Energy Efficiency Development in Lithuanian Furniture Industry

Vasauskaite, Jovita; Štreimikienė, Dalia

doi:10.12720/joams.4.1.9-15

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Other empirical studies also applied some indicators from the ESDI framework. The Energy for Sustainable Development framework has also been applied to sustainability assessments of electricity market models [43][44][45][46], energy-efficiency policies [47,48], and the impact of corporate social responsibility on sustainable energy development [49,50].…”

Section: Framework Of Energy Indicators For Sustainable Developmentmentioning

confidence: 99%

The Impact of Greening Tax Systems on Sustainable Energy Development in the Baltic States

et al. 2018

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The paper deals with the greening of tax systems in the European Union (EU), and reviews the achievements of the Baltic States in relation to greening their tax systems and implementing the sustainable energy development goals set by the EU's energy policies. Environmental taxes promote sustainable energy development, as they allow internalizing the external costs of atmospheric pollution in the energy sector. Energy production and consumption are a major source classical pollutants and greenhouse gas (GHG) emissions. Almost of the all EU member states (MS) apply pollution taxes as the most important economic tool for mitigating the environmental impacts of various economic activities. Considering the importance of the energy sector in terms of its contributions to total atmospheric emissions in the EU, it is supposed that environmental taxes are important drivers of sustainable energy development. Environmental taxes, as the main tool for the integration of negative externalities that are related to atmospheric pollution, are imposed to create incentives for reducing fossil fuel consumption and switching to renewable energy sources or fuels that have a lower carbon content and thus cause less pollution. The paper presents a comparative assessment of the impact of environmental taxes on sustainable energy development indicators in three selected countries from the Baltic region (Lithuania, Latvia, and Estonia) during the period 2005-2015, and reveals the role that the greening of tax systems has had on implementing sustainable energy development targets in the Baltic States.

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Section: Framework Of Energy Indicators For Sustainable Developmentmentioning

confidence: 99%

The Impact of Greening Tax Systems on Sustainable Energy Development in the Baltic States

et al. 2018

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“…Research rationale: Both approaches address energy efficiency and the use of RES, which are seen as policies to promote sustainable energy and the competitiveness of developing countries [4][5][6][7]. If there are policy approaches to promote sustainable energy development, then sustainable energy indicators can be used to determine how to define the boundaries and framework for sustainable energy development.…”

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Application of Artificial Intelligence in the Unit Commitment System in the Application of Energy Sustainability

Garlík

2022

Energies

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This article approaches the optimal solution of energy sustainability based on the use of artificial intelligence (AI). The application of renewable energy sources (RES) and unit commitment (UC) is the basic idea of this concept. Therefore, a new approach to solving the UC problem is introduced. The proposed method has a simple procedure to obtain the popular solutions in an acceptable time interval, by creating a basic model of the schedule of the state of energy units RES. It is obvious that individual consumer units, of an operational nature, take hourly performance values by performing economic evaluations on them in the sense of cost optimization. This is conducted through an artificial intelligence (AI) algorithm by optimizing the dedicated cost function, simulated by annealing. Despite the acceptable solution obtained from these two steps, another shift is proposed, called the TDD process in a given consumer area. This process in the application of AI in the system of selection of universal load TDD from hundreds of possible ones is based on the use of artificial neural networks and cluster analysis, which is represented by the application of the Kohonen map. This logical process to achieve a modified solution is a self-organizing map (SOM). It is a software tool for visualizing high-dimensional data. Converts complex, nonlinear statistical relationships (functions) between high-dimensional data to simple geometric relationships, low-dimensional representation. The output of SOM is an optimized load TDD on the basis of which the process of automatic control of UC in the local urban area is built. The results of the AI application in the case of sustainable energy solutions confirm that this UC method provides a robust solution to an almost optimal solution.

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Applying Energy Efficiency Indicators in the Industrial Sector - Case Study in the Furniture Industry Focused on Electricity Consumption

Melo,

Disconzi

2024

Braz. arch. biol. technol.

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Energy Efficiency Development in Lithuanian Furniture Industry

Cited by 3 publications

References 13 publications

The Impact of Greening Tax Systems on Sustainable Energy Development in the Baltic States

The Impact of Greening Tax Systems on Sustainable Energy Development in the Baltic States

Application of Artificial Intelligence in the Unit Commitment System in the Application of Energy Sustainability

Applying Energy Efficiency Indicators in the Industrial Sector - Case Study in the Furniture Industry Focused on Electricity Consumption

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