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"Quantitative information about solar radiation in agro-forestry system in Indonesia is relatively limited. To study the amount of solar radiation below forest trees stand, a survey based research was conducted from october 2002 to February 2003 in Central Java, Indonesia. The location of the survey were chosen based on the kinds of trees forests. They were Purwodadi (teak, mahogany and sonokeling production forest), Karanganyer- Purworejo (pines production forest) and Klaten (semolina and yucca as conservation forest). The decrease in the relative's Irradiation Fraction (RIF) under the trees was found realted to the increased of the tree aging, adjusted to the exponential decrease model (RIF=1.25e -0,18 x). The RIF under tree canopy was clearly explained by diameter on the breast height diameter of trunk (DBH) divided by the half of tree row spacing (2D/(X+Y) therefore the RIF was formulated as e 0.2829 (2D/(X+Y)."

"Quantitative information about solar radiation in agro-forestry system in Indonesia is relatively limited. To study the amount of solar radiation below forest trees stand, a survey based research was conducted from October 2002 to February 2003 in Central Java, Indonesia. The location of the survey were chosen based on the kinds of trees and forests. They were Purwodadi (teak, mahogany and sonokeling production forest), Karanganyar - Purworejo (pines production forest), and Klaten (semolina and yucca as conservation forest). The decrease in the Relative's Irradiation Fraction (RIF) under the trees was found related to the increased of the tree aging, adjusted to the exponential decrease model (RIP=1.25e -0.18 X). The RIP under tree canopy was clearly explained by diameter on the breast height diameter of trunk (DBH) divided by the half of tree row spacing (2D/X+Y) therefore the RIF was formulated as 0.2829 (2D/(X+Y)."

"Research has been carried out for designing and construction of solar radiation concentration by using array of mirrors. A solar water heater is used to demonstrate the usefulness of such solar radiation concentration."

"Provinsi Jawa Barat memiliki potensi yang signifikan untuk pengembangan energi surya melalui pemanfaatan radiasi matahari. Penelitian ini bertujuan untuk mengestimasi radiasi matahari di Provinsi Jawa Barat menggunakan metode ANN untuk menemukan model konfigurasi optimal dan menganalisis distribusi spasialnya. Pengukuran radiasi matahari dilakukan di lima lokasi berbeda, dengan dua lokasi terbaik dipilih untuk pemrosesan data. Dataset yang digunakan adalah data tahun 2022, yang dibagi menjadi 70% untuk pelatihan dan 30% untuk pengujian. Hasilnya menunjukkan bahwa konfigurasi optimal 6-30-1 di lokasi Puslitbang PLN mencapai nilai RMSE sebesar 135,8 W/m², rRMSE sebesar 54,8%, MBE sebesar 15,9 W/m², dan rMBE sebesar 0,064%. Sementara itu, untuk lokasi Sumedang, konfigurasi optimal adalah 5-40-1, yang menghasilkan nilai RMSE sebesar 156,7 W/m², rRMSE sebesar 49,29%, MBE sebesar 7,75 W/m², dan rMBE sebesar 0,024%. Secara keseluruhan, model ini masih memiliki kesalahan estimasi sebesar 48-50%.Untuk meningkatkan akurasi, penelitian ini mengintegrasikan model ANN dengan WRF, yang mampu meningkatkan akurasi di Sumedang sebesar 2%. Analisis menunjukkan bahwa daerah dengan ketinggian rendah memiliki intensitas radiasi matahari yang tinggi, sedangkan daerah dengan ketinggian lebih tinggi menerima radiasi matahari yang lebih rendah

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West Java Province has significant potential for solar energy development through the utilization of solar radiation. This study aims to estimate solar radiation in West Java Province using ANN methods to find the optimal configuration model and analyze its spatial distribution. Solar radiation measurements were conducted at five different locations, with the two best locations selected for data processing. The dataset used is from the year 2022, which was divided into 70% training and 30% testing. The results showed that the optimal configuration of 6-30-1 at the Puslitbang PLN location achieved an RMSE value of 135.8 W/m², an rRMSE of 54.8%, an MBE of 15.9 W/m², and an rMBE of 0.064%. Meanwhile, for the Sumedang location, the optimal configuration was 5-40-1, which produced an RMSE value of 156.7 W/m², an rRMSE of 49.29%, an MBE of 7.75 W/m², and an rMBE of 0.024%. Overall, this model still has an estimation error of 48-50%. To improve accuracy, this study integrated the ANN model with WRF, which was able to increase accuracy in Sumedang by 2%. Analysis shows that low-altitude areas have high solar radiation intensity, while higher-altitude areas receive lower solar radiation."

"Automatic Weather Station (AWS) mengalami kendala berupa kerusakan komponen dan kegagalan sistem komunikasi, sehingga menyebabkan data parameter tidak lengkap. Kerusakan komponen juga terjadi pada pyranometer. Penurunan kinerja pyranometer menghasilkan penyimpangan, ketidakpastian pengukuran intensitas radiasi matahari, serta gap data. Imputasi data menjadi salah satu solusi dalam meminimalisir penyimpangan pengukuran dan terjadinya missing data pyranometer AWS. Penelitian ini bertujuan mendesain serta menganalisis performa akurasi model imputasi data intensitas radiasi matahari pyranometer AWS multisite ketika terjadi gap data. Penelitian ini berupaya memanfaatkan kaitan spasio-temporal intensitasi radiasi matahari AWS multisite di dalam model imputasi. Algoritma Long-Short Term Memory (LSTM) digunakan sebagai estimator pada jaringan pyranometer AWS multisite. Tahap pemodelan imputasi data meliputi pengumpulan data, pra-pemrosesan data, pembuatan skenario missing data, desain LSTM dan pengujian model. Metode berbasis machine learning ini diharapkan mampu mengimputasi data AWS pada missing data dalam jangka menit maupun jam, jika AWS mengalami kerusakan sistem atau gangguan jaringan komunikasi. Nilai MAPE model LSTM untuk imputasi pyranometer AWS Cikancung untuk missing data 30 menit, 1 jam dan 3 jam berturut-turut yaitu 1,81% ; 2,72% ; dan 5,07%. Nilai MAPE model LSTM untuk AWS Cimalaka untuk missing data 30 menit, 1 jam dan 3 jam berturut-turut yaitu 0,46% ; 1,25% ; dan 3,24%. Nilai MAPE model LSTM untuk AWS Cipasung untuk missing data 30 menit, 1 jam dan 3 jam berturut-turut yaitu 2,30% ; 1,67% ; dan 0,94%.

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Automatic Weather Station (AWS) experienced problems in the form of component damage and communication system failure, resulting in incomplete parameter data. Component damage also occurs in pyranometers. Decreased pyranometer performance results in deviations, uncertainty in measuring solar radiation intensity, and data gaps. Data imputation is one solution to minimize measurement deviations and the occurrence of missing AWS pyranometer data. This research aims to design and analyze the accuracy performance of the multisite AWS pyranometer solar radiation intensity data imputation model when a data gap occurs. This research attempts to utilize the spatio-temporal relationship of multisite AWS solar radiation intensity in the imputation model. The Long-Short Term Memory (LSTM) algorithm is used as an estimator in the multisite AWS pyranometer network. The data imputation modeling stage includes data collection, data pre-processing, creating missing data scenarios, LSTM design and model testing. This machine learning-based method is expected to be able to impute AWS data for missing data in minutes or hours, if AWS experiences system damage or communication network disruption. The MAPE value of the LSTM model for the AWS Cikancung pyranometer for missing data of 30 minutes, 1 hour and 3 hours respectively is 1.81%; 2.72% ; and 5.07%. The MAPE value of the LSTM model for AWS Cimalaka for missing data of 30 minutes, 1 hour and 3 hours respectively is 0.46%; 1.25% ; and 3.24%. The MAPE value of the LSTM model for AWS Cipasung for missing data of 30 minutes, 1 hour and 3 hours respectively is 2.30%; 1.67% ; and 0.94%."

"Sesuai tren dan perkembangan teknologi sekarang, penerapan PLTS yang berbasis pada energi surya sebagai Energi Baru Terbarukan (EBT) di Indonesia kian hari kian meningkat. Menurut Rencana Usaha Penyediaan Tenaga Listrik (RUPTL) PT PLN Tahun 2021-2030, potensi energi surya di Indonesia relatif tinggi sebesar 207.898 MW dan potensi ini merupakan potensi terbesar dibandingkan EBT lain. Namun keberadaan energi surya bersifat intermittent karena dipengaruhi oleh banyak faktor misalnya cuaca dan awan, sehingga mempengaruhi energi listrik dan kualitas daya keluaran dari PLTS. Studi ini bertujuan untuk menganalisis pengaruh radiasi matahari terhadap kualitas daya sistem distribusi listrik dan menganalisis variasi besaran - besaran tegangan fasa, arus fasa, daya aktif, daya reaktif, daya semu, Total Distorsi Harmonik Tegangan (THDV), Total Distorsi Harmonik Arus (THDI), dan Total Distorsi Permintaan (TDD) yang terjadi. Berdasarkan hasil pengukuran secara langsung yang dilaksanakan pada Gedung Energi Puspitek dengan studi objek PLTS Rooftop On Grid 90 kWp, pengaruh radiasi surya terhadap perubahan - perubahan nilai yang relatif tidak signifikan adalah tegangan fasa, THDv dengan nilai rata - rata secara berurutan, yaitu 0,37%; 1,97% saat kenaikan radiasi matahari serta 0,29%; 2,19% saat penurunan radiasi matahari. Dan perubahan - perubahan nilai yang sangat signifikan adalah arus fasa, daya aktif, daya reaktif, daya semu, THDi, TDD dengan nilai rata rata masing - masing 89,13%; 89,98%; 89,91%; 89,97%; 32,10%; 17,08% saat kenaikan radiasi matahari serta 37,61%; 37,79%; 37,79%; 39,59%; 14,33% saat penurunan radiasi matahari.

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In accordance with current trends and technological developments, the application of PLTS based on solar energy as New Renewable Energy "EBT" in Indonesia is increasing day by day. According to PT PLN's 2021-2030 Electric Power Supply Business Plan (RUPTL), the potential for solar energy in Indonesia is relatively high at 207,898 MW and this potential is the largest potential compared to other EBT. However, the existence of solar energy is intermittent because it is influenced by many factors such as weather and clouds, thus affecting electrical energy and the quality of the output power of PLTS. This study aims to analyze the effect of solar radiation on the power quality of the electrical distribution system and analyze variations in the magnitudes of phase voltage, phase current, active power, reactive power, apparent power, Total Harmonic Distortion of Voltage (THDV), Total Harmonic Distortion of Current (THDI), and Total Demand Distortion (TDD) that occurred. Based on the results of direct measurements carried out at the Puspitek Energy Building with a 90 kWp Rooftop On Grid PLTS object study, the effect of solar radiation on changes in values that are relatively insignificant is the phase voltage, THDv with an average value sequentially, namely 0,37 %; 1,97% when the increase in solar radiation and 0,29%; 2,19% when the decrease in solar radiation. And very significant changes in values are phase current, active power, reactive power, apparent power, THDi, TDD with an average value of 89,13% each; 89,98%; 89,91%; 89,97%; 32,10%; 17,08% when solar radiation increases and 37,61%; 37,79%; 37,79%; 39,59%; 14,33% when the solar radiation decreases."