The rapid expansion of solar photovoltaic capacity in Abu Dhabi presents a growing challenge of daytime energy surplus and grid curtailment. This paper proposes a circular solar-hydrogen energy optimization framework that transforms curtailed solar electricity (conventionally treated as waste) into a recoverable resource through green hydrogen production, storage, and nighttime re-electrification. The system integrates three distributed solar generation sources unique to the Abu Dhabi urban and coastal context: (i) building-integrated photovoltaic thin-film sheets applied to building envelopes and rooftops; (ii) offshore floating solar arrays positioned along the Abu Dhabi coastal shelf; and (iii) solar canopy domes installed over highway flyovers and bridge decks. Daytime surplus electricity is directed to polymer electrolyte membrane electrolysers for producing green hydrogen, which is stored and subsequently converted back to electricity via fuel cells during the evening and nighttime demand window, completing a 12-hour circular storage rotation. The dispatch strategy is formulated as a mixed-integer linear programming model that allocates generation across three operating modes (direct grid supply, hydrogen production, and hydrogen-to-power reconversion) while minimising curtailment and maximising net energy value delivered to the Abu Dhabi transmission grid. The circular economy principle is operationalised through a quantified waste-recovery key performance indicator, measuring the percentage of otherwise-curtailed solar energy recaptured through the hydrogen loop. Simulation results based on Abu Dhabi irradiance profiles and grid demand data demonstrate the technical feasibility of the proposed framework and quantify the round-trip efficiency, daily hydrogen throughput, and carbon displacement potential. The proposed model provides a replicable optimisation template for solar-surplus economies, and lays the groundwork for a full technoeconomic evaluation and UAE-wide deployment study as future research directions.

Green hydrogen is a promising solution for decarbonizing hard-to-abate sectors; however, its production is challenged by the mismatch between intermittent renewable generation and fixed hydrogen demand. This paper proposes an integrated optimization framework for the capacity planning and operational scheduling of a grid-connected green hydrogen system under variable electricity tariffs. The system consists of photovoltaic generation, a proton exchange membrane electrolyzer, and a hydrogen storage tank supplying a fixed hydrogen demand. A bi-level optimization approach is adopted, where Particle Swarm Optimization determines optimal system sizing, while a linear programming-based Energy Management System optimizes hourly operation. The objective is to minimize the levelized cost of hydrogen by jointly optimizing design and dispatch decisions. The framework is evaluated under three representative solar irradiance scenarios (high, average, and low) to capture resource variability. Results show that solar availability significantly impacts both system sizing and operational strategy. The lowest levelized cost of hydrogen of 6.36 USD/kg is achieved under favorable solar conditions, while limited solar availability leads to increased reliance on grid electricity and higher costs. The findings highlight the importance of integrating storage and flexible operation to shift production toward low-tariff periods.

Green hydrogen is a potential decarbonization option for oil refineries, where hydrogen is already used in hydrotreating and hydrocracking. While previous studies have examined hydrogen production economics, limited work has integrated refinery simulation, hydrogen supply optimization, and refinery margin analysis for a UAE refinery. This study evaluates the techno-economic impact of replacing grey hydrogen with green hydrogen in the UAE's refinery operations, using the Ruwais refinery as a case study. The methodology combines CAESAR refinery simulation, green hydrogen supply-system modeling, and refinery economic and emissions analysis. CAESAR estimates refinery operation, product output, utility use, and hydrogen demand, which is used to size an off-grid solar-based green hydrogen system. The refinery requires 270,2 kt/yr of hydrogen. Meeting this demand requires 9.4 GWp of PV, 5.5 GW of electrolysis, and 824.6 tonnes of hydrogen storage, resulting in an LCOH of 6.32 USD/kg H2. Switching to green hydrogen reduces the refinery margin from 12.1 to 7.1 USD/bbl and avoids 2.7 MtCO₂/year. The results suggest that refinery-scale green hydrogen can substantially reduce emissions, but remains economically challenging under current technology costs, requiring carbon pricing, policy support, or future cost reductions to become competitive.

Residential rooftop photovoltaic (PV) systems can support the UAE's transition toward sustainable energy, but their adoption depends strongly on residents' perceptions and readiness. This exploratory qualitative study examines the factors shaping UAE residents' willingness to adopt rooftop PV through semi-structured interviews with four purposively selected participants representing diverse ages, genders, and income levels. Transcripts were analyzed using word-frequency, Classical Content, thematic, and sentiment analysis. Four themes emerged: economic considerations, technical performance and reliability, structural and residential constraints, and adoption enablers. Upfront costs, financing, maintenance, and provider trust were key concerns, while long-term savings, environmental benefits, social influence, and government support encouraged adoption, with priorities varying by income group. Despite these concerns, sentiment analysis revealed consistently positive attitudes toward rooftop PV across all participants. Although the small sample limits generalizability, these preliminary findings can help UAE policymakers and PV providers design targeted financial incentives, reliability assurances, and awareness campaigns to support residential PV adoption.