首页> 外文会议>2014 IEEE International Conference on Intelligent Autonomous Agents, Networks and Systems >An ARCH model the electric power of extra high voltage (EHV) transmission substation forecasting in Cawang, Jakarta, Indonesia
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An ARCH model the electric power of extra high voltage (EHV) transmission substation forecasting in Cawang, Jakarta, Indonesia

机译:ARCH模型在印度尼西亚雅加达卡旺的超高压(EHV)输电变电站的电力预测

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摘要

An ARCH forecasting model for electric power demand of an EHV is proposed in this work. The power demand in EHV substation, Jakarta, Indonesia which passed through Cawang substation is continuously changed in values either normally or drastically. These electric demands were measured every 30 minutes so that there are 48 different values of electric demand that pass through a substation for one day. To distribute the power to the customers, PT Perusahaan Listrik Negara (PLN) has to determine which power plant will be used with the most optimum route and minimum operations budget. For that purpose, an ARCH modeling was applied so that the forecast power demand could be estimated. This model is applied to unveil the heteroscedasticity character of residuals with inconstant variance. In this work, MATLAB software and NUMXL were used for parameters estimation of model identification. As a result, it turns out that convergent parameter values obtained when 28 data observations were used. Therefore, the forecasting of electric power was generated in order to forecast up to ten steps ahead. This forecasting of the electric power could provide extensive and valuable information of electric power to PLN so that electric route and related budget can be optimized.
机译:本文提出了超高压电力需求的ARCH预测模型。通过Cawang变电站的印度尼西亚雅加达超高压变电站的电力需求,无论是正常值还是急剧变化的值都在不断变化。这些用电需求每30分钟测量一次,因此一天中有48种不同的用电需求值通过变电站。为了将电力分配给客户,PT Perusahaan Listrik Negara(PLN)必须确定将使用最佳路线和最小运营预算的电厂。为此,应用了ARCH模型,以便可以估算预测的功率需求。该模型用于揭示具有恒定方差的残差的异方差特征。在这项工作中,使用MATLAB软件和NUMXL进行模型识别的参数估计。结果表明,使用28个数据观测值时获得的收敛参数值。因此,生成了电力预测,以便预测最多十个步骤。电力的这种预测可以为PLN提供广泛而有价值的电力信息,从而可以优化电力路线和相关预算。

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