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At least 19 records

Your Clean Graphene is Still Not Clean

Researchers working with thin samples, such as monolayer graphene, are consistently struggling against contamination. Indeed, the problem of hydrocarbon contamination is known from the earliest days of electron microscopy and efforts to reduce this problem are ubiquitous to almost all high-vacuum experiments. Accurate knowledge of the behavior of such contamination is essential for electron beam (e-beam) based atomic fabrication, where it is aspired to select and control matter on an atom-by-atom basis. Here, the vexing question of hydrocarbon contamination on graphene is taken up. Image intensity is used to directly reveal the presence of diffusing hydrocarbons on ostensibly clean graphene. These diffusing hydrocarbons are previously inferred but not directly observed. Surprising dynamic variations of the concentration of these hydrocarbons impels questions about their origin. Here, some possible explanations are presented and some tentative conclusions are drawn. This work updates the conceptual model of “clean graphene” and offers refinements to the description of e-beam induced hydrocarbon deposition.

atomic fabrication

Optimizing a chemical cleaning protocol to determine the nickel isotopic composition of ancient seawater from carbonates

Reconstructing the ancient marine cycle of Ni, a trace metal in the oceans essential to enzymes regulating the C, N, and O cycles, would inform how Ni bioavailability shaped early life. The Ni isotopic composition of seawater (δ 60 Ni SW ) through time could provide insight, but this approach requires sedimentary archives that faithfully record δ 60 Ni SW . Carbonates are an often-used record of seawater chemistry, but contaminants could bias the measured δ 60 Ni of bulk sediment. To isolate the true carbonate-bound δ 60 Ni signal, we optimized a chemical cleaning protocol designed to minimize non‑carbonate Ni contributions and maximize carbonate recovery. We analyzed ODP Site 1007 sediments and evaluated oxidative and reductive pre-cleaning steps and carbonate dissolution protocols. Our results show that only reductive cleaning significantly altered the subsequent carbonate leachate composition, lowering Ni/Ca ratios by up to 60% and δ 60 Ni values by as much as 0.4 ‰. In contrast, δ 60 Ni values were largely insensitive to premature carbonate dissolution during pre-cleaning or to partial leaching of silicates during carbonate dissolution, even at higher acid molarities or longer reaction times. We recommend an evidence-based protocol that removes hydro-soluble salts and clays, applies reductive cleaning and oxidative cleaning for certain sample compositions, and dissolves carbonate using 0.5 M acetic acid, adjusted to pH 5. Using these results, we infer a ∼ 0.9 ‰ Ni isotopic fractionation between chemically cleaned deep-water carbonates (+0.4 ± 0.1 ‰) and deep seawater. This method development is a key step toward accurately reconstructing ancient marine Ni cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Advancing Affordable, Efficient, and Clean Transportation

Clean Cities and Communities is a U.S. Department of Energy (DOE) partnership to advance clean transportation nationwide. More than 75 DOE-designated Clean Cities and Communities coalitions work locally in urban, suburban, and rural communities to strengthen the nation's environment, energy security, and economic prosperity. As partners with DOE's Vehicle Technologies Office (VTO), coalitions work to deploy affordable, efficient, and clean transportation; energy efficient mobility systems; and fuel-saving technologies and practices.

ADVANCED PROPULSION SYSTEMS

U.S. State Renewables Portfolio & Clean Electricity Standards: 2024 Status Update [Slides]

This report provides an overview and status update on U.S. state renewables portfolio standards (RPS) and has been expanded from previous editions to also cover 100% clean electricity standards (CES) adopted by a growing number of states. The report, published in slide-deck form along with accompanying data files, describes recent legislative revisions, key policy design features, compliance with interim targets, past and projected impacts on clean electricity development, and compliance costs. The 2023 edition presents historical data through year-end 2023 and projections out to 2050. Key trends from this edition of the report include the following: -Evolution of state RPS and CES programs: States continue to refine and revise their RPS policies, often by adopting higher targets and/or broader CES policies. Among the 29 states plus DC with an RPS, 16 have RPS targets of at least 50% of retail sales, and 4 states have a 100% RPS. An additional 16 states have adopted a broader 100% CES. -Historical impacts on renewables development: Almost half of all growth in U.S. renewable electricity (RE) generation and capacity since 2000 is nominally associated with state RPS requirements. That percentage has declined over time to 35% of all U.S. RE capacity additions in 2023, though in certain regions RPS policies continue to play a dominant role in driving RE growth. -Future RPS and CES demand and incremental needs: The combined demand for clean electricity from RPS and CES policies will grow from roughly 500 TWh today to 1700 TWh by 2050. Accounting for current supplies—including existing nuclear and hydroelectric generation eligible for CES targets—RPS and CES policies will require 900 TWh of new clean electricity by 2050, equivalent to roughly 3x the historical rate of RPS-buildout. -RPS target achievement to-date: States have generally met their interim RPS targets in recent years, with only a few exceptions reflecting unique, state-specific issues. Most CES targets are not yet in force, and so little compliance experience to-date. -REC pricing trends: Prices for NEPOOL Class I RECs remained at roughly $\$40$/MWh over the past year, just below ACP rates in the larger state markets, while PJM Tier I REC prices continued to rise, reaching $\$35$/MWh by year-end 2023 and surpassing ACP levels in some states. Prices for solar RECs remained relatively stable, and continue to exhibit wide variation across states, with the highest prices ($200-450/MWh) in NJ, MA, and DC. -RPS compliance costs: RPS compliance costs average roughly 4% of retail electricity bills across RPS states, though vary widely from state to state, with the highest costs (11-12% of retail bills) in states with solar carve-outs and high SREC prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Consumer Benefits of Clean Energy: The resilience value of residential solar + storage systems in the continental U.S.

