CASE STUDY: Data links Covid-19 lockdowns to consumption change
公用事业
Coronavirus Covid-19
欧洲
2020年4月23日星期四

CASE STUDY: Data links Covid-19 lockdowns to consumption change

Producing real-time information

家庭工作,学校关闭和社会限制增加对全球数百万人产生重大影响。

由Covid-19流行病影响的另一个区域是耗水量。

A recent analysis was carried out on water consumption pattern changes in the city of Karlsruhe, Germany.

This showed how Covid-19 related societal changes are directly impacting when and how much water people are consuming.

A rise in the number of Covid-19 cases in early March prompted the German government to take further measures.

在巴登 - 符腾堡州的状态下,学校于3月17日关闭,其他措施逐步增强,以限制更多的社会活动和公共生活。

水实用程序Stadtwerke Karlsruhe(Swka)在巴登 - 符腾堡州的国家提供超过400,000名居民的地区。

Using the WatEner Platform from the Spanish company, the Inclam Group, SWKA integrated measured and simulated data from different sources, producing information in real-time.

通过在3月期间连续四个星期二进行比较,显示锁定措施之前和之后,可以观察到水消耗的变化。

CASE STUDY: Data links Covid-19 lockdowns to consumption change

在遏制措施(蓝线)和放学后和社会限制(绿线)之前,观察到消费行为的变化(图2)。

推迟高峰用水需求

“The slope of consumption curve at the beginning of the day is higher under normal situation (before Covid-19 measures) and lower after the measures were adopted, with a demand peak that occurred approximately two hours later,” said Jorge Helmbrecht, general manager at WatEner (Inclam Group).

此外,早晨的需求峰值也在锁定条件下延迟。

如下所示(图3),3月初,需求峰值发生在第一种情况下,大约7.10 AM,当学校在正常行为期间开放时。

然而,在之后的星期一th, this shifts to 9.40 am under lockdown measures, which is more akin to consumption behaviour during the weekends.

据总经理说,耗水量也在一天的过程中展开,更多的人留在家里。

“在禁闭的情况下,消费在早上逐渐分布,慢慢减少,直到下午,”他补充道。

CASE STUDY: Data links Covid-19 lockdowns to consumption change

Impacts on forecast demand

Water utilities around the world are积极沟通在Covid-19大流行周围,甚至声称他们的劳动力97%are working remotely.

So what does the data from this analysis mean for the German water utility?

The Demand Forecast System (DFS) used applies Artificial Intelligence (AI) and Pattern Recognition Techniques, adapting to meteorological parameters, as well as changes in consumer behaviour.

通过分析“精灵”od March 1-24, the AI system adjusts to the changing pattern in consumption behaviour caused by the Covid-19 emergency.

简而言之:随时调整需求预测。

“The system can adapt quickly to the new consumption patterns, providing a precise demand forecast using algorithms without the need for manual inputs," adds Helmbrecht.

CASE STUDY: Data links Covid-19 lockdowns to consumption change

The first day of school closing and lockdown measures (March 17) shows a steeper slope in the forecasted demand (as expected in a typical Tuesday of March) than the real demand.

经过一周(星期二,3月24日),DFS有更多信息来自动调整对新的消费者行为的预测,显示出类似于真正需求的更平滑的坡度和曲线形状。

Helmbrecht concludes that despite the recognised patterns, more data is still needed and he is working on a more detailed study.

“A more in-depth analysis and more data are probably needed to draw wider conclusions on demand changes related to the Covid-19 lockdown situation,” he said.


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