基于模糊的住宅用电量预测人类行为模型

M. Alrizq, E. de Doncker
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引用次数: 1

摘要

当涉及到扩张计划时,电力公司对负荷概况(电力消耗)数据很感兴趣。随着智能电网和分布式能源概念的发展,对负荷剖面数据的需求对电网规划的重要性日益突出。收集负荷剖面数据的传统方法,如调查和计量,是非常繁琐和耗时的活动。消费者的需求以及持续的技术发展导致数据在短时间内被淘汰。此外,繁琐的数据收集过程也构成障碍。在本文中,我们提出了一个创新的行为模型,以产生电力消耗负荷分布。我们的模型需要最少的消费者数据,并且可以很容易地更新以适应不断变化的技术。我们用真实世界的数据来证明我们的模型的准确性。
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A novel fuzzy based human behavior model for residential electricity consumption forecasting
Electric utility companies are interested in load profile (electricity consumption) data when it comes to expansion planning. With the evolution of the smart grid and distributed energy resource concepts, the requirement of load profile data for planning has become critical. Conventional methods of collecting the load profile data, such as surveys and metering, are very tedious and time consuming activities. Consumer demand, as well as continuous technological evolution, contribute to rendering data obsolete in a short period of time. Furthermore, cumbersome data collection processes also pose barriers. In this paper, we present an innovative behavior model for generating electricity consumption load profiles. Our model requires minimum consumer data and can be easily updated to adapt to the changing technology. We demonstrate the accuracy of our model against real world data.
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