scholarly journals Final Report - Conservation & Renewable Energy Potential Study For Smith River Rancheria

2007 ◽  
Author(s):  
Greg Retzlaff
Keyword(s):  
Renewable Energy ◽  
Final Report ◽  
Energy Potential ◽  
Potential Study

Model Statistika Prediksi Energi Surya Dengan Menggunakan Autoregresif Integrated Moving Average (ARIMA)

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 181
Author(s):  
Imriani Moroki ◽  
Alfrets Septy Wauran
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Moving Average ◽  
Arima Model ◽  
Solar Irradiation ◽  
Energy Sources ◽  
Energy Potential ◽  
Good Design ◽  
Potential Sources ◽  
The Common

Energi terbarukan adalah salah satu masalah energi paling terkenal saat ini. Ada beberapa sumber potensial energi terbarukan. Salah satu energi terbarukan yang umum dan sederhana adalah energi matahari. Masalah besar ketersediaan energi saat ini adalah terbatasnya sumber energi konvensional seperti bahan bakar. Ini semua sumber energi memiliki banyak masalah karena memiliki jumlah energi yang terbatas. Penting untuk membuat model dan analisis berdasarkan ketersediaan sumber energi. Energi matahari adalah energi terbarukan yang paling disukai di negara-negara khatulistiwa saat ini. Tergantung pada produksi energi surya di daerah tertentu untuk memiliki desain dan analisis energi matahari yang baik. Untuk memiliki analisis yang baik tentang itu, dalam makalah ini kami membuat model prediksi energi surya berdasarkan data iradiasi matahari. Kami membuat model energi surya dan angin dengan menggunakan Metode Autoregresif Integrated Moving Average (ARIMA). Model ini diimplementasikan oleh R Studio yang kuat dari statistik. Sebagai hasil akhir, kami mendapatkan model statistik solar yang dibandingkan dengan data aktualRenewable energy is one of the most fomous issues of energy today. There are some renewable energy potential sources. One of the common n simple renewable energy is solar energy. The big problem of the availability of energy today is the limeted sources of conventional enery like fuel. This all energy sources have a lot of problem because it has a limited number of energy. It is important to make a model and analysis based on the availability of the energy sources. Solar energy is the most prefered renewable energy in equator countries today. It depends on the production of solar energy in certain area to have a good design and analysis of  the solar energy. To have a good analysis of it, in this paper we make a prediction model of solar energy based on the data of solar irradiation. We make the solar and wind enery model by using Autoregresif Integrated Moving Average (ARIMA) Method. This model is implemented by R Studio that is a powerfull of statistical. As the final result, we got the statistical model of solar comparing with the actual data

Assessment of bioenergy development potential in agricultural enterprises

2020 ◽  
pp. 165-171
Author(s):  
Iryna Hryhoruk
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
Agricultural Waste ◽  
General Structure ◽  
Geographical Location ◽  
Economic Assessment ◽  
Energy Resources ◽  
Industrial Complex ◽  
Renewable Energy Resources ◽  
Energy Potential

Exhaustion of traditional energy resources, their uneven geographical location, and catastrophic changes in the environment necessitate the transition to renewable energy resources. Moreover, Ukraine's economy is critically dependent on energy exports, and in some cases, the dependence is not only economic but also political, which in itself poses a threat to national security. One of the ways to solve this problem is the large-scale introduction and use of renewable energy resources, bioenergy in particular. The article summarizes and offers methods for assessing the energy potential of agriculture. In our country, a significant amount of biomass is produced every year, which remains unused. A significant part is disposed of due to incineration, which significantly harms the environment and does not allow earning additional funds. It is investigated that the bioenergy potential of agriculture depends on the geographical distribution and varies in each region of Ukraine. Studies have shown that as of 2019 the smallest share in the total amount of conventional fuel that can be obtained from agricultural waste and products suitable for energy production accounts for Zakarpattya region - 172.5 thousand tons. (0.5% of the total) and Chernivtsi region - 291.3 thousand tons. (0.9%). Poltava region has the greatest potential - 2652.2 thousand tons. (7.8%) and Vinnytsia - 2623.7 thousand tons. (7.7%). It should be noted that the use of the energy potential of biomass in Ukraine can be called unsatisfactory. The share of biomass in the provision of primary energy consumption is very small. For bioenergy to occupy its niche in the general structure of the agro-industrial complex, it is necessary to develop mechanisms for its stimulation. In addition, an effective strategy for the development of the bioenergy sector of agriculture is needed. The article considers the general energy potential of agriculture, its indicative structure. The analysis is also made in terms of areas. In addition, an economic assessment of the possible use of existing potential is identified.

