Published: May 17, 2024
Language: Английский
Energy & Environment, Journal Year: 2024, Volume and Issue: 35(7), P. 3833 - 3879
Published: May 22, 2024
The global transition toward sustainable energy sources has prompted a surge in the integration of renewable systems (RES) into existing power grids. To improve efficiency, reliability, and economic viability these systems, synergistic application artificial intelligence (AI) methods emerged as promising avenue. This study presents comprehensive review current state research at intersection AI, highlighting key methodologies, challenges, achievements. It covers spectrum AI utilizations optimizing different facets RES, including resource assessment, forecasting, system monitoring, control strategies, grid integration. Machine learning algorithms, neural networks, optimization techniques are explored for their role complex data sets, enhancing predictive capabilities, dynamically adapting RES. Furthermore, discusses challenges faced implementation such variability, model interpretability, real-time adaptability. potential benefits overcoming include increased yield, reduced operational costs, improved stability. concludes with an exploration prospects emerging trends field. Anticipated advancements explainable reinforcement learning, edge computing, discussed context impact on Additionally, paper envisions AI-driven solutions smart grids, decentralized development autonomous management systems. investigation provides important insights landscape applications
Language: Английский
Citations
57
Smart Cities, Journal Year: 2024, Volume and Issue: 7(3), P. 1346 - 1389
Published: June 10, 2024
As urbanization continues to pose new challenges for cities around the world, concept of smart is a promising solution, with artificial intelligence (AI) playing central role in this transformation. This paper presents literature review AI solutions applied cities, focusing on its six main areas: mobility, environment, governance, living, economy, and people. The analysis covers publications from 2021 2024 available Scopus. examines application each area identifies barriers, advances, future directions. authors set following goals analysis: (1) identify applications using cities; (2) barriers implementation (3) explore directions usage cities.
Language: Английский
Citations
53
Energies, Journal Year: 2023, Volume and Issue: 16(24), P. 7988 - 7988
Published: Dec. 9, 2023
This paper provides a comprehensive review of solutions based on artificial intelligence (AI) in the urban energy sector, with focus their applications and impacts. The study employed literature methodology to analyze recent research AI’s role energy-related solutions, covering years 2019 2023. authors classified publications according main focus, resulting two key areas AI implementation: residential individual user applications, infrastructure integration for society. objectives this are following: O1: identify trends, emerging technologies, using field; O2: provide up-to-date insights into use applications; O3: gain understanding current state AI-driven solutions; O4: explore future directions, challenges field solutions. contributes deeper transformative potential management, providing valuable directions researchers practitioners field. Based results, it can be claimed that connected at homes is used following areas: heating cooling, lighting, windows blinds, home devices, management systems. integrating through solutions: enhancement electric vehicle charging infrastructure, reduction emissions, development smart grids, efficient storage. What more, latest associated implementation include need balance resident comfort efficiency homes, ensuring compatibility cooperation among various preventing unintended consumption increases due constant connectivity, renewable sources, coordination consumption.
Language: Английский
Citations
43
Journal of Advanced Research in Applied Sciences and Engineering Technology, Journal Year: 2024, Volume and Issue: 38(1), P. 77 - 88
Published: Jan. 24, 2024
The Internet of Things (IoT) brings new products to everyone improve daily life. Concurrently other emerging technologies, including Big Data, Cloud Services, and surveillance, can participate through these technological advances. This research work explores the synergies among four systems identify their shared functionalities integrate them create useful potential applications. Despite limitations smart city concept, researchers would seek innovative methods collect process sensor information within an IoT-enabled building. A cornerstone proposed system is utilization cloud services as foundational technology for a schema management platform. platform efficiently gathers data generated by sensors industrial units. Leveraging capabilities IoT technology, be remotely managed accessed using mobile devices with network connectivity. addresses challenges related perception supports revolutionary approaches in collection manipulation Sensor data. By doing so, it imagines creation green, schemes that contribute sustainable urban development.
