DOI: 10.1016/j.eneco.2024.107748 Corpus ID: 270783584 An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence @article{Ding2024AnII, title={An inquiry into the nexus between artificial intelligence and …
AI encompasses the sub-fields of machine learning and deep learning, which use AI algorithms that are trained on data to make predictions or classifications. The benefits of AI include automation of repetitive tasks, improved decision making and a better customer experience. Analyst report Gartner names IBM a leader.
Multi-objective optimization of compressed air, power, and heating with constraints of compressed air between 550 and 600 g/s, power between 400 and 450 kW, and heating between 550 and 600 kW. The parameters have been modified to include compressed air flow rates ranging from 550 to 600 g/s, power levels between 350 and …
Machine learning is a specific application of artificial intelligence that allows computers to learn and improve from data and experience via sets of algorithms, without the need for reprogramming.
Research shows that companies can realize benefits in organizational creativity by cultivating AI capabilities. But did not point out the specific influence path between the two. Therefore, this paper introduces knowledge sharing to explore its role in the relationship between artificial intelligence capability and organizational creativity.
Applications of AI in Advanced Energy Storage Technologies Article May 2023 Rui Xiong Hailong ... These results provide an insight into the relationship between artificial intelligence and supply ...
1. Introduction. AI may be defined as a mix of large sums of data, enough computer power, and machine learning. ML is a subcategory of AI that may be described as a means of constructing a series of activities to solve a problem that mechanically optimises via experience – with or without human participation [1] today''s complicated …
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances — at the materials, devices and systems levels — for the efficient harvesting ...
First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy ...
1. Introduction. The prompt development of renewable energies necessitates advanced energy storage technologies, which can alleviate the intermittency of renewable energy. In this regard, artificial intelligence (AI) is a promising tool that provides new opportunities for advancing innovations in advanced energy storage technologies (AEST).
In the rapidly evolving landscape of customer service, integrating AI-powered solutionshas emerged as a game-changer. This study delves into the intricate dynamics of AI-Powered Customer Service and its profound impact on customer loyalty, specifically focusing on the mediating roles played by customer satisfaction and perceived …
The papers within this cluster stress that AI, including machine learning (ML) and deep learning (DL), is instrumental in transforming education. Within this context, some papers explore enhancing ...
Specifically, using artificial intelligence technology could automatically optimise the application of energy according to the electric vehicles'' driving route, road conditions and energy needs (Ye et al., 2023; Hu et al., 2024), such as adjusting the electric vehicles'' driving speed and switching air conditioning to realise the efficient use ...
The papers within this cluster stress that AI, including machine learning (ML) and deep learning (DL), is instrumental in transforming education. Within this context, some papers explore …
The prompt development of renewable energies necessitates advanced energy storage technologies, which can alleviate the intermittency of renewable energy. In this regard, artificial intelligence (AI) is a promising tool that provides new opportunities for …
Artificial intelligence (AI) and machine learning (ML) have been transforming the way we perform scientific research in recent years.1–4 This themed collection aims to showcase the implementation of AI and ML in energy storage and conversion research, including that on batteries, supercapacitors, electrocatalysis, and photocatalysis.
Machine learning will be the only tool to reduce running costs, which can be an efficient roadmap for improving energy storage (batteries, super capacitors, fuel cells, conversions cells, etc.).
Second, this study measures ED. Our ultimate goal in measuring ED is to capture energy poverty in different countries (Oum, 2019).Therefore, the energy poverty index (EP) required for this study can be obtained through EP = 1 / ED since the lower ED value of a country in a given year, the higher its level of energy poverty (Banerjee et al., 2021).
A microgrid with energy storage, PV power systems, wind turbines, diesel generators, and customer loads [56] Batch Q-learning ... A Venn diagram showing the overlap between the artificial intelligence, big data …
Artificial intelligence (AI) offers a smart way to help society achieve goals in a modern manner by implementing techniques involving predictive analytics, claims analytics, emerging issues detection, survey analysis, etc. AI covers a wide range, but the fields were not formally founded until 1956, at a conference at Dartmouth College, in Hanover.
Section 2 entails a literature review covering AI''s application and its relation to energy systems, AI''s quantitative approaches, and the quantitative methods of energy transition. Section 3 covers the methodology, detailing the reasons and sources for the data selected and the methodologies for building the model herein.
In this paper, data mining is used to quantify the relationship between the input data and the output; the results of this analysis were used to select the best data for training. ... Energy Storage System (Battery, Flywheel, Thermal Storage etc.) ... A Venn diagram showing the overlap between the artificial intelligence, big data and digital ...
Artificial Intelligence (AI) has taken center stage and the massive adoption of AI has disrupted businesses across sectors. AI has rapidly emerged as a transformative that has already revolutionized customer experiences to automated complex processes. It''s definitely a game-changer that has helped organizations to what they do – …
Generative artificial intelligence uses massive amounts of energy for computation and data storage and millions of gallons of water to cool the equipment at data centers. Now, legislators and regulators — in the U.S. …
The relationship between artificial intelligence (AI) and its aspects in higher education - Author: Bahaa Razia, Bahaa Awwad, Najma Taqi This paper aims to provide better understanding on this phenomenon, as well as some recommendations to assist in preparing Al technology and its related aspects during crisis like Covid period …
After presenting the theoretical foundations of renewable energy, energy storage, and AI optimization algorithms, the paper focuses on how AI can be applied to improve the efficiency and performance of energy storage systems.
Big data and artificial intelligence have a synergistic relationship. AI requires a massive scale of data to learn and improve decision-making processes and big data analytics leverages AI for better data analysis. With this convergence, you can more easily leverage advanced analytics capabilities like augmented or predictive analytics and more ...
The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of …
This paper aims to introduce the need to incorporate information technology within the current energy storage applications for better performance and reduced costs. Artificial intelligence based BMSs facilitate parameter predictions and state estimations, thus
AI''s Carbon Footprint. Behind the scenes of AI''s brilliance lies an energy-intensive process with a staggering carbon footprint. As datasets and models become more complex, the energy needed to train and run AI models becomes enormous. This increase in energy use directly affects greenhouse gas emissions, aggravating climate change.
August 8, 2022. When partnered with Artificial Intelligence (AI), the next generation of battery energy storage systems (BESS) will give rise to radical new opportunities in power optimisation and predictive maintenance for all types of mission-critical facilities. Undeniably, large-scale energy storage is shaping variable generation and ...
This whitepaper gives businesses, developers, and utilities an understanding of how artificial intelligence for energy storage works. It dives into Athena''s features and Stem''s principles that drive product development, and discusses how that supports our …
A city is considered to be smart when the application of Artificial Intelligence (AI) and the Internet of Things (IoT) is integrated with it. This enables the collection of data from people, devices, and buildings, then analyses are performed to optimize control over infrastructure, traffic, energy, etc. A smart city is a collective …
Existing studies offer a concise overview of research findings and insights into the evolving relationship between Artificial Intelligence (AI) and firm high-quality development. In particular, regarding to the sustainable development approach, AI has the potential to enhance the accuracy and transparency of sustainability reporting.
The questions of where technology will eventually lead humanity, to what extent artificial intelligence will change the relationship between humans and work, and whether advanced productivity will ...
He looked at the relationship between artificial intelligence and neuroscience over time and focused on the most recent developments in AI that have influenced research on human and other animal neuro-computing. 5G mobile networks were considered to be a key factor in the ICT industry and offered different services and met …