发展中国家和新兴工业化国家电力负荷预测方法研究进展:建立有效负荷预测模型的倡议

H. Bakiri, N. Mvungi, Hamisi Ndyetabura, L. Massawe, Hellen Maziku
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引用次数: 0

摘要

发展中国家和新兴工业化国家的现有研究仅仅分析了负荷需求预测的方法,很少强调考虑数据质量、提供研究议程和提出负荷预测的设计架构。因此,本文调查了来自18个DNI国家的22篇文章,试图研究负荷预测方法和数据清理机制,然后为这些国家提出了一个通用的设计框架。本研究采用系统评价方案,以获得公正和科学的研究结果。经济增长、客户数量、电价、温度、日历事件和白天被发现是电力消耗的重要驱动因素。此外,研究结果表明,63.64%的负荷预测机制考虑了异常值去除预处理。本文指出了与DNI国家的负荷预测有关的问题,这样就可以高效地建立一个适合上下文的稳健模型。
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Review on the State of the Art of Electricity Load Forecasting Methodologies in Developing and Newly-Industrialised Countries: An Initiative to Establish an Effective Load Forecasting Model
Existing studies in Developing and Newly-Industrialised (DNI) countries merely analysed the load demand forecasting methodologies, with little emphasis on consideration of data quality, provision of research agenda and the proposition of the design architecture of load forecasting. Therefore, this paper surveys 22 articles from 18 DNI countries, attempting to investigate the load forecasting methodologies as well as data cleansing mechanisms, and then proposes a general design framework for these countries. A systematic review protocol is applied in this study to achieve unbiased and scientific-based findings. Economic growth, number of customers, price of electricity, temperature, calendar events, and daytime found to be significant drivers of electricity consumption. Furthermore, the findings indicate that 63.64% of the surveyed load forecasting mechanisms considered the inclusion of outlier-removal preprocessors. This paper has pinpointed the issues pertaining to load forecasting in the DNI countries such that a robust model, fitting a context can be built with efficiency.
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