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Effect of Day-ahead Forecasts on Curtailment Planning of PV Power in Japan

机译:日前预报对日本光伏发电削减计划的影响

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The objective of this study is to evaluate the effect that the accuracy of day-ahead forecasts of photovoltaic, PV, power generation has on forecast based curtailment of PV power. Two main regions of Japan were targeted, Kanto, which has a high potential for installations of roof-top PV systems; and Kyushu, which already has high levels of PV power penetration. To provide a qualitative measure of the importance of accurate PV forecasts with different levels of PV power generation, for each region, 2 penetration scenarios were assumed. One year of regional and day-ahead forecasts of PV power were done using numerical weather prediction data, support vector regression, and measured PV power generation data. The PV power generation data comes from to a set of 52 PV systems in Kyushu and to a set of 62 PV systems located in Kanto. The curtailment of PV power was planned one day ahead of time, using the PV power forecasts and a method based on residual loads. The results show that with current day-ahead forecasts it is possible to correctly predict the hours when curtailment will occur most of the time. For example, for Kyushu, curtailment was properly detected 83.1% of the time in a scenario of 8.64 GW of PV installed. For Kanto the values were between 73% and 80.5%. Regarding the effect of the forecast error, we found that it annualy represents near to 35% of the amount curtailed, indicating the importance of improvement of day-ahead forecasts in the curtaiment problem. Finally, the study shows that the relation between the months and hours of curtailment with the period of high forecast errors is crutial to the efficient use of the forecasts, and must be considered before using the forecasts to plan curtailment.
机译:本研究的目的是评估光伏,光伏发电的日期预测的准确性对PV电力的预测预测的效果。日本的两个主要地区是针对性的,Kanto是屋顶PV系统的安装很高的潜力;和九州已经拥有高水平的光伏电源渗透。为了提供具有不同水平的PV发电量的精确PV预测的定性衡量标准,对于每个区域,假设2个渗透方案。使用数值天气预报数据,支持向量回归和测量的PV发电数据,完成了一年的区域和日期的PV电力预测。光伏发电数据来自九州的一套52个光伏系统,以及位于卡托的一组62个PV系统。使用PV功率预测和基于残留负荷的方法,计划提前一天的PV电力缩减。结果表明,随着当前的一天预测,有可能正确预测缩减大部分时间的时间。例如,对于九州来说,缩减在安装8.64 GW的PV中的情况下被正确检测到83.1%。对于Kanto,价值在73%和80.5%之间。关于预测误差的影响,我们发现IT年度涉及缩减金额的35%,表明在凝视问题中改善日前预测的重要性。最后,该研究表明,在高预测误差期间缩减的月份和时间之间的关系是对预测的有效利用,并且必须在利用预测计划缩减之前进行审议。

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