeping the demand at levels that better match variable supply, maintaining lower overall system costs, and reducing carbon dioxide emissions. To increase the potential for demand-side flexibility, a deeper understanding of domestic electricity load profiles is needed. Informed by customer grouping based on similar consumption patterns and drivers, targeted interventions can be better designed to time-shift peak loads and reduce overall demand. Thus, the objectives of this study are (i) to segment households in relation to their electricity load patterns using K-means clustering and (ii) to investigate household characteristics that have an influence on electricity load patterns by employing multinomial probit regression. This study uses hourly electricity consumption for 2017, combined with population-based register data for a large sample of Danish households. The results indicate that four distinct Danish household groups are characterized by different timing and magnitudes of electricity consumption, which are influenced by specific sociodemographics and dwelling characteristics. Similarities between the groups emerge with respect to the evening peak consumption, seasonal variation in electricity demand, and weekend morning demand ramp-up. Challenges and opportunities for domestic load profiling in the power industry and policymaking are discussed.

随着可再生能源在发电中所占份额的增加，最终用户在保持需求水平以更好地适应可变电力供应，保持较低的整体系统成本以及减少二氧化碳排放方面发挥着关键作用。为了增加需求侧灵活性的潜力，需要对家庭用电负荷状况有更深入的了解。通过基于相似的消费模式和驱动因素的客户分组，可以更好地设计针对性的干预措施，以时移高峰负荷并减少总体需求。因此，本研究的目标是（i）使用K-means聚类将家庭与其电力负荷模式相关，以及（ii）通过采用多项式概率回归来研究对电力负荷模式有影响的家庭特征。这项研究使用2017年的每小时用电量，结合大量丹麦家庭的基于人口的登记数据。结果表明，四个不同的丹麦家庭群体的特征是用电的时间和幅度不同，这受特定的社会人口统计学和居住特征的影响。两组之间在夜间高峰用电量，电力需求的季节性变化以及周末早晨的需求增加方面存在相似之处。讨论了电力行业中进行家庭负荷分析和制定政策的挑战和机遇。结果表明，四个不同的丹麦家庭群体的特征是用电的时间和幅度不同，这受特定的社会人口统计学和居住特征的影响。两组之间在夜间高峰用电量，电力需求的季节性变化以及周末早晨的需求增加方面存在相似之处。讨论了电力行业和政策制定中家庭负荷分析的挑战和机遇。结果表明，四个不同的丹麦家庭群体的特征是用电的时间和幅度不同，这受特定的社会人口统计学和居住特征的影响。两组之间在夜间高峰用电量，电力需求的季节性变化和周末早晨的需求增加方面存在相似之处。讨论了电力行业和政策制定中家庭负荷分析的挑战和机遇。