AIMC Topic: Renewable Energy

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Application of artificial intelligence in solar and wind energy resources: a strategy to deal with environmental pollution.

Environmental science and pollution research international
Environmental pollution has become a significant concern of nations. International organizations, local authorities, and social activists try to achieve sustainable development goals (SDGs) to protect the environment. However, this cannot be achieved...

Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm.

Journal of environmental management
China's carbon reduction is of substantial significance in combating global climate change. In the context of the COVID-19 epidemic hit and economic and social development uncertainty, this study intends to discover whether China can attain the strat...

Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models.

Scientific reports
Detached off-grids, subject to the generated renewable energy (RE), need to balance and compensate the unstable power supply dependent on local source potential. Power quality (PQ) is a set of EU standards that state acceptable deviations in the para...

Prediction of Electric Power Production and Consumption for the CETATEA Building Using Neural Networks.

Sensors (Basel, Switzerland)
Economic and social development is hardly influenced by electric power production and consumption. In this context of the energy supply pressure, energy production and consumption must be monitored and controlled in an intelligent way. Due to the ava...

Investigating a Dual-Channel Network in a Sustainable Closed-Loop Supply Chain Considering Energy Sources and Consumption Tax.

Sensors (Basel, Switzerland)
This paper proposes a dual-channel network of a sustainable Closed-Loop Supply Chain (CLSC) for rice considering energy sources and consumption tax. A Mixed Integer Linear Programming (MILP) model is formulated for optimizing the total cost, the amou...

A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management.

Environmental science and pollution research international
Energy is the source of economic growth, and energy consumption indicates the country's state of development. Energy engineering is a relatively new technical discipline. It is increasingly considered as a significant step in meeting carbon reduction...

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.

Nature communications
Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning t...

Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.

PloS one
The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to...

Artificial neural network-based output power prediction of grid-connected semitransparent photovoltaic system.

Environmental science and pollution research international
The solar photovoltaic system is an emerging renewable energy resource. The performance of the solar photovoltaic system is predicted based on the historical experimental dataset. In this work, the real-time prediction models are developed for the ou...

Perceptions of GHG emissions and renewable energy sources in Europe, Australia and the USA.

Environmental science and pollution research international
People's sentiments and perceptions of greenhouse gas emission and renewable energy are important information to understand their reaction to the planned mitigation policy. Therefore, this research analyzes people's perceptions of greenhouse gas emis...