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. Clean energy resources that are located behind the meter have the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Solar plus storage systems (PVESS) are clean energy resources that can supply backup power without requiring fuel resupply or increasing local emissions. This report examines the regional value of PVESS for resilience by calculating a benefit-cost ratio (BCR) that considers the annual resiliency benefits of PVESS and the annualized cost of the investment. In addition, we estimate the expected technical mitigation potential of PVESS systems at the county-level to these expected events, and characterize the customer interruption costs by determining the value of lost load at the state level.

14 SOLAR ENERGY

From Silos to Synergy: Identifying a Roadmap for Cross-Sector Research to Accelerate the Clean Energy Transition

The U.S. Department of Energy's blueprints for the transportation, buildings, and electricity sectors call for substantial reductions in greenhouse gas (GHG) emissions by 2050. These plans focus on zero-emission vehicles, investments in transit, energy-efficient buildings, and the widespread adoption and deployment of renewable energy technologies like solar photovoltaics (PV), energy storage and energy-efficient appliances. However, these sectors are often studied and modeled in isolation, overlooking how household decisions to adopt clean technologies in one sector influence others. This study, led by an interdisciplinary team at the National Renewable Energy Laboratory (NREL), explores opportunities for cross-sector collaboration to drive more effective and equitable decarbonization. Through discussions with 22 NREL researchers across transportation, building, solar, and grid sectors, the study highlights the need for integrated tools and models that capture interactions between these sectors. Key insights include the need for data standardization and interoperability to enable cross-sector analysis and decision-making. Strengthening utility partnerships is also critical to align energy policies with decarbonization goals and manage the increased demand for renewable energy. The study also emphasizes the importance of equity in the clean energy transition, calling for targeted incentives and support to ensure that low-income and underserved communities benefit from clean technologies like electric vehicles and energy-efficient appliances. To support these efforts, innovative funding mechanisms must be expanded to facilitate interdisciplinary research, such as city-specific decarbonization plans and federal projects like DOE"s Standard Scenarios. By encouraging collaboration and integrating cross-sector insights, this study aims to provide a roadmap to accelerate the clean energy transition and ensure it is both sustainable and inclusive.

14 SOLAR ENERGY

Life Cycle Analysis of Greenhouse Gas Emissions of Clean Fuels with the R&D GREET 2024 Model

This document summarizes research on the life cycle greenhouse gas (GHG) emissions rates from the production and use of clean fuels to support a new version of the Research and Development Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (R&D GREET) model, R&D GREET 2024 In this effort, Argonne National Laboratory (ANL) focuses on clean fuel pathways that are readily available in the market or are emerging in the near term. The selected pathways represent clean fuel technologies that convert biomass- and/or waste-based feedstocks to liquid and/or gaseous fuels for the transportation sector and other potential uses. The pathways are configured in R&D GREET 2024 with up-to-date feedstock-to-fuel life cycle inventory (LCI) data. Additionally, a new tab has been added to R&D GREET 2024 called “Clean Fuels” which allows the user to easily change inputs and access LCA results. Argonne does not warrant that the results presented in this report are consistent with the requirements of any particular regulatory or incentive program. Users interested in specific programs that reference GREET are encouraged to review guidance specific to those programs if and when it is available to determine appropriate means of compliance and contact the relevant responsible agencies for those specific policies or programs.

09 BIOMASS FUELS

New Mexico Clean Energy and Resilience Growth (NM CERG) Cluster

The New Mexico Clean Energy Resilience and Growth (NM CERG) project was designed to foster a clean energy cluster in New Mexico by providing a robust pipeline of support for clean-energy technology startups. By leveraging the expertise and resources of national laboratories, universities, and regional partners, the project contributed to a deeper understanding of how public-private partnerships can enhance the commercialization of innovative clean energy technologies. The project explored the key challenges faced by startups, such as securing capital, rapