Transforming the Nicaraguan energy mix towards 100% renewable

Meza, Carlos; Amado, Nilton Bispo; Sauer, Ildo Luís

doi:10.1016/j.egypro.2017.10.234

Cited by 13 publications

(2 citation statements)

References 9 publications

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“…If it seems unfair to compare ASEAN to the EU, one can instead compare it to emerging economies in other parts of the world. Nicaragua stands out for aiming to make a leap from a 50% share of renewables in the power mix in 2013 to 90% in 2020 [62] . Even more impressively, the Guatemalans aim for an 80% share of renewables, in a country where fossil fuels made up 85% of electricity generation capacity less than a decade ago [63] .…”

Section: Renewable Energymentioning

confidence: 99%

The ASEAN climate and energy paradox

Øverland

Sagbakken

Chan

et al. 2021

Energy and Climate Change

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This article carries out a multisectoral qualitative analysis (MSQA) and policy integration analysis of six sectors important for climate mitigation in Southeast Asia in order to assess the status of the climate-energy nexus in the region. It concludes that Southeast Asia will be heavily affected by climate change but the mitigation efforts of the member states of the Association of Southeast Asian Nations (ASEAN) are incommensurate with the threat they face. Their nationally determined contributions under the Paris Agreement are modest, they have a low proportion of renewable energy in their energy mixes, a modest target for raising the share of renewable energy and they are not likely to reach this target. The ASEAN countries have also been slow to adopt electric vehicles and to accede to the International Renewable Energy Agency (IRENA), while continuing to burn their forests, channel subsidies to fossil fuels and invest in new coal power plants. If ASEAN accelerated decarbonization, it could seize business opportunities, secure its standing in the international political system and climate justice discussions, and increase its chances of reaching the United Nations Sustainable Development Goals (SDGs).

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Section: Renewable Energymentioning

confidence: 99%

The ASEAN climate and energy paradox

Øverland

Sagbakken

Chan

et al. 2021

Energy and Climate Change

View full text Add to dashboard Cite

show abstract

“…Megura and Gunderson [5], Chiari and Zecca [6], Braungardt et al [7] and Zecca and Chiari [8] have highlighted the positive impact of fossil fuel usage on global warming, and it has been estimated that the mean temperature of the world will be increased by 1.2 °C in 2100 in comparison with 2000, due to the carbon dioxide emissions in the production of electricity from fossil fuels. On the other hand, according to Tutak and Brodny [9], Poudyal et al [10], Pietrosemoli and Rodríguez-Monroy [11] and Meza et al [12] the consumption of electricity produced by RES has a positive effect on a country's economic development and in solving the problem of the energy crisis.…”

Section: Introductionmentioning

confidence: 99%

On the Usage of Artificial Neural Networks for the Determination of Optimal Wind Farms Allocation

Xenitidis,

Ioannou,

Tsantopoulos

et al. 2023

Sustainability

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Worldwide energy demand is constantly increasing. This fact, in combination with the ever growing need to reduce the energy production footprint on the environment, has led to the adoption of cleaner and more sustainable forms of energy production. Renewable Energy Sources (RES) are constantly developing in an effort to increase their conversion efficiency and improve their life cycle. However, not all types of RES are accepted by the general public. Wind Turbines (WTs) are considered by many researchers as the least acceptable type of RES. This is mostly because of how their installation alters the surrounding landscape, produces noise and puts birds in danger when they happen to fly over the installation area. This paper aims to apply a methodology which, by using Rational Basis Function Neural Networks (RBFNN), is capable of investigating the criteria used for the installation locations of WTs in a transparent way. The results from the Neural Network (NN) will be combined with protected areas and the Land Fragmentation Index (LFI), in order to determine possible new installation locations with increased social acceptance and, at the same time, increased energy production. A case study of the proposed methodology has been implemented for the entire Greek territory, which is considered one of the most suitable areas for the installation of wind farms due to its particular geomorphology.

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Quantitative Import and Export Restrictions

Frey¹

2022

World Trade Law and the Emergence of International Electricity Markets

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Transforming the Nicaraguan energy mix towards 100% renewable

Cited by 13 publications

References 9 publications

The ASEAN climate and energy paradox

The ASEAN climate and energy paradox

On the Usage of Artificial Neural Networks for the Determination of Optimal Wind Farms Allocation

Quantitative Import and Export Restrictions

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