Language: Английский
Citations
6
Sensors, Journal Year: 2024, Volume and Issue: 24(5), P. 1391 - 1391
Published: Feb. 21, 2024
Accurate short-term load forecasting (STLF) is essential for power grid systems to ensure reliability, security and cost efficiency. Thanks advanced smart sensor technologies, time-series data related can be captured STLF. Recent research shows that deep neural networks (DNNs) are capable of achieving accurate STLP since they effective in predicting nonlinear complicated data. To perform STLP, existing DNNs use time-varying dynamics either past consumption or correlated features such as weather, meteorology date. However, the DNN approaches do not time-invariant users, building spaces, ages, isolation material, number floors purposes, enhance In fact, those user consumption. Integrating enhances this paper, a fuzzy clustering-based proposed by using both The clustering first groups users with similar behaviours. models then developed features. Since have already been learned clustering, model does need learn features; therefore, simpler generated. addition, only learns same cluster; more learning performed predictions achieved. performance evaluated performing STLF, where included. Experimental results show outperforms commonly used long memory convolution networks.
Language: Английский
Citations
6
International Journal of Intelligent Networks, Journal Year: 2024, Volume and Issue: 5, P. 267 - 274
Published: Jan. 1, 2024
Machine learning models are the backbone of smart grid optimization, but their effectiveness hinges on access to vast amounts training data. However, grids face critical communication bottlenecks due ever-increasing volume data from distributed sensors. This paper introduces a novel approach leveraging Generative Artificial Intelligence (GenAI), specifically type pre-trained Foundadtion Model (FM) architecture suitable for time series its efficiency and privacy-preserving properties. These GenAI agents, or holders, empowering them fine-tune foundation model with local datasets. By fine-tuning model, updated can produce synthetic that mirrors real-world conditions. The server aggregates fine-tuned all agents then generates which considers collected in grid. be used train global machine specific tasks like anomaly detection energy optimization. Then, trained task leverage them. highlights advantages communication, including reduced burden, enhanced privacy through anonymized transmission, improved scalability. enabling intelligent architecture, way more secure, efficient, sustainable future.
Language: Английский
Citations
5
International Journal on Semantic Web and Information Systems, Journal Year: 2024, Volume and Issue: 20(1), P. 1 - 32
Published: Jan. 12, 2024
This study aims to quantify the perception of value and acceptance by citizens use cyber-physical systems (CPS) in transportation smart cities using neurotechnologies. The work has been developed main following Latin American countries: Spain, Ecuador, Colombia, Argentina. Targeting urban, public transport-using graduates, it assesses CPS user experiences. Triangulating qualitative research neurotechnology, extends taxonomy emotional domains. results indicate that users do not always assign equivalent importance what they truly feel, is noteworthy most important factor, both quantitatively emotionally, application improve efficiency transportation. implications these analyses are discussed final part article with aim providing recommendations policymakers on key aspects be considered design development for cities.
Language: Английский
Citations
4
Energies, Journal Year: 2023, Volume and Issue: 16(22), P. 7633 - 7633
Published: Nov. 17, 2023
This systematic review investigates the role of artificial intelligence (AI) in advancing clean energy technologies within Europe, based on a literature survey from 2006 to 2023. The assessment reveals that AI, particularly through deep learning and neural networks, enhances efficiency, optimization, management systems. Noteworthy is AI’s capacity improve short-term forecasts, essential for smart cities IoT applications. Our findings indicate AI drives innovation renewable energy, contributing development grids enabling collaborative energy-sharing models. While research underscores substantial influence Europe’s sector, it also identifies gaps, such as varied algorithm applications different sectors. study emphasizes need integrating with emerging innovations, advocating interdisciplinary navigate socio-economic, environmental, policy dimensions. approach crucial guiding sustainable balanced advancement landscape, signifying pivotal transition.
Language: Английский
Citations
10
Peer-to-Peer Networking and Applications, Journal Year: 2025, Volume and Issue: 18(3)
Published: March 7, 2025
Language: Английский
Citations
0
Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 435 - 462
Published: March 7, 2025
Due to increasing urbanization, smart cities have developed rapidly, and they focus on technology driven infrastructure sustainable development. With becoming more digital, Corporate Social Responsibility (CSR) Artificial Intelligence (AI) are key issues in determining the urban habitat of future. This work investigates relationship between CSR, AI cities, their implications for Aiming from perspective role city making responsibility corporations enhancing environment, this chapter discusses opportunities difficulties combining CSR building liveable, efficient, cities. More specifically, study aims help extend understanding entanglement corporate responsibility, technological innovation, sustainability guide development resilient just
Language: Английский
Citations
0