PERANCANGAN PEMBANGKIT LISTRIK TENAGA SURYA

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Ima Rochimawati

Metode penelitian yang digunakan untuk menyusun laporan ini yaitu menggunakan beberapa pendekatan dengan membuat prototyping dalam bentuk maket melalui beberapa tahap yaitu tahap Planning dan Desain dan Analisa Kebutuhan. Pada tahap planning penulis membuat sebuah perencanaan siteplan prototype sebelum tahap analisan dan selanjutnya. Dari hasil pembahasan dengan menggunakan metode pendekatan Perencanaan, Desain dan Analisa Kebutuhan didapat bahwa untuk memenuhi kebutuhan listrik di Kabupaten Demak dengan jumlah  10.000 unit rumah, power house, penerangan umum dan Industri dibutuhkan listrik 30 MW. Untuk memenuhi kebutuhan itu maka diperlukan  400.000 panel surya, 375.000 baterai,10.000 buah charge controller dengan kapasitas 300 Ampere dan 167 Buah inverter dengan kapasitas 15 Kw. Untuk kebutuhna tersebut diatas maka dibutuhkan anggaran biaya USD 60,000,000.00 (Enam Puluh Juta United States Dollar).

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Dhata Praditya

Kabupaten Demak merupakan daerah yang terletak di pulau Jawa Propinsi Jawa Tengah, merupakan salah satu daerah yang sebagian masyarakatnya belum pernah merasakan terangnya listrik seperti daerah lain di kota-kota besar di pulau Jawa. Listrik di wilyah ini belum masuk di karenakan jangkauan PLN untuk masuk kedaerah terpencil seperti Kabupaten Demak sangat sulit. Oleh karena itu penulis berinisiatif untuk merancang pembangunan pembangkit listrik tenaga surya untuk daerah tersebut. Pembangkit Listrik Tenaga Surya (PLTS) sebagai pembangkit listrik diarahkan agar dapat dimanfaatkan oleh para pemakai di daerah terpencil yang tidak mungkin dijangkau oleh jaringan PLN. Dari hasil pembahasan dengan menggunakan metode pendekatan Perencanaan, Desain dan Analisa Kebutuhan didapat bahwa untuk memenuhi kebutuhan listrik di Kabupaten Demak dengan jumlah 10.000 unit rumah, power house, penerangan umum dan Industri dibutuhkan listrik 30 MW. Untuk memenuhi kebutuhan itu maka diperlukan 400.000 panel surya, 375.000 baterai,10.000 buah charge controller dengan kapasitas 300 Ampere dan 167 Buah inverter dengan kapasitas 15 Kw. Untuk kebutuhna tersebut diatas maka dibutuhkan anggaran biaya USD 60,000,000.00 (Enam Puluh Juta United States Dollar). Analisis Investasi dari perhitungan Cash Flow menunjukkan bahwa Payback Period terjadi pada tahun ke 7. Nilai NPV adalah USD 27,125,809 dan IRR sebesar 15%. Hal ini menunjukkan bahwa investasi Pembangkit Listrik Tenaga Surya di Kabupaten Demak adalah FEASIBEL.


2011 ◽  
Vol 51 (1) ◽  
pp. 411
Author(s):  
Noll Moriarty

Accurate forecasts for medium-term commodity prices are essential for resource companies committing to large capital expenditures. The inaccuracy of conventional forecasting methods is well known because they tend to be extrapolations of the current price trend. The inevitable reversal catches many by surprise. This paper demonstrates that medium-term (2–5 years) commodity prices are not strongly linked to economic health and commodity demand-supply, but are instead inversely controlled by supply-demand for the United States dollar (USD) and consequent valuation. P90, P50 and P10 projection bounds for future valuation of the USD are presented based on the successful probabilistic techniques of the petroleum exploration industry. This allows probabilistic projections for the oil price, which is inversely related to the USD valuation. I show that the USD is significantly undervalued at present. Probabilistic projection of the USD valuation indicates that likely appreciation will put downward pressure on commodity prices for the next 2–5 years. If the USD premise is correct, likely appreciation of the dollar during the next 2–5 years will hold stable, or even decrease, oil price to around USD $50 BBL. This is a contrary expectation to most forecasts—one which, if it eventuates, should give cause for reflection before committing to large capital expenditures. Further investigation could examine the extent to which the USD valuation can be modelled as a fractal phenomenon. If so, it would mean the USD valuation is not driven by conventional economic fundamentals; instead, it is a semi-random number series with serial correlation. If true, probabilistic forecasts of the USD can be significantly improved, hence that of medium-term commodity prices.


Headline UNITED STATES: Dollar pushes up trade deficit


1953 ◽  
Vol 7 (3) ◽  
pp. 419-420

After consulting the International Monetary Fund, on unification of its exchange system, the government of Greece on April 9, 1953, eliminated all multiple currency practices and adjusted the official exchange rate from 15,000 drachmas per United States dollar to 30,000 drachmas per United States dollar. The Fund's announcement of this action by the Greek government added that it welcomed and concurred in these policies. Another proposal to adjust an official exchange rate was approved by the Fund on May 14; the government of Bolivia proposed to establish a new par value for the boliviano of 190 bolivianos per United States dollar. The previous par value was 60 bolivianos per United States dollar. At the same time a Bolivian proposal to simplify its exchange system was approved; effective May 14 the exchange system was to consist of an official and a free market. The official market would be for all trade transactions, government payments, registered capital, and certain specified invisibles. All present exchange taxes, multiple import and export rates, retention quotas, compensation and divisas propias arrangements were eliminated. The Fund welcomed these efforts toward monetary stabilization and emphasized “the importance of firm anti-inflationary measures as a basis for further progress towards the achievement of Bolivia's international equilibrium.”


2018 ◽  
Vol 7 (4.38) ◽  
pp. 1070
Author(s):  
Azim Muhammad Fahmi ◽  
Noor Azah Samsudin ◽  
Aida Mustapha ◽  
Nazim Razali ◽  
Shamsul Kamal Ahmad Khalid

In 2017, a significant number of individuals profited from the staggering growth of the price of Bitcoin from $800 USD in January to almost $20,000 USD in December. Because the cryptocurrency market being relatively new when compared to traditional markets such as stocks, foreign exchange, and gold, there is a significant lack of studies in regard to predicting its price behavior. This research is interested in evaluating a number of regression-based algorithms in predicting the price of the Bitcoin (BTC) against United States Dollar (USD). Among the algorithms that will be investigated include the Linear Regression (LR), Neural Network Regression (NNR), Bayesian Linear Regression (BLR), and Boosted Decision Tree Regression (BDTR). By applying such regression-based analysis algorithms, the findings f should further help document the behavior of such a brand new, challenging yet extremely lucrative market.  


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