A Bottom-Up Weather-Sensitive Residential Demand Model for Developing Countries

We develop a novel method method to estimate unsuppressed demand for developing countries. A bottom-up approach is employed using socioeconomic data and a time-of-use database developed from a householder survey. This is used to simulate household activity profiles that are converted into electrical load time series by simulating electrical appliance use. Reanalysis weather data is used in the simulation of ambient conditions for the generation of cooling demand profiles. The time series model is validated against results of a small-scale residential metering trial and is shown to be a credible research tool for electrical demand studies in developing countries that have power networks constrained by intermittent load management program. An illustrative analysis presents regional and national peak load estimates for a range of appliance ownership scenarios that demonstrates the value added by the model.本研究提出一种新颖方法，用于估算发展中国家的未抑制电力需求。研究采用自下而上方法（bottom-up approach），整合社会经济数据与基于住户调查（householder survey）构建的用电时段数据库（time-of-use database）。依托该数据库模拟住户活动时序特征，并通过模拟家用电器使用行为，将其转化为电力负荷时间序列。本研究使用再分析气象数据（reanalysis weather data）模拟环境条件，以生成制冷需求曲线。所提出的时间序列模型通过小型住宅计量试验的结果进行验证，结果表明，对于电力网络受间歇性负荷管理计划（intermittent load management program）约束的发展中国家而言，该模型是开展电力需求研究的可靠工具。通过示例分析，本研究针对多类家电保有率场景估算了区域及全国峰值负荷，直观展示了该模型的附加应用价值。