Sustainable development: Case study in the implementation of renewable energy in Brazil

González, Mario Orestes Aguirre; Gonçalves, Joeberson S.; Vasconcelos, Rafael Monteiro de

doi:10.1016/j.jclepro.2016.10.052

Cited by 66 publications

(15 citation statements)

References 66 publications

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“…They also highlight the potential of renewable resources (e.g., RE) for protecting the environment. González et al (2016) studied the implementation of renewable resources to achieve sustainable development in the case of Brazil. They show that the use of renewable resources combined with effective institutions contributes to sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Nexus Between Sustainable Development and Renewable Energy: The African Perspectives

Tiba

Bélaïd

2020

Journal of Economic Surveys

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Motivated by the gained momentum of the sustainable development goals (SDGs) under the umbrella of the United Nations organization, in the light of the SDG-7, which stipulates the access to affordable, sustainable, and modern energy, this paper explores the dynamic relationship between renewable energy and the pillars of sustainable development. Its insights are driven using a simultaneous equation model based on a panel of 25 African economies covering the period 1990-2014. The results show that renewable energy is important for sustainable development and that higher levels of renewable energy can increase sustainability. The findings also confirm the positive influence of renewable energy on the economic, environmental, social, and institutional dimensions. These positive effects stem from investment in clean energy in the whole of Africa, combined with structural changes promoting the use of clean energy and the achievement of the millennium development goals. The findings should be useful for policymakers in Africa. Aggressive renewable energy policies will be crucial for achieving energy-policy goals and the "multiple benefits" of renewable energy, such as reducing climate change and air pollution, improving energy security, and increasing access to energy.

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Section: Introductionmentioning

confidence: 99%

Modeling the Nexus Between Sustainable Development and Renewable Energy: The African Perspectives

Tiba

Bélaïd

2020

Journal of Economic Surveys

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“…Authors have already depicted smart practices also in renewable energy development, yet mostly with a focus on individual renewable energy production systems and within one or similar regional contexts. For example, Wolsink (2007), He et al (2016), González et al (2017) and have focused on successful measures in the promotion of either on-shore or off-shore wind farms; Cabraal et al (1996) and Tsikalakis et al (2011) highlighted smart practices in solar schemes; and Dolman and Simmonds (2010) examined wave and tidal energy. The criterial of smart practice and negative side-effects of projects in bioenergy, biomass and biogas production have been recently explored by Ciervo andSchmitz (2017 or Martinát et al (2017).…”

Section: Theoretical Departures: From ´Best Practice´ To ´Smart Practmentioning

confidence: 99%

Spatial targeting, synergies and scale: Exploring the criteria of smart practices for siting renewable energy projects

et al. 2018

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Policies and strategies to develop renewable energy and the rates of successful deployment vary from country to country. Academic literature is rife with examples of recurring problems and malpractice in the implementation of renewable energy projects. We could see each national and sectoral effort as an 'experiment' in the early phase of our attempted transition to a low carbon energy system. What lessons can we learn from a comparative analysis of these experiments? This paper seeks to draw generic lessons not from what has gone wrong but from national case studies that stand out in a best way. Through a European academic network, we have selected and analysed 51 'smart practice' case studies of renewable energy development from 20 countries. We present the outcomes of both qualitative and quantitative analysis of these case studies (smart practice criteria) and discuss a set of generic findings concerning specific types of smart practices and problems of potential transferability of projects to other regions. With regards to policy relevance, the findings can be used for evaluating portfolios of renewable energy projects developed to date and for setting guiding principles for project design, spatial planning and consent by means of cross-national learning and fertilization.

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“…Therefore, renewable energies, such as solar energy, have proved to be feasible alternatives that enable productivity and social and environmental wellness [13]. They are abundant, clean and, above all, free [14] [15] [16], and can be used in energy generation projects in areas that are currently unused, reconciling the demand for energy and the recovery of these areas.…”

Section: Introductionmentioning

confidence: 99%

Classification of Abandoned Areas for Solar Energy Projects Using Artificial Intelligence and Quantum Mechanics

Franco¹,

Steiner²

2021

JGIS

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The increasing demand for energy has intensified recently, requiring alternative sources to fossil fuels, which have become economically and environmentally unfeasible. On the other hand, the increasing land occupation in recent centuries is a growing problem, demanding greater efficiency, particularly in the reuse of abandoned areas, which has become an alternative. An interesting alternative would be installing energy facilities like solar, wind, biomass, and geothermal, in these areas. The objective of this paper is to develop a classification methodology, based on Artificial Intelligence (AI) and Quantum Theory (QT), to automatically carry out the classification of abandoned areas suitable for the settlement of these power plants. Artificial Neural Networks (ANNs) improved by the hybrid algorithm Quantum-behaved Particle Swarm Optimization (QPSO) together with the Levenberg-Marquardt Algorithm (LMA) were used for the classification task. In terms of Mean Squared Error (MSE), the QPSO-LMA approach achieved a decrease of 19.6% in relation to the classical LMA training with random initial weights. Moreover, the model's accuracy showed an increase of 7.3% for the QPSO-LMA over the LMA. To validate this new approach, it was also tested on six different datasets available in the UCI Machine Learning Repository and seven classical techniques established in the literature. For the problem of installing photovoltaic plants in abandoned areas, the knowledge acquired with the solar dataset can be extrapolated to other regions.

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Sustainable development: Case study in the implementation of renewable energy in Brazil

Cited by 66 publications

References 66 publications

Modeling the Nexus Between Sustainable Development and Renewable Energy: The African Perspectives

Modeling the Nexus Between Sustainable Development and Renewable Energy: The African Perspectives

Spatial targeting, synergies and scale: Exploring the criteria of smart practices for siting renewable energy projects

Classification of Abandoned Areas for Solar Energy Projects Using Artificial Intelligence and Quantum Mechanics

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