186+ open-access research outputs.
As edge AI deployments scale to billions of devices running always-on, real-time compound AI pipelines, they represent a massive and largely unmanaged source of energy consumption and carbon emissionsโฆ
The integration of the high penetration of intermittent renewable energy sources (RES) and the retirement of thermal units have significantly aggravated the flexibility scarcity and real-time balancinโฆ
Carbon-aware grid optimization relies on accurate locational emission metrics to effectively guide demand-side decarbonization tasks such as spatial load shifting. However, existing metrics are only vโฆ
The increasing penetration of intermittent renewable energy sources and the retirement of thermal units have widened the power system flexibility gap. Industrial demand response (DR) driven by real-tiโฆ
Uncertainties in balancing generation and load in low-carbon industrial microgrids (IMGs) make hybrid energy storage systems (HESS) crucial for their stable and economic operation. Existing model predโฆ
Tackling climate change requires the rapid and deep decarbonization of electric power systems. While energy management systems (EMSs) play a central role in this transition, conventional EMSs focus maโฆ
This paper presents joint sampling frequency offset (SFO) estimation and compensation algorithms based on the Farrow structure. Unlike conventional approaches that treat estimation and compensation seโฆ
Leveraging future observation modeling to facilitate action generation presents a promising avenue for enhancing the capabilities of Vision-Language-Action (VLA) models. However, existing approaches sโฆ
Truss optimization is a rich research field receiving renewed interest in limiting the carbon emissions of construction. However, a persistent challenge has been to construct highly optimized and ofteโฆ
This paper proposes a two-stage stochastic optimization formulation to determine optimal operation and procurement plans for achieving a 24/7 carbon-free energy (CFE) compliance at minimized cost. Theโฆ
The increasing global push for carbon reduction highlights the importance of integrating renewable energy into the supply chain of cellular networks. However, due to the stochastic nature of renewableโฆ
The global carbon market is fragmented and characterized by limited pricing transparency and empirical evidence, creating challenges for investors and policymakers in identifying carbon management oppโฆ
Fiber reinforcement and polymer matrix respond differently to manufacturing conditions due to mismatch in coefficient of thermal expansion and matrix shrinkage during curing of thermosets. These heterโฆ
The excellent structural and piezoresistive properties of continuous carbon fiber make it suitable for both structural and sensing applications. This work studies the use of 3D printed, continuous carโฆ
Human Action Recognition using WiFi Channel State Information (CSI) has emerged as an attractive alternative to vision-based methods due to its ubiquity, device-agnostic nature, and inherent privacy-pโฆ
Reliable positioning in GNSS-challenged environments remains a critical challenge for navigation systems. Tightly coupled GNSS/IMU fusion improves robustness but remains vulnerable to non-Gaussian noiโฆ
This paper addresses the joint scheduling problem of stochastic workloads and a hydrogen-enabled distributed energy system in a low-carbon Internet data centers (IDC). Although such workloads can be sโฆ
Constructing clean and low-carbon rural integrated energy system (RIES) is a fundamental requirement for supporting China's rural modernization and new-type urbanization. Existing research on RIES decโฆ
Allocating costs, benefits, and emissions fairly among power system participant entities represents a persistent challenge. The Shapley value provides an axiomatically fair solution, yet computationalโฆ
Quantifying locational carbon emissions in power grids is crucial for implementing effective carbon reduction strategies for customers relying on electricity. This paper presents a carbon-aware optimaโฆ
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