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Artificial Intelligence and Machine Learning New Concepts in SMART Energy Systems

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Special Issue Editors

Special Issue Information

Dear Colleagues,

Integrating various energy sectors into smart energy systems is considered to be a potential paradigm for offering an all-encompassing and optimal solution for a feasible, reasonably priced, and sustainable energy system in the near future. According to Mathiesen, a smart energy system is one that is powered exclusively by renewable energy, utilizes a sustainable amount of bioenergy, makes use of the system's synergies to enhance efficiency, and lowers prices to make it more accessible. Growing energy use is inextricably linked to both economic growth and increased wellbeing. Relatively new ideas in the fields of energy, artificial intelligence (AI) and machine learning (ML) have the potential to be employed as useful tools in the operation of systems, using previous and anticipated future events to enhance system efficacy. The application of AI in energy systems has garnered increasing attention in recent years. Energy systems include various types of machinery, structures, vegetation, and even intelligent energy (such as electrical grids). In other words, they are any system that requires energy in order to function, preserve a given state, or move energy between points. Possessing a smart management system that can anticipate future events to run grid assets to their maximum capacity or respond to abrupt changes in inputs (such as rising or falling demand) may be extremely helpful when it comes to transmitting or consuming energy.

Dr. Joanna Rosak-Szyrocka
Prof. Dr. Radosław Wolniak
Guest Editors

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Keywords

application of AI and ML for the effective use of energy storage
using the Internet of Things to minimize energy consumption, costs and emissions
optimization of energy flow
smart energy optimization
smart energy systems: smart power system control, smart thermal system control, smart cross-sector control, the utilization of clean or renewable energy, the reliability and resilience of energy systems, system integration among multiple energy sectors

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Published Papers (1 paper)

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Review

34 pages, 1519 KiB

Open AccessEditor’s ChoiceReview

Challenges of Artificial Intelligence Development in the Context of Energy Consumption and Impact on Climate Change

by Sergiusz Pimenow, Olena Pimenowa and Piotr Prus

Energies 2024, 17(23), 5965; https://doi.org/10.3390/en17235965 - 27 Nov 2024

Cited by 3 | Viewed by 1971

Abstract

With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) entail significant energy consumption, potentially undermining carbon neutrality efforts. Key findings include an analysis of 237 scientific publications from 2010 to 2024, which highlights significant advancements and obstacles to AI adoption across sectors, such as construction, transportation, industry, energy and households. The review showed that interest in the use of AI and ML in energy efficiency has grown significantly: over 60% of the documents have been published in the last two years, with the topics of sustainable construction and climate change forecasting attracting the most interest. Most of the articles are published by researchers from China, India, the UK and the USA, (28–33 articles). This is more than twice the number of publications from researchers around the rest of the world; 58% of research is concentrated in three areas: engineering, computer science and energy. In conclusion, the review also identifies areas for further research aimed at minimizing the negative impacts of AI and maximizing its contribution to sustainable development, including the development of more energy-efficient AI architectures and new methods of energy management. Full article

(This article belongs to the Special Issue Artificial Intelligence and Machine Learning New Concepts in SMART Energy Systems)

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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Impact of the Internet of Things to minimize energy consumption, costs and emissions for creating Sustainable economic in XXI century
Author: Bhattacharya
Highlights: Internet of Things , cybersecurity , renewable energy , carbon footprints

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