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 21–40 of 1789 papers
Yuheng Li, Gang Lin, Shenggong Li +3
A study assessing the development potential of floating photovoltaics (FPV) in China under its carbon-neutrality framework. It examines the energy-water-land nexus, analyzing how FPV deployment interacts with water resources and land constr…
Lia Firyanti
A book chapter reviewing how AI—intelligent energy management, machine learning, smart grids, microgrids, IoT, predictive analytics, battery management, solar forecasting, digital twins—can improve renewable energy performance and resilienc…
Jyoti Prakash Myageri, Math Abhishek Gurulingayya
This review synthesizes recent evidence on the global economic and environmental significance of renewable energy, drawing on IRENA, IEA, and ILO data covering investment, employment, LCOE, energy security, and access, alongside GHG mitigat…
Moritz Johann Gräfe, Samuel Kainz, Vasilis Pettas +6
Hourly simulation of the Lillgrund offshore wind farm examines how wind- vs solar-driven negative prices affect operation, economics and environmental value under revenue-triggered curtailment. Wind-driven negative hours carry high fatigue …
Zilio, Samuele, Zandonella Callegher, Claudio, Prina, Matteo Giacomo +1
This repository publishes spatially explicit renewable energy potential estimates from Task 2.2 of the LIFE-funded PLANtoACT project (2025-2028), covering five European pilot regions in Germany, France, Italy, Portugal, and Romania. PV pote…
Yu, Minghao, Tang, Yufei, DeVito, Louis +3
This work develops a physics-informed deep learning framework that estimates three-dimensional subsurface velocities in the Florida Straits from 35 gridded surface and hydrographic input channels. It aims to improve depth-resolved reconstru…
Tamang, Samiksha, Grandelli, Patrick, VanZwieten, James +2
OTEC generates continuous baseload power from the temperature difference between warm surface and cold deep seawater. This study updates a power prediction model for mid-scale (20-30MW) OTEC plants using ocean temperature gradient data and …
Do Prado, Victor, Redigan, Noah, Mountcastle, Emily +5
Marine hydrokinetic energy, notably the Gulf Stream, offers a predictable, continuous renewable resource for coastal electrification and grid resilience. This senior design project builds a high-fidelity hardware-in-the-loop (HIL) platform …
Singh, Shreepooja, Singh, Deepi, Bhansali, Gaurav +1
Proposes a hybrid energy storage system (HESS) that splits tidal and wave power fluctuations by frequency, with a battery handling bulk shifts and a supercapacitor absorbing high-frequency transients. A real-time co-simulation framework com…
Emamdoost, Nazila, Sharman, Krish Thiagarajan, Shoefs, Franck +1
Marine biofouling on offshore wind, wave, and tidal devices raises hydrodynamic loads, shortens fatigue life, and increases inspection and maintenance needs. This study proposes an integrated AI framework combining deep-learning image class…
Jahanbakhsh, Yashar, Jamaleddin, Neda, Gabr, Mohammed
This study experimentally investigates the monotonic axial capacity of a retrievable Ocean Petal Anchor (ROPA) intended as a mooring/foundation solution for offshore renewable energy devices such as wave and tidal systems. It addresses the …
Gilani Nejad, Mehregan, Villacres, Daniela, Iwakin, Oluwabunmi +3
Wave energy is promising but stochastic waves and oscillatory converters create large power variability, complicating grid and microgrid integration. This paper proposes a hierarchical control scheme for battery-integrated WEC arrays that s…
Vourdoubas, John
This study assesses a 31.29 kWp solar PV system (48,500 kWh/yr) plus 147.64 kWh Li-ion battery storage to meet the electricity demand of an existing 3,300 m² grid-connected greenhouse in Crete. Combined with locally sourced solid biomass fo…
Dr. Yan Lu, Qing-Xiu JIN, Jian-Jun YU +3
A global monthly dataset of compound wind–solar–hydropower climate-resource indices (CEI/CED) on a 1° grid, derived from ERA5 and six CMIP6 models for 1950–2100 under SSP2-4.5 and SSP5-8.5. It enables analysis of compound low-resource event…
Blázquez M.
Examines how guarantees of origin interact with competition in spot electricity markets. Without an abstract, the exact method is unclear, but it likely analyzes how renewable certificates affect market competition and price formation, link…
Maria Antonietta Clerici
Using GIS, this study examines Emilia-Romagna's 350 m "solar belts" around industrial and commercial sites, legally designated as suitable for ground-mounted PV. It finds these belts overlap extensively with ordinary farmland and high-quali…
Dıpu Sarkar, Yanrenthung Odyuo, Abraham Lomi
This chapter reviews the convergence of renewable energy technologies with power system characteristics and the challenges of high renewable penetration. It examines variability, reduced inertia, bidirectional flows, and infrastructure cons…
Thilo Wiertz, Benjamin Schuetze, Rosa Lehmann +3
This theme issue introduction foregrounds the spatialities and scales of renewable energy expansion, arguing that rollout is uneven and deeply contested. Drawing on cases from Morocco, Jordan, Namibia, Mexico, Brazil, Peru and Ecuador, it l…
Raihan Uddin, Nadia Hossain Riya, Anik Datta +8
A multi-country study identifying critical bottlenecks to renewable energy deployment and examining policy interventions for a sustainable green energy transition. Authored by researchers across Bangladeshi, Malaysian, Finnish and other ins…
Jolaolu O, Oladiran A, Osibamowo D
This paper presents a physics-driven AI digital twin that integrates open-source geospatial data (OpenStreetMap) with physics-constrained machine learning to optimise solar infrastructure planning. A modular physics engine computes building…
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