Results 21 to 30 of about 120 (97)
This paper proposes a mixed game model incorporating a carbon trading mechanism to facilitate energy scheduling and low‐carbon optimisation for multi‐region integrated energy systems. ABSTRACT Multi‐region integrated energy systems (IESs) represent a crucial approach for reducing carbon emissions and improving energy efficiency.
Kuan Wang, She Yi, Yongqian Li
wiley +1 more source
In this work we proposed a cooperative control method for uncontrolled intersections, which employs a leader–follower decision–making process to assign roles to vehicles by constructing a role relationship directed graph. The weighted maximum clique algorithm is used to break the loops in the role relationship directed graph, considering the influence ...
Zhaojie Wang, Guangquan Lu, Haitian Tan
wiley +1 more source
An AI–Blockchain‐Based Network Optimization Framework for Energy‐Efficient Computing Systems
This paper presents AIBLOCK, an AI–blockchain‐based network optimisation framework that enables energy‐efficient and self‐optimising operation in large‐scale distributed computing networks. By integrating multi‐agent reinforcement learning with real‐time blockchain telemetry, the framework adaptively adjusts consensus parameters such as the block size,
Udit Mamodiya +4 more
wiley +1 more source
This study proposes a bi‐level optimization model to coordinate carbon reduction across multi‐echelon power equipment supply chains under carbon quota and trading policies. Results demonstrate that carbon price provides dual incentives for abatement and revenue generation, with the abatement cost coefficient being the dominant factor influencing ...
Wei Xu, Lu Zhang, Grace Kouassi
wiley +1 more source
Moment‐Based Risk Coordination for Multi‐Area Power Systems Under Non‐Gaussian Uncertainty
This paper proposes a hierarchical probabilistic coordination framework for multi‐area power systems that incorporates higher‐order statistical moments–mean, variance, skewness and kurtosis–via the Cornish–Fisher expansion to capture non‐Gaussian wind power uncertainty.
Aamir Nawaz +4 more
wiley +1 more source
Low‐Carbon TSO‐DSO Dispatch Coordination Under Wind Power Uncertainty
This paper presents a novel bi‐level optimisation framework to coordinate the operations of transmission system operators (TSOs) and distribution system operators (DSOs) under wind power uncertainty. By incorporating the carbon emission flow theory, the framework accurately quantifies carbon intensity at each transmission node, providing essential ...
Yingli Wei +6 more
wiley +1 more source
Optimised Pairing–Based Fair Resource Management in LTE‐Advanced Device‐to‐Device Communications
This paper addresses the challenges of interference management and resource allocation in LTE‐Advanced Device‐to‐Device (D2D) communications. It proposes a comprehensive framework integrating optimal pairing, resource allocation, and power assignment to maximize network performance.
Siavash Rajabi +3 more
wiley +1 more source
The transportation sector is a major contributor to global carbon emissions; however, the high costs of infrastructure and equipment present significant barriers to effective emission reduction. As a market‐based mechanism, carbon trading improves the efficiency of emission reductions and facilitates the integration of the transportation sector into ...
Si Chen +5 more
wiley +1 more source
Smart healthcare edge networks should be able to serve two purposes at once: to train federated machine learning models across a range of devices without violating patient privacy and to schedule other activities with latency constraints, like real‐time patient events.
K. Praghash +6 more
wiley +1 more source
Editorial: Smart and sustainable supply chain and logistics - trends, challenges, methods and best practices. [PDF]
Golinska-Dawson P +3 more
europepmc +1 more source

