Efficient production and reliable availability of electricity requires comprehensive understanding of load demand trends to plan and match production with consumption. Although electricity demand depends on a combination of cultural and economic conditions, weather conditions remain as the major driver. With increased capabilities of accurate predictions of weather, the importance of investigating and quantifying its impact on electricity demand becomes obvious. The electrical system in Jordan has been facing several challenges including the failure to respond to increased demands induced by extreme temperatures. This paper covers a clear gap in literature through presenting a detailed investigation of the electricity consumption trends and in identifying the susceptibility of these trends to weather. This study relies on the statistical processing and analysis, through modeling of hourly electricity demands in Jordan in the period of 10 years between 2007 and 2016. Actual weather data was used employing the degree-day approach. The monthly, daily, and hourly seasonal variation indices were determined. Optimally formulated piecewise functions were used to track the thermal comfort zone and rate of increase in electricity demand for temperatures beyond it for each year. Moreover, the elasticity of polynomial functions was adopted to identify saturation points to thermally map the electricity consumption. The developed models successfully described the relationship between the daily electricity demand and the mean daily ambient temperature. The average comfort zone width was 4 °C and the average mean base temperature was 17.9 °C. The sensitivity of electricity demand to both high and low temperatures has increased on average, with 11% and 16.4% to hot and cold weather, respectively. Finally, the electricity demand in cooling was found to saturate at 32.9 °C, whereas it saturates for heating at 4.7 °C. The electricity demand in Jordan observes seasonal trends in a consistent and predictable manner. An optimally formulated piecewise function successfully tracked the thermal comfort zone and the rate of increase in electricity demand for temperatures beyond it for each year of the study period. Finally, saturation heating and cooling temperatures were acquired from the elasticity of the daily electricity demands modeled against daily HDD and CDD.

中文翻译：

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调查约旦的电力需求趋势及其对周围空气温度的敏感性，以实现可持续发电

有效的生产和可靠的电力供应需要对负荷需求趋势有全面的了解，以计划生产和消耗。尽管电力需求取决于文化和经济条件的结合，但天气条件仍然是主要驱动因素。随着对天气的准确预测能力的增强，调查和量化其对电力需求影响的重要性变得显而易见。约旦的电气系统一直面临数项挑战，包括无法应对极端温度引起的不断增长的需求。本文通过对用电量趋势进行详细调查并确定这些趋势对天气的敏感性，从而弥补了文献中的明显空白。这项研究依靠统计处理和分析，通过对约旦在2007年至2016年之间的10年间每小时用电需求进行建模。使用度数日方法使用了实际天气数据。确定了每月，每天和每小时的季节性变化指数。使用最佳公式化的分段函数来跟踪热舒适区以及每年超过此温度的用电需求的增长率。此外，采用多项式函数的弹性来识别饱和点以热绘制电力消耗。所开发的模型成功地描述了每日电力需求与平均每日环境温度之间的关系。平均舒适区宽度为4°C，平均平均基准温度为17.9°C。电力需求对高温和低温的敏感度平均提高了，对炎热和寒冷天气的敏感性分别为11％和16.4％。最后，发现冷却中的电力需求在32.9°C时达到饱和，而在4.7°C的加热时达到饱和。约旦的电力需求以一致且可预测的方式观察季节趋势。最优公式化的分段函数成功地跟踪了研究期间每一年的热舒适区和超过该温度的用电需求的增长率。最后，根据针对每日HDD和CDD建模的每日电力需求的弹性来获取饱和加热和冷却温度。分别。最后，发现冷却中的电力需求在32.9°C时达到饱和，而在4.7°C的加热时达到饱和。约旦的电力需求以一致且可预测的方式观察季节趋势。最优公式化的分段函数成功地跟踪了研究期间每一年的热舒适区和超过该温度的用电需求的增长率。最后，根据针对每日HDD和CDD建模的每日电力需求的弹性来获取饱和加热和冷却温度。分别。最后，发现冷却中的电力需求在32.9°C时达到饱和，而在4.7°C的加热时达到饱和。约旦的电力需求以一致且可预测的方式观察季节趋势。最优公式化的分段函数成功地跟踪了研究期间每一年的热舒适区和超过该温度的用电需求的增长率。最后，根据针对每日HDD和CDD建模的每日电力需求的弹性来获取饱和加热和冷却温度。最优公式化的分段函数成功地跟踪了研究期间每一年的热舒适区和超过该温度的用电需求的增长率。最后，根据针对每日HDD和CDD建模的每日电力需求的弹性来获取饱和加热和冷却温度。最优公式化的分段函数成功地跟踪了研究期间每一年的热舒适区和超过该温度的用电需求的增长率。最后，根据针对每日HDD和CDD建模的每日电力需求的弹性来获取饱和加热和冷却温度。