GX & Decarbonization Research

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…

Dana Golden, Aruna Balasubramanian, Niranjan Balasubramanian

This paper examines the effectiveness of renewable energy certificates (RECs) and power purchase agreements (PPAs) for data centers driven by AI demand growth. Using a game-theoretic model and difference-in-differences analysis with a novel…

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…

W. Mörbe, P. Yogeshwar, E. Hoffmann +1

This study applies drone-based semi-airborne electromagnetics (sAEM) to investigate a graphite deposit critical for renewable energy transition. Focusing on the Kropfmühl deposit in Bavaria, the method combines UAV magnetic field measuremen…

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=…

Dina Qarashay, Farah Aldaghestani

This study examines the role of sustainable management in green retrofitting of existing buildings through a comparison of Jordan and Canada. Using literature review and case studies, it shows the energy and GHG reduction benefits of deep r…

Şamil Mehdi

This paper analyzes the current status and challenges of integrating green technologies in Azerbaijan's tourism industry. It examines renewable energy use, waste management, and ecological certification, identifying high initial investment …

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…

C. Gebara, Maria Flora Andersen, E. Simioni +2

This study uses a hypothetical e-methanol case to examine how different policy accounting requirements affect the accuracy of inventory emissions. Hourly energy matching is crucial; without additionality, emissions can be 14-28 times higher…

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…

Edobot Udo Ekere, S. N. Chukwu

This empirical study examines the impact of various green finance forms on CO2 emissions in six West African countries. It finds that international clean energy funding and biodiversity conservation donations reduce emissions, while infrast…

J. Kean, A. O'Sullivan

European TSOs need accurate day-ahead wind forecasts for bidding zones. This study trains a deep neural network on 1.57 million hourly observations from 36 European BZs using ENTSO-E and Open-Meteo data, outperforming state-of-the-art TSO f…

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…

Nan Jiang, Zeyuan Liu, Zhu Li +4

This paper proposes a power spot market clearing model that relaxes price limits while constraining the average grid price, addressing the failure of narrow price limits under high renewable penetration. Using IEEE 30-bus system and data fr…

Haoyang Fan, Qi Huang, Zhenyuan Zhang +4

This study proposes tunnel transmission for renewable energy in mountainous regions, finding gas-insulated lines cost-effective where environmental costs are high. Multi-physics analysis and lifecycle cost assessment show optimized conducto…

Lissy Langer

This study empirically analyzes the impact of the proposed GHG Protocol revision requiring temporal and spatial matching for RECs in scope 2 accounting, using open European data. It finds that the effect varies by country, time of day, and …

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 (…