Results 121 to 130 of about 3,204 (210)

Optimisation or Learning? Appropriate Choice of Models and Methods for Sequential Decision‐Making in Power System Operation

Energy Internet, EarlyView.
ABSTRACT Power system operation is inherently a sequential decision‐making problem, traditionally addressed through optimisation models built upon high‐quality load forecasts. However, the rapid proliferation of renewable generation and price‐responsive demands, such as electric vehicles and merchant energy storage, has introduced multiple sources of ...
Wei Wei, Runze Liang
wiley   +1 more source

A Hybrid Energy Storage‐Based 800 V DC Distribution Architecture and Hierarchical Rolling Scheduling Strategy for Intelligent Data Centres

Energy Internet, EarlyView.
ABSTRACT Intelligent computing loads, which are characterised by high‐power density and impulsive, pose a significant challenge to high‐power impact resilience and fast dynamic response capability of the internal power supply system in data centres. To tackle this challenge, this paper proposes an 800 V HVDC distribution architecture integrated with ...
Yanlin Song, Min Chen, Xiaojun Wang, Mohammad Shahidehpour, Yongqin Qiu   +4 more
wiley   +1 more source

From Cardiopulmonary Resuscitation Training to Guiding Bystanders: The Growing Role of AI in Resuscitation. [PDF]

J Med Internet Res
Falci M.
europepmc   +1 more source

Large language model‐enhanced deep reinforcement learning for voltage control in active distribution networks

Energy Conversion and Economics, EarlyView.
Abstract As active distribution networks (ADNs) become increasingly saturated with intermittent renewable energy sources, maintaining voltage within safe operational limits has become a critical and complex task, requiring advanced control methods beyond traditional rule‐based approaches.
Jing Ma, Xian Zhang, Guibin Wang, Yujian Ye, Fushuan Wen, Jing Qiu, Abdelmonem Elsawy Khalil   +6 more
wiley   +1 more source

Location-resolved performance of public-access defibrillation in an urban EMS system: a population-based study in Yokohama, Japan. [PDF]

Resusc Plus
Usui H, Taniguchi H, Abe T, Nogaki A, Takeuchi I.   +4 more
europepmc   +1 more source

CodeGen‐Resilience: A Framework for Automated Generation and Validation of Complex Scenarios for Large‐Scale Power System Resilience Analysis

Energy Conversion and Economics, EarlyView.
Abstract Power‐system resilience analysis requires executable simulation scenarios under changing risk conditions that translate disturbance descriptions into precise model modifications. This paper focuses empirically on steady‐state alternating‐current (AC) power‐flow scenario generation for physical‐layer power‐system disturbances; cyber‐layer and ...
Xinlei Cai, Qian Guo, Zhijun Shen, Lizhou Jiang, Mengfan Min, Xuanang Gui, Junhua Zhao, Yuheng Cheng   +7 more
wiley   +1 more source

Emergency call training in primary school children: effects of instruction format and dispatcher influence. [PDF]

Front Pediatr
Peters A, Bagci S, Müller N.
europepmc   +1 more source

Wind farm maintenance optimisation strategy considering MFTS distance‐based K‐medoids clustering and mixed Weibull model

Energy Conversion and Economics, EarlyView.
Abstract This paper proposes a wind‐resource‐weighted maintenance optimization framework to reduce operation and maintenance (O&M) costs and improve power generation efficiency. Existing clustering methods based on single distance metrics cannot fully capture the multidimensional temporal characteristics of wind‐speed data, while single Weibull models ...
Haixin Wang, Rui Zhuang, Junyou Yang, Mingchao Xia, Qifang Chen, Yubin Wang, Gang Zhao, Minghang Cao, Sharara Rehimi, Hassan Bevrani, Dan Doru Micu, Jingtao Zhao   +11 more
wiley   +1 more source

DispatchMAS: fusing taxonomy and artificial intelligence agents for emergency medical services. [PDF]

BMC Emerg Med
Li X, Yu H, Wang W, Wu Y, Zhou J, Hua W, Lin X, Tan W, Zhu L, Chen B, Chen G, Chen ML, Zhou Y, Li Z, Assimes TL, Zhang Y, Wu Q, Ma X, Li L, Fan L.   +19 more
europepmc   +1 more source

Research on Embodied Intelligence Technology for Electric Power Equipment Based on Large‐Scale Pre‐Trained Models

High Voltage, EarlyView.
ABSTRACT With the development of electric power artificial intelligence (AI) technology, many complicated challenges emerged during application. Traditional AI algorithms work well in specialised tasks such as detection and classification. However, they are unlikely to solve general problems.
Yuanpeng Tan, Rui Song, Ankai Zhang, Wenhao Mo, Wenjin Ji   +4 more
wiley   +1 more source