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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Shangheng Yao

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Conference Open access Sep 2026

Life-cycle carbon-footprint accounting of regional power systems: A production-consumption framework

In interconnected regional power grids, electricity generation, transmission, and final consumption are often spatially separated, making local-generation-based accounting insufficient for allocating life-cycle carbon responsibility. Taking Guangdong, Guangxi, Yunnan, Guizhou, and Hainan within China Southern Power Gri...

Zhi-Yuan Yang, Yang Guo, Yan-Bo Sun et al. · 0 citations
Conference Open access Sep 2026

System construction and theoretical analysis of green power life-cycle accounting based on large language models

Green power from renewable resources is essential for low-carbon development, but its life-cycle management is constrained by fragmented data, complex monitoring tasks, traceability requirements, and greenwashing risks. This paper develops a conceptual framework for applying large language models (LLMs) to green power...

Zhi-Yuan Yang, Yang Guo, Yan-Bo Sun et al. · 0 citations
Open access Sep 2026

Assessing global carbon mitigation benefits of wind power with spatiotemporal characteristics and production-deployment pathways

As wind power capacity continues expanding, its carbon-reduction effectiveness increasingly hinges on the spatiotemporal alignment of production, deployment, and power systems. However, these dimensions are assessed separately, and the role of spatiotemporal interactions in shaping carbon mitigation benefits remains un...

Jing-Yan Yang, Shang-Heng Yao, Chao-Jun Li et al. · 0 citations
Open access 2026

Carbon Footprint Accounting Driven by Large Language Models and Retrieval-Augmented Generation

LLMs-RAG-CFA, a unified framework that combines large language models with retrieval-augmented generation (RAG) to deliver real-time, reliable, cost-efficient, and privacy-preserving CFA, offers a scalable, practical pathway for real-time carbon emission monitoring and supports improved sustainability practices.

H.-J. Wang, M.-R. Zhang, Z. Chen et al. · 0 citations

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