Improvement of Coding for Solar Radiation Forecasting in Dili Timor Leste—A WRF Case Study

This paper investigates the accuracy of weather research and forecasting by improving coding for solar radiation forecasting for location in Dili Timor Leste. Weather Research and Forecasting (WRF) model version 3.9.1 is used in this study for improvement purposes. The shortwave coding of WRF is used to improve in order to decrease error simulation. The importance of improving WRF coding at a specific region will reduce the bias and root mean square root when comparing to the observed data. This study uses high resolution based on the WRF modeling to stabilize the performance of forecasting. The decrease in error performance will be expected to enhance the value of renewable energy. The results show the root mean square error of the WRF default is 233 W/m2 higher compared to 205 W/m2 from the WRF improvement model. In addition, the Mean Bias Error (MBE) of the WRF default is obtained value 0.06 higher than 0.03 from the WRF improvement in rainy days. Meanwhile, on sunny days, the performance Root Mean Square Error (RMSE) of WRF default is 327 W/m2 higher than 223 W/m2 from the WRF improvement. The MBE of WRF improvement obtained 0.13 lower compared to 0.21 of WRF default coding. Finally, this study concludes that improving the shortwave code under the WRF model can decrease the error performance of the WRF simulation for local weather forecasting.

A Case Study: Performance Comparison of Solar Power Generation between GridLAB-D and SAM in Dili Timor Leste

Study of comparison of solar power generation between the GridLAB-D tool and System Advisor Model (SAM) in Dili, Timor Leste is presented in this paper. Weather Research and Forecasting (WRF) model is used to simulate solar radiation for one calendar year from January to December 2014 using six-hourly interval 1° × 1° NCEP FNL analysis data. The one calendar year results from the WRF model will be used as input data for GridLAB-D and SAM to estimate the solar power generation. GridLAB-D is an open-source and analysis tool designed to operate the distribution power systems with a high-performance algorithm. System Advisor Model version SAM 2017.9.5 is used to estimate solar power performance with Photovoltaics (PVWatts)- Commercial Distributed model. This model is designed to analyze the performance and the financing of renewable energy for electricity generation. The results show the lowest solar radiation is 512 W/m2 obtained in June with an average monthly power of 20.6 kW and 30.55 kW generated from the SAM model and the GridLAB-D simulator, respectively. Meanwhile, the highest solar radiation is 1100 W/m2, 1112 W/m2, 1046 W/m2, and 1077 W/m2 obtained in October, November, December, and January with an average monthly power of 55.72 kW, 62.44 kW, 56.65 kW, and 56.97 kW from the SAM model, in the other hand, 48.89 kW, 51.31 kW, 55.51 kW, and 57.18 kW generated by the GridLAB-D. Finally, the results show that the performance of the GridLAB-D and the SAM model was quite good because both model precisely presented values are almost closest to each other. This study proposes that the results of solar output power from both methods, GridLAB-D and SAM can be used to design grid-connected or stand-alone electric power projects to increase the quality of electricity generation in Dili, Timor Leste.

Combination of WRF Model and LSTM Network for Solar Radiation Forecasting—Timor Leste Case Study

A study of a combination of Weather Research and Forecasting (WRF) model and Long Short Term Memory (LSTM) network for location in Dili Timor Leste is introduced in this paper. One calendar year’s results of solar radiation from January to December 2014 are used as input data to estimate future forecasting of solar radiation using the LSTM network for three months period. The WRF model version 3.9.1 is used to simulate one year’s solar radiation in horizontal resolution low scale for nesting domain 1 × 1 km. It is done by applying 6-hourly interval 1º × 1º NCEP FNL analysis data used as Global Forecast System (GFS). LSTM network is applied for forecasting in numerous learning problems for solar radiation forecasting. LSTM network uses two-layer LSTM architecture of 512 hidden neurons coupled with a dense output layer with linear as the model activation to predict with time steps are configured to 50 and the number of features is 1. The maximum epoch is set to 325 with batch size 300 and the validation split is 0.09. The results demonstrate that the combination of these two methods can successfully predict solar radiation where four error metrics of mean bias error (MBE), root mean square error (RMSE), normalized MBE (nMBE), and normalized RMSE (nRMSE) perform small error distribution and percentage in three months prediction where the error percentage is obtained below the 20% for nMBE and nRMSE. Meanwhile, the error distribution of RMSE is obtained below 200 W/m2 and maximum bias error is 0.07. Finally, the values of MBE, RMSE, nMBE, and nRMSE conclude that the good performance of the combination of two methods in this study can be applied to simulate any other weather variable for local necessary.

for fear(that)与lest有何区别?

