Application of Artificial Intelligence in Renewable Energy

Alankrita,; Srivastava, S. K.

doi:10.1109/compe49325.2020.9200065

Cited by 12 publications

(2 citation statements)

References 42 publications

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“…Based on the stochastic and intermittent nature of renewable resources, significantly affecting the stable behavior and sustainability of the energy system when it is integrated into the overall energy system, it is necessary to improve the accuracy of existing forecasting approaches, for which a number of AI technologies can be used [28,29]. Artificial intelligence is a certain complex high-tech discipline, the main field of study of which is "machine" intelligence and computing systems based on its use.…”

Section: Artificial Intelligence In Solar and Wind Power Forecastingmentioning

confidence: 99%

A Solar and Wind Energy Evaluation Methodology Using Artificial Intelligence Technologies

Simankov,

Buchatskiy,

Kazak

et al. 2024

Energies

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The use of renewable energy sources is becoming increasingly widespread around the world due to various factors, the most relevant of which is the high environmental friendliness of these types of energy resources. However, the large-scale involvement of green energy leads to the creation of distributed energy networks that combine several different generation methods, each of which has its own specific features, and as a result, the data collection and processing necessary to optimize the operation of such energy systems become more relevant. Development of new technologies for the more optimal use of RES is one of the main tasks of modern research in the field of energy, where an important place is assigned to the use of technologies based on artificial intelligence, allowing researchers to significantly increase the efficiency of the use of all types of RES within energy systems. This paper proposes to consider the methodology of application of modern approaches to the assessment of the amount of energy obtained from renewable energy sources based on artificial intelligence technologies, approaches used for data processing and for optimization of the control processes for operating energy systems with the integration of renewable energy sources. The relevance of the work lies in the formation of a general approach applied to the evaluation of renewable energy sources such as solar and wind energy based on the use of artificial intelligence technologies. As a verification of the approach considered by the authors, a number of models for predicting the amount of solar power generation using photovoltaic panels have been implemented, for which modern machine-learning methods have been used. As a result of testing for quality and accuracy, the best results were obtained using a hybrid forecasting model, which combines the joint use of a random forest model applied at the stage of the normalization of the input data, exponential smoothing model, and LSTM model.

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Section: Artificial Intelligence In Solar and Wind Power Forecastingmentioning

confidence: 99%

A Solar and Wind Energy Evaluation Methodology Using Artificial Intelligence Technologies

Simankov,

Buchatskiy,

Kazak

et al. 2024

Energies

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“…In the field of renewable energies several relevant research state-of-the-art projects have being conducted to improve efficiency and to rationalize installation costs by introducing several innovative approaches [2], [3], [4] [5], [6], [7], [8], [9] and [10]. All the described goals and innovation achievements supported by data networks for data flow brought along the new introduction of concepts such as Big Data [11], [12] and [13], Artificial Intelligence (AI) [14], [15], [16], [17], [18], Internet of Things (IoT) [19], [20], [21], [22] and [23] and many others. All these new technologies open the hot topic of cybersecurity into the REP world.…”

Section: Introductionmentioning

confidence: 99%

The relevance of IT Security awareness in Renewable Energy facilities

Lourenço¹,

Zanghi²,

Morais³

et al. 2024

RE&PQJ

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In recent years several efforts have being made in bringing smart network connectivity to the Renewable Energy Plant (REP) environment. On the other hand, REP is extending in scale from specialized points where the energy provider acts as a supplier to home REP (self-energy producers). This enables new important features such as: process automation, monitoring, control and optimizations. On the other hand, and in particular during and after the Covid19 pandemics the cybersecurity menace is a massive concern. The digital literacy of a worker of such an infrastructure is relevant to the correct implementation of adequate security policies. This article describes the threats and challenges on the field and conducts an enquire for perceiving the awareness of Automation and Mechanics Engineering students for this relevant problem, as future player in the field.

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Artificial Intelligence and Machine Learning Based: Advances in Demand-Side Response of Renewable Energy-Integrated Smart Grid

Chaurasia

Kamath

2021

Smart Systems: Innovations in Computing

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Application of Artificial Intelligence in Renewable Energy

Cited by 12 publications

References 42 publications

A Solar and Wind Energy Evaluation Methodology Using Artificial Intelligence Technologies

A Solar and Wind Energy Evaluation Methodology Using Artificial Intelligence Technologies

The relevance of IT Security awareness in Renewable Energy facilities

Artificial Intelligence and Machine Learning Based: Advances in Demand-Side Response of Renewable Energy-Integrated Smart Grid

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