Analysis of Japan's Long-Term Energy Outlook Considering Massive Deployment of Variable Renewable Energy under Nuclear Energy Scenario

2014 ◽  
Vol 190 (2) ◽  
pp. 24-40 ◽  
Author(s):  
Ryoichi Komiyama ◽  
Yasumasa Fujii
Keyword(s):  
Renewable Energy ◽  
Nuclear Energy ◽  
Energy Scenario ◽  
Term Energy

scholarly journals Study on the production and use of biomass energy in the Timis County

2021 ◽  
Vol 26 (2) ◽  
pp. 2434-2440
Author(s):  
CRISTINA BACĂU ◽  
◽  
NICOLETA MATEOC-SÎRB ◽  
RAMONA CIOLAC ◽  
TEODOR MATEOC ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Production ◽  
Nuclear Energy ◽  
Renewable Energy Sources ◽  
Biomass Energy ◽  
Renewable Energy Resources ◽  
Continuous Increase ◽  
Fossil Energy ◽  
Term Energy

The use of renewable energy resources is gaining more and more ground, thanks to the continuous increase in the price of fossil energy and the decrease in stocks, and the management of waste from nuclear energy production, respectively. The implementation of an energy strategy to harness the potential of renewable energy sources (RES) is part of the coordinates of Romania’s medium – and long-term energy development and provides the appropriate framework for the making of decisions on energy alternatives and the inclusion in the Community acquis in the field. In this respect, a study on the biomass potential of Timiş County and on the possibilities of producing unconventional energy from biomass has been carried out. The study is based on research, data collection from the literature, as well as from official documents or official websites, the processing and interpretation of the data and their quantitative and qualitative analysis. It was concluded that biomass is a promising renewable energy source for Romania, both in terms of potential and in terms of usability.

scholarly journals Long-Term Projection of Renewable Energy Technology Diffusion

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4261 ◽  
Author(s):  
Tadeusz Skoczkowski ◽  
Sławomir Bielecki ◽  
Joanna Wojtyńska
Keyword(s):  
Renewable Energy ◽  
Technology Diffusion ◽  
Renewable Energy Sources ◽  
Unit Cost ◽  
Learning Curves ◽  
Novel Technologies ◽  
The Future ◽  
Term Energy ◽  
The Eu

The EU aims at increasing the use of renewable energy sources (RES), mainly solar-photovoltaic (PV) and wind technologies. Projecting the future, in this respect, requires a long-term energy modeling which includes a rate of diffusion of novel technologies into the market and the prediction of their costs. The aim of this article has been to project the pace at which RES technologies diffused in the past or may diffuse in the future across the power sector. This analysis of the dynamics of technologies historically as well as in modeling, roadmaps and scenarios consists in a consistent analysis of the main parameters of the dynamics (pace of diffusion and extent of diffusion in particular markets). Some scenarios (REMIND, WITCH, WEO, PRIMES) of the development of the selected power generation technologies in the EU till 2050 are compared. Depending on the data available, the learning curves describing the expected development of PV and wind technologies till 2100 have been modeled. The learning curves have been presented as a unit cost of the power versus cumulative installed capacity (market size). As the production capacity increases, the cost per unit is reduced thanks to learning how to streamline the manufacturing process. Complimentary to these learning curves, logistic S-shape functions have been used to describe technology diffusion. PV and wind generation technologies for the EU have been estimated in time domain till 2100. The doubts whether learning curves are a proper method of representing technological change due to various uncertainties have been discussed. A critical analysis of effects of the commonly applied models for a long-term energy projection (REMIND, WITCH) use has been conducted. It has been observed that for the EU the analyzed models, despite differences in the target saturation levels, predict stagnation in the development of PV and wind technologies from around 2040. Key results of the analysis are new insights into the plausibility of future deployment scenarios in different sectors, informed by the analysis of historical dynamics of technology diffusion, using to the extent possible consistent metrics.

scholarly journals Embedding power system’s reliability within a long-term Energy System Optimization Model: Linking high renewable energy integration and future grid stability for France by 2050

2020 ◽  
Vol 257 ◽  
pp. 114037 ◽  
Author(s):  
Gondia Sokhna Seck ◽  
Vincent Krakowski ◽  
Edi Assoumou ◽  
Nadia Maïzi ◽  
Vincent Mazauric
Keyword(s):  
Renewable Energy ◽  
Optimization Model ◽  
System Optimization ◽  
Energy System ◽  
Energy Integration ◽  
Renewable Energy Integration ◽  
Term Energy

An Analytical Model for Evaluating Wind Turbine Types

2014 ◽  
Vol 543-547 ◽  
pp. 333-336 ◽  
Author(s):  
Amy H.I. Lee ◽  
Meng Chan Hung ◽  
W.L. Pearn ◽  
He Yau Kang
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Evaluation Model ◽  
Renewable Energy Sources ◽  
Multiple Criteria Decision Making ◽  
Analytic Network Process ◽  
Renewable Energy Resources ◽  
Network Process ◽  
Term Energy

With worldwide developments stressing the security, economy, human well-beings and environmental costs of relying heavily on fossil and nuclear energy, the demand of safe renewable energy resources is expanding consistently and tremendously in recent years. With its safe and environmental characteristics, wind energy production has become one of the fastest growing renewable energy sources in the world. While new wind power capacity is being added in more places in various countries, the installation of wind turbines is an important process for long-term energy generation. In this study, an evaluation model, which incorporates multiple criteria decision making (MCDM) methods, including decision making trial and evaluation laboratory (DEMATEL) and fuzzy analytic network process (FANP), is developed to establish interactive relationships between criteria. Fuzzy Yager ranking method is used for deffuzification. The final ranking of the alternatives is obtained, and this can provide decision-makers for references.

Solar futures: a systematic review of long-term global solar photovoltaic adoption scenarios

2020 ◽  
Author(s):  
Marc Jaxa-Rozen ◽  
Evelina Trutnevyte
Keyword(s):  
Climate Change ◽  
Renewable Energy ◽  
Solar Photovoltaic ◽  
Energy Access ◽  
Solar Pv ◽  
Global Energy ◽  
Energy Transitions ◽  
Term Energy

<p>Solar photovoltaic (PV) technology has been the fastest-growing renewable energy technology in recent years. Since 2009, it has in fact experienced the largest capacity growth of any power generation technology, with benchmark levelized costs falling by four-fifths [1]. In addition, the global technical potential of PV largely exceeds global primary energy demand [2]. Nonetheless, PV typically only appears as a relatively marginal option in long-term energy modelling studies and scenarios. These include the mitigation pathways evaluated in the context of the work of the Intergovernmental Panel on Climate Change (IPCC), which rely on integrated assessment models (IAMs) of climate change and have in the past underestimated PV growth as compared to observed rates of adoption [2]. Similarly, global energy projections, such as the International Energy Agency's World Energy Outlook, have been relatively conservative regarding the role of solar PV in long-term energy transitions.</p><p>In order to better understand the long-term global role of solar PV as perceived by various modeling communities, this work synthesizes a broad ensemble of scenarios for global PV adoption at the 2050 horizon. This ensemble includes 784 IAM-based scenarios from the IPCC SR15 and AR5 databases, and 82 other systematically selected scenarios published over the 2010-2019 period in the academic and gray literature, such as PV-focused techno-economic analyses and global energy outlooks. The scenarios are analyzed using a descriptive framework which combines scenario indicators (e.g. mitigation policies depicted in a scenario), model indicators (e.g. the representation of technological change in the underlying model), and meta-indicators (e.g. the type of institution which authored a scenario). We extend this scenario framework to include a text-mining approach, using Latent Dirichlet Allocation (LDA) to associate scenarios with different textual perspectives identified in the ensemble, such as energy access or renewable energy transitions. We then use a scenario discovery approach to identify the combinations of indicators which are most strongly associated with different regions of the scenario space.</p><p>Preliminary results indicate that the date of publication of a scenario has a predominant influence on projected PV adoption values: scenarios published in the first half of the 2010s thus tend to represent considerably lower PV adoption levels. In parallel, higher projected values are more strongly associated with renewable-focused institutions. Increasing the institutional diversity of scenario ensembles may thus lead to a broader range of considered futures [3].</p><p> <br>References<br>[1] Frankfurt School-UNEP Centre, “Global Trends in Renewable Energy Investment 2019,” Frankfurt, Germany, 2019.<br>[2] F. Creutzig, P. Agoston, J. C. Goldschmidt, G. Luderer, G. Nemet, and R. C. Pietzcker, “The underestimated potential of solar energy to mitigate climate change,” Nat Energy, vol. 2, no. 9, pp. 1–9, Aug. 2017, doi: 10.1038/nenergy.2017.140.<br>[3] E. Trutnevyte, W. McDowall, J. Tomei, and I. Keppo, “Energy scenario choices: Insights from a retrospective review of UK energy futures,” Renewable and Sustainable Energy Reviews, vol. 55, pp. 326–337, Mar. 2016, doi: 10.1016/j.rser.2015.10.067.</p>

The role of nuclear energy system for Korean long-term energy supply strategy

1995 ◽  
Vol 29 ◽  
pp. 71-78 ◽  
Author(s):  
K.N Chae ◽  
D.G Lee ◽  
C.Y Lim ◽  
B.W Lee
Keyword(s):  
Energy Supply ◽  
Nuclear Energy ◽  
Energy System ◽  
Term Energy

An econometric study on long-term energy outlook and the implications of renewable energy utilization in Malaysia

Energy Policy ◽  
2008 ◽  
Vol 36 (2) ◽  
pp. 890-899 ◽  
Author(s):  
Peck Yean Gan ◽  
ZhiDong Li
Keyword(s):  
Renewable Energy ◽  
Energy Utilization ◽  
Term Energy ◽  
Econometric Study
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