AIMC Topic: Renewable Energy

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Strategic forecasting of renewable energy production for sustainable electricity supply: A machine learning approach considering environmental, economic, and oil factors in Türkiye.

PloS one
Providing electricity needs from renewable energy sources is an important issue in the energy policies of countries. Especially changes in energy usage rates make it necessary to use renewable energy resources to be sustainable. The electricity usage...

Artificial intelligence-driven green innovation for sustainable development: Empirical insights from India's renewable energy transition.

Journal of environmental management
This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Developm...

How renewable energy policies cut greenhouse gas emissions: Insights from advanced data analysis techniques.

Journal of environmental management
Renewable Energy Policies (REPs) have gained prominence at recent UNFCCC COPs as pivotal tools for mitigating greenhouse gas (GHG) emissions. In response, many countries have devised Renewable Energy Strategic Plans (RESPs) and set Renewable Energy T...

Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Neural networks : the official journal of the International Neural Network Society
Electricity is generated through various resources and then flows between regions via a complex system (grid). Imbalances in electricity generation can lead to the waste of renewable energy. As renewable energy is becoming a larger part of the grid, ...

Climate Sustainability through AI-Crypto Synergies and Energy Transition in the Digital Landscape to Cut 0.7 GtCOe by 2030.

Environmental science & technology
The rapid expansion of artificial intelligence (AI)-enabled systems and cryptocurrency mining poses significant challenges to climate sustainability due to energy-intensive operations relying on fossil-powered grids. This work investigates the strate...

Integrating intuitionistic fuzzy and MCDM methods for sustainable energy management in smart factories.

PloS one
Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework to optimize energy efficiency in smart manufacturing environments, i...

Short-term power load forecasting in China: A Bi-SATCN neural network model based on VMD-SE.

PloS one
This study focuses on improving short-term power load forecasting, a critical aspect of power system planning, control, and operation, especially within the context of China's "dual-carbon" policy. The integration of renewable energy under this polic...

Optimizing wave energy converter benchmarking with a fuzzy-based decision-making approach.

PloS one
The quest for sustainable energy solutions has intensified interest in marine renewables, particularly wave energy. This study addresses the crucial need for an objective assessment of Wave Energy Converter (WEC) technologies, which are instrumental ...

Environmental impact assessment of ocean energy converters using quantum machine learning.

Journal of environmental management
The depletion of fossil energy reserves and the environmental pollution caused by these sources highlight the need to harness renewable energy sources from the oceans, such as waves and tides, due to their high potential. On the other hand, the large...

A survey on advanced machine learning and deep learning techniques assisting in renewable energy generation.

Environmental science and pollution research international
The sustainability of the earth depends on renewable energy. Forecasting the output of renewable energy has a big impact on how we operate and manage our power networks. Accurate forecasting of renewable energy generation is crucial to ensuring grid ...