scholarly journals A Study on the Characteristics of Academic Topics Related to Renewable Energy Using the Structural Topic Modeling and the Weak Signal Concept

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1497
Author(s):  
Chankook Park ◽  
Minkyu Kim
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Topic Modeling ◽  
Academic Research ◽  
High Rate ◽  
Weak Signals ◽  
Energy Potential ◽  
Rate Of Increase ◽  
Probabilistic Topic Modeling ◽  
To Receive

It is important to examine in detail how the distribution of academic research topics related to renewable energy is structured and which topics are likely to receive new attention in the future in order for scientists to contribute to the development of renewable energy. This study uses an advanced probabilistic topic modeling to statistically examine the temporal changes of renewable energy topics by using academic abstracts from 2010–2019 and explores the properties of the topics from the perspective of future signs such as weak signals. As a result, in strong signals, methods for optimally integrating renewable energy into the power grid are paid great attention. In weak signals, interest in large-capacity energy storage systems such as hydrogen, supercapacitors, and compressed air energy storage showed a high rate of increase. In not-strong-but-well-known signals, comprehensive topics have been included, such as renewable energy potential, barriers, and policies. The approach of this study is applicable not only to renewable energy but also to other subjects.

scholarly journals Agricultural Residue Management for Sustainable Power Generation: The Poland Case Study

2021 ◽  
Vol 11 (13) ◽  
pp. 5907
Author(s):  
Valerii Havrysh ◽  
Antonina Kalinichenko ◽  
Anna Brzozowska ◽  
Jan Stebila
Keyword(s):  
Power Generation ◽  
Spatial Distribution ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Agricultural Waste ◽  
Energy Utilization ◽  
Evaluation Methodology ◽  
Energy Sources ◽  
Energy Potential ◽  
Agricultural Residue

The European Union has set targets for renewable energy utilization. Poland is a member of the EU, and its authorities support an increase in renewable energy use. The background of this study is based on the role of renewable energy sources in improving energy security and mitigation of climate change. Agricultural waste is of a significant role in bioenergy. However, there is a lack of integrated methodology for the measurement of its potential. The possibility of developing an integrated evaluation methodology for renewable energy potential and its spatial distribution was assumed as the hypothesis. The novelty of this study is the integration of two renewable energy sources: crop residues and animal husbandry waste (for biogas). To determine agricultural waste energy potential, we took into account straw requirements for stock-raising and soil conservation. The total energy potential of agricultural waste was estimated at 279.94 PJ. It can cover up to 15% of national power generation. The spatial distribution of the agricultural residue energy potential was examined. This information can be used to predict appropriate locations for biomass-based power generation facilities. The potential reduction in carbon dioxide emissions ranges from 25.7 to 33.5 Mt per year.

Review on Renewable Energy Potential in Australian Subtropical Region (Central and North Queensland)

2011 ◽  
Vol 347-353 ◽  
pp. 3846-3855 ◽  
Author(s):  
Ali Baniyounes ◽  
Gang Liu ◽  
M. G. Rasul ◽  
M. M. K. Khan
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Spatial Databases ◽  
Cost Effective ◽  
Climatic Conditions ◽  
Energy Resources ◽  
Climatic Data ◽  
Renewable Energy Resources ◽  
Subtropical Region ◽  
Energy Potential

In Australia the future demand for energy is predicted to increase rapidly. Conventional energy resources soaring prices and environmental impact have increased the interest in renewable energy technology. As a result of that the Australian government is promoting renewable energy; such as wind, geothermal, solar and hydropower. These types of energy are believed to be cost-effective and environmentally friendly. Renewable energy availability is controlled by climatic conditions such as solar radiation, wind speed and temperature. This paper aims to assess the potential of renewable energy resources, in particular wind and solar energy in an Australian subtropical region (Central and North Queensland) namely, Gladstone, Emerald, Rockhampton, Yeppoon, Townsville, and Cairns. Analysis is done by using the latest statistical state of Queensland energy information, along with measured data history of wind speed, solar irradiations, air temperature, relative humidity, and atmospheric pressure for those sites. This study has also shown that national assessments of solar and wind energy potential can be improved by improving local climatic data assessments using spatial databases of Central and North Queensland areas.

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