PREVOS-DZ: A Short-Mid Term Algerian Electric Load Forecasting Software

M. T. Khadir, N. Farah, K. Farfar, N. Bendaoud, A. Ameyoud, N. Tenzer
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引用次数: 2

Abstract

Electricity demand is nowadays a very important development factor for growing economies. In order to support daily electrical demand and meet the customer daily needs, electricity and companies operators must rely on powerful and precise forecasting tools. PREVEOS-DZ was designed and implemented in order to predict Short and Midterm electrical energy and power demand in order to plan day to day production planning as well as yearly electrical development established by the Algerian Operator System. The software is based, on the multiple regression approach as well as Artificial Neural Networks, especially for power forecasting, offering models in both paradigms. The Forecast strategy is implemented not only for global national forecast but also for regional demands, even if the electrical grid is fully connected. PREVOS-DZ is implemented using C # and allows full compatibility with Excel tabular, used mostly by the System Operator. The results of PREVELOS-DZ obtained as a prevision exercise were validated on data from 2018 and presented in this paper.
PREVOS-DZ:阿尔及利亚中短期电力负荷预测软件
如今,电力需求是发展中经济体的一个非常重要的发展因素。为了支持日常电力需求和满足客户的日常需求,电力和公司运营商必须依靠强大而精确的预测工具。PREVEOS-DZ的设计和实施是为了预测短期和中期的电能和电力需求,从而规划日常的生产计划以及由阿尔及利亚运营商系统制定的年度电力发展。该软件基于多元回归方法和人工神经网络,特别是用于功率预测,提供两种范式的模型。预测策略不仅适用于全球国家预测,也适用于区域需求,即使电网完全连接。PREVOS-DZ是使用c#实现的,并允许与Excel表格完全兼容,主要由系统操作符使用。PREVELOS-DZ作为预演得到的结果在2018年的数据上进行了验证,并在本文中提出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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