New technologies for optimal scheduling of electric vehicles in renewable energy‐oriented power systems: A review of deep learning, deep reinforcement learning and blockchain technology

Hu, Junjie; Hu, Junjie; Yao, Li; Fu, Zhuoming; Morais, H.; Marinelli, Mattia

doi:10.1049/enc2.12071

Cited by 10 publications

(2 citation statements)

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“…Likewise, ref. [156] provided an overview of deep reinforcement learning's application in the optimal scheduling of EVs, highlighting recent developments. The application of reinforcement learning to hybrid electric tracked vehicles was investigated by [157], focusing on learning transition probability matrices from specific driving schedules.…”

Section: Survey Of Charge Management Optimisation Methodsmentioning

confidence: 99%

A Comprehensive Review on Smart Electromobility Charging Infrastructure

Ayoade,

Longe

2024

WEVJ

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This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the article elucidates the evolving ecosystem of smart charging solutions, considering aspects including advancements in charging protocols. Additionally, the review highlights challenges and prospects in the SECI domain, providing insightful information for scholars, practitioners, and policymakers involved in the dynamic field of electromobility. Technical potentials, including functionalities and integration with the smart grid, have been thoroughly reviewed. An analysis is conducted on the effects of intelligent charging on power distribution systems and strategies to lessen these effects. This study also examines the development of intelligent charging algorithms, optimisation methods, and security analysis. This paper, therefore, contributes to fostering a more thorough comprehension of the current state and future trajectories of Smart Electromobility Charging Infrastructure.

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Section: Survey Of Charge Management Optimisation Methodsmentioning

confidence: 99%

A Comprehensive Review on Smart Electromobility Charging Infrastructure

Ayoade,

Longe

2024

WEVJ

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“…Additionally, innovative developments in human-computer interaction (HCI) and future trends should be explored to understand the evolving landscape of technology in community development (Hasan & Yu, 2015). Advancing technology in community development also requires exploring new technologies such as deep learning, deep reinforcement learning, and blockchain technology for optimal scheduling of electric vehicles in renewable energy-oriented power systems (Hu et al, 2022). Furthermore, technology forecasting using deep learning neural networks and future-oriented technology analysis based on text mining can provide insights into the emerging technological landscape (Gui & Xu, 2021;Chunlei & Lu, 2013).…”

Section: Future Research Directions Of Technology In Community Develo...mentioning

confidence: 99%

Technology in community development: A comparative review of USA and African Projects

Beatrice Adedayo Okunade,

Ololade Elizabeth Adewusi,

Foluke Eyitayo Adediran

et al. 2024

Int. J. Sci. Res. Arch.

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This paper conducts a comprehensive comparative review of technology-driven community development initiatives in the United States and various regions across Africa. The study aims to shed light on the diverse approaches and outcomes of projects leveraging technology to empower communities in different socio-cultural and economic contexts. The review begins by examining the landscape of community development in both the USA and Africa, emphasizing the challenges faced by urban and rural communities alike. It establishes a foundation for understanding the increasing role of technology in addressing these challenges, framing it as a dynamic and evolving field with vast potential for positive impact. Key findings from the comparative analysis are distilled, emphasizing the importance of context-specific approaches in technology-driven community development. Projects that demonstrate a nuanced understanding of local needs, cultural dynamics, and infrastructural realities exhibit greater success. The review underscores that successful implementation requires more than the transfer of technology; it demands a deep integration into the fabric of community life. The paper also touches upon overarching insights, highlighting the transformative power of technology when thoughtfully applied to community development. It acknowledges the significance of community engagement, adaptability, and a holistic understanding of local nuances as critical factors influencing project success. In concluding remarks, the paper encourages continued research and collaboration. It recognizes the ongoing journey towards harnessing technology's potential for global community empowerment and emphasizes the importance of cross-cultural partnerships, interdisciplinary collaboration, and knowledge sharing. Ultimately, the paper seeks to contribute to the ongoing discourse on technology in community development, offering insights that can inform future projects, policies, and academic pursuits in this dynamic field.

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