This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 1–5 of 5 papers
Junhao Ren, Honglin Gao, Lan Zhao +3
This study develops a multi-agent reinforcement learning framework for self-interested microgrids in P2P electricity trading, addressing renewable generation and demand uncertainties. Each microgrid independently bids price and quantity, op…
Xiaonan Li, Rongxin Sun, Wenxu Zhang +2
This paper proposes a bilevel optimization model for distributed energy storage configuration that integrates wind-solar uncertainty and a tiered carbon trading scheme. It uses SNGAN and K-means for scenario generation, and an improved Ospr…
RPS制度とFIT制度下の再生可能エネルギー導入量の比較
(著者不明)
This paper compares renewable energy adoption under Japan's RPS and FIT schemes. It quantitatively evaluates the effectiveness and operational challenges of both systems, offering insights for policy improvement.
Awuor Ponge, Aisha Adhiambo Awuor
This paper analyzes Africa's green industrialization as a transformative pathway to reconcile economic growth with ecological preservation. By leveraging renewable energy, local processing of transition minerals, and the African Continental…
Mohammad Zardoshti Zadeh Yazdi, Jörn‐Christian Meyer, Grit Walther
This paper proposes a multi-objective optimization model for renewable energy carrier (REC) imports to Europe. It evaluates trade-offs between cost, GHG emissions, and supply security, showing that a supply-risk-optimal approach reduces sec…
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