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Modelling and forecasting hourly electricity demand in West African countries

机译:西非国家的每小时电力需求建模与预测

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The Economic Community of West African States aims to achieve 100% electrification rates by 2030 in all member countries. To achieve this ambitious target, electricity generation capacities need to be increased significantly. Forecasting hourly electricity demand is imperative for capacity planners in optimizing investment options and ensuring reliable electricity supply. However, modelling hourly electricity demand in developing countries can be a challenge due to paucity of historical demand data and methodological frameworks that adequately capture technology transitions and urban-rural communities. In this study, we address this gap by developing an hourly electricity demand model for 14 West African countries in the year 2016 and 2030. The model takes into account electrification rates, available household appliances, occupancy patterns of household members, type of day, available daylight hours and hourly weather conditions. Annual electricity demand in non-residential sectors and electricity access rates in urban and rural households are forecasted using multiple regression analysis. We validated the developed model using actual 2016 monthly and annual electricity demand data. The results show the seasonal variations of electricity demand, with hourly electricity demand in dry seasons relatively higher than demand in wet seasons. The results also indicate that in 2030, electricity demand in the West African region is estimated to be five times its 2016 level. The methodology presented in this study can be applicable for modelling hourly electricity demand in developing countries that have scarce historical hourly demand data, a significant electricity supply-demand gap, and varying electricity access rates in urban and rural areas.
机译:西非国家的经济共同体旨在在所有成员国到2030年实现100%的电气化率。为实现这种雄心勃勃的目标,需要大幅增加发电能力。预测每小时电力需求对于能力规划者在优化投资选择和确保可靠的电力供应方面是必不可少的。然而,由于历史需求数据和方法论框架的缺乏充分捕获技术过渡和城乡社区,建模在发展中国家的每小时电力需求可能是一个挑战。在这项研究中,我们通过开发2016年和2030年的14个西非国家的每小时电力需求模型来解决这一差距。该模型考虑了电气化率,可用的家用电器,家庭成员的入住模式,一天的类型,可用日光小时和每小时天气状况。使用多元回归分析预测了城乡家庭的非住宅行业和电力访问率的年度电力需求。我们使用2016年每月和年电费数据验证了开发的模型。结果表明,电力需求的季节性变化,在干燥季节中的每小时电力需求相对高于潮湿季节的需求。结果还表明,2030年,西非地区的电力需求估计是2016年级别的五倍。本研究中提出的方法可适用于在发展中国家在缺乏历史时空需求数据,大量电力供需差距和城市和农村地区的电力访问率不同的情况下进行建模的每小时电力需求。

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