首页> 外文期刊>AIMS Energy >Applying Johansen VECM cointegration approach to propose a forecast model of photovoltaic power output plant in Reunion Island
【24h】

Applying Johansen VECM cointegration approach to propose a forecast model of photovoltaic power output plant in Reunion Island

机译:应用约翰逊VECM协整方法提出荷兰岛光伏电力输出厂的预测模型

获取原文
           

摘要

Since 2007 Reunion Island, a French overseas region located in the Indian Ocean, aims to achieve energy self-sufficiency by 2030. The French government has made this insular zone an experimental territory for renewable energy resources (RES) by implementing great powers photovoltaic (PV) plants. However, the performance of PV conversion is highly climate dependent, and there have been many research contributions to show that the two main factors that influence PV cell efficiency are solar radiation and cell temperature. Moreover, considering the high variability of environmental factors on PV plants, the high penetration of PV in electric systems may threaten the stability and reliability of the electrical power grid. In this study, a linear relation analysis of time series data collected over one year is performed in order to investigate the dependent variable of PV power output from explanatory variables such as solar irradiance, cell temperature, wind speed and humidity. The originality of this paper is to apply cointegration methods, usual tools of econometrics, to PV systems. More precisely, this research work lies in the use a robust statistical method to model a vector cointegrating relationship linking the PV power output and the four environmental parameters mentioned above, to make accurate forecasts in a tropical area. The Johansen vector error correction model (VECM) cointegration approach is used to determine the most appropriate PV power output forecasting when the desired model is concerned with N explanatory variables and for N 2. This long run equilibrium relationship has been tested over many years of data and the outcome is more than reliable when comparing the model to measured data.
机译:自2007年以来,位于印度洋的法国海外地区重聚岛,旨在将能源自给自足于2030年。法国政府通过实施大力光伏(PV)为可再生能源(RES)的实验领域进行了这一欧洲实验领域) 植物。然而,PV转换的性能是高度气候依赖性,并且已经有许多研究贡献表明影响光伏电池效率的两个主要因素是太阳辐射和细胞温度。此外,考虑到光伏设备上的环境因素的高变异性,电力系统中PV的高渗透可能威胁到电力电网的稳定性和可靠性。在这项研究中,执行一年内收集的时间序列数据的线性关系分析,以研究PV功率输出从解释性变量,例如太阳辐照度,细胞温度,风速和湿度等变量。本文的原创性是应用协整方法,通常的经济学工具,以PV系统。更确切地说,该研究工作在于使用稳健的统计方法来模拟连接光伏电源输出和上述四个环境参数的矢量协整关系,以便在热带区域进行准确的预测。 Johansen Vector纠错模型(VECM)协整方法用于确定所需模型涉及N个解释变量的最合适的PV功率输出预测,并且对于N> 2。这种长期的均衡关系已经过多年数据和结果在将模型与测量数据进行比较时比较可靠。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号