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谈英语中几个状语从句的分类

语法学家多把forfearthat、lest以及某些情况下incase引导的从句归类为目的状语从句,本文旨在通过语义和例证分析论证forfearthat引导的从句为原因状语从句;lest和incase引导的从句在某些情况下亦应归类为原因状语从句。

Verification of option parity relations in domestic warrants market of China

This paper screens five pairs of call walTants/put warrants with the same listing date and final exercise date from domestic delisted wattant, and collects and processes relevant statistic in warrant market and stock market. Because inconformity of strike price between call warrants/put warrants in domestic warrant market, and regarding the strike price of put warrants as standard, this paper takes advantage of BSM formula recalculates the price of call warrants, and carries out verification of option parity relations by regression analysis and Wilcoxon＇s Sign Rank Test. From a theoretical point of view, homogenous call warrants/put warrants should satisfy the parity relations. However, due to the lack of short sales mechanism in domestic warrant market and stock market, the empirical results indicate that domestic warrant market can＇ t meet the option parity relations.

鸟儿歌唱、蜜蜂歌唱,甚至树也歌唱

在自然、科学和技术的帮助下,塞莱斯特·布尔西耶-穆热诺教会世界去唱歌。在上周五,尽管还在忙于筹备参加第56届威尼斯双年展的项目,但塞莱斯特·布尔西耶-穆热诺（Celeste BoursierMougenot）仍然有意识地待在法国南部的家中,进行他的日常生活。从信号并不清楚的手机通话中,我得知他正全神贯注于去城里买一些鸡,作为他儿子6岁生日的食材（他的另外三个孩子都是女儿）。他愉快地透露了一个秘密，蛋糕——尽管并非他亲手烘焙——的形状将会是一只长颈鹿。

如何辨析FOR FEAR THAT，LEST，IN CASE引导的状语从句

笔者在教学工作中发现,很多学生关于for fear that；lest和 in case引导的状语从句含糊不清,不知它们的从句如何辨析,也把握不好其中的判断标准。本文通过语义和例证分析,结合笔者自己的教学实践,浅谈对 for fear that,lest 以及 in case的理解。

集成者

在早前的2月,当很多人还在为威尼斯双年展苦苦准备的时候,Céleste Boursier-Mougenot正在法国南部家里全神贯注地为他六岁儿子的生日party做准备,捉土鸡,做蛋糕极其放松。对于54岁的Céleste Boursier-Mougenot来说,生活、艺术和思想是一致的,非独立的。Céleste Boursier-Mougenot是一个各种学科的集成者。他的工作包含了科学、技术、动物和植物。这一定程度上与他的家庭背景有关。

聆听生命的苏醒 雅克德罗早春腕表

春天是万物复苏的美好时节,早春的阳光温和明媚,大地绿草如茵。古往今来,多少文人骚客因迷恋芳春的丽景而谱写出一首首佳作。此刻,雅克·德罗(Jaquet Droz)带您聆听自然界的美妙福音,以充满诗意及想象力的构图为您呈现超凡写意之作。

摇滚鸟和它们的音乐

我想提出的问题是,究竟什么才是音乐？你能想象一只只飞鸟变身摇滚吉他手,弹奏起动人的音乐吗？这件由法国声音艺术家塞莱斯特·布希耶-穆杰诺（Céleste BoursierMougenot）创作的《从这里入耳》（From Here to Ear）再一次让我们思考音乐该如何产生,我们又该如何与音乐产生互动。在这次别开生面的场景装置个展中,穆杰诺将画廊空间转变成为一座可以供观众直接走入其中的大鸟笼,70只小鸟自由翱翔其间。＂鸟笼＂的地面被沙石覆盖,陈列着电吉他、乐架和音箱,