This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing 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 2261–2280 of 4867 papers
Breen M.
This paper analyzes policy misalignment and systemic barriers to sustainable aviation fuel (SAF) deployment in Europe, employing a Multi-Level Perspective (MLP) informed stakeholder analysis. It identifies that lack of policy coherence and …
D'Amore F.
This paper examines the policy sequencing approach for green energy reform in Turkmenistan, focusing on the transition from framework laws to implementable steps. It provides insights into designing effective energy transition policies in d…
Vivoda V.
This paper analyzes the conditions attracting investment in critical minerals processing, beyond mining. It focuses on policy and economic factors outside the mine, examining how to strengthen supply chains for clean energy technologies.
Fauré E.
This paper presents four low-carbon scenarios for Sweden that go beyond GDP growth, exploring the possibility of reconciling degrowth economies with climate targets.
Salikhov M.R.
This paper presents scenarios for decarbonizing the Russian economy, exploring the possibilities and challenges of energy transition.
Lijun Liang, Mengze Ma, Jianglin Feng
This study addresses carbon peaking pathways in topographically constrained inland Chinese cities, using Chongqing as a case. Using an extended STIRPAT model and ridge regression, it identifies population, industrial structure, and energy m…
E. Figini, Mario Paolone
This paper proposes a framework for small-scale data centers to participate in the day-ahead electricity market with a carbon-aware, risk-averse bidding strategy that leverages flexibility from local energy resources, waste heat recovery, a…
Akhmad Rifkyansyah, Rahmat Setiawan
This study analyzes the role of the merit order in PLN and PLN Nusantara Power, linking operational efficiency, Power Purchase Agreement (PJBTL) structure, and digital transformation. Using a systematic literature review, it finds that the …
Ali S. Aljumah, Mohammed H. Alqahtani, A. Shaheen +1
This paper proposes a Modified Newton-Raphson-Based Optimizer for optimal power flow with renewable photovoltaic sources. It adds adaptive crossover and sigmoid decay, tested on IEEE 30-bus system. Includes probabilistic OPF with solar unce…
Yannick Heiser, J. Kazempour, F. Pourahmadi
This paper proposes a predict-then-contextual-optimize framework for a power trader to engage in arbitrage between day-ahead and balancing electricity markets. It uses a probabilistic classifier to decide when to deviate from the power fore…
Umud Shokri
Amid the 2026 Iran War, the energy relationship between the GCC and Asia-Pacific is becoming dual-track: hydrocarbon interdependence persists while cooperation grows in renewables, hydrogen, ammonia, and transition finance. Using project-le…
Yue Lyu
This study proposes a neurocognitive-cultural entropy framework (LSF) to reconcile deep decarbonization with biocultural heritage preservation. By robotically replicating Ming-era masonry, it achieves minimal cultural entropy deviation (ΔH=…
Jan Niklas Lettner, Hadeer El Ashhab, V. Hagenmeyer +1
This paper compares task-specific ML models (NHITS+QRA, Normalizing Flow) with Time Series Foundation Models (Moirai, ChronosX) for day-ahead probabilistic electricity price forecasting in European bidding zones. TSFMs outperform in CRPS an…
Antonio Pesenti, A. O'Sullivan
This paper combines deep neural networks with explainable AI (XAI) to analyze electricity price drivers across 39 European bidding zones. Using SHAP, it finds that renewable energy (especially solar) plays a disproportionately important rol…
Peng Ji, Yiman Liu, Nan Li +1
This paper develops a bilevel optimization framework for nuclear power plants participating simultaneously in energy, reserve, and capacity markets. The model captures system operator welfare maximization and nuclear operator profit maximiz…
Xin Zhao
This paper proposes a joint bidding model for multiple electricity markets (day-ahead, real-time, reserve, frequency regulation) under price limits, incorporating risk preferences. Using 17,520 hours of data from 4 trading zones, the method…
Francesca Curinga, Lorenzo Vitulano, A. Zani
This paper presents a modeling framework to assess the impact of alternative bidding behaviors on price formation in the Italian Day-Ahead Market (2023-2024), supporting a regulatory investigation. It focuses on strategic bidding by combine…
Umair Khan, Shouwen Wang, Zhaohui Qin +4
This paper proposes the PODO model, a financial framework using Security Token Offerings (STOs) to enable fractional public investment in renewable energy and early capital recovery. Quantitative simulations using Korean power market data (…
Chenyu Su, Yixing Du, Anders Avelin +2
This study proposes four KPIs (NLRR, IRRE, FRM, IFI) to assess power system flexibility under high renewable penetration. Applied to Sweden's SE3 zone in 2024, results show high flexibility adequacy with limited ramping shortages (IRRE 0.03…
Zhihan Sun, Wenbo Sun, Tianhao Yu +3
This review focuses on the molecular design of organic and porous framework cathodes for aqueous zinc-ion batteries (AZIBs). It systematically analyzes soft organic small molecules, polymers, MOFs/COFs with structural tunability and redox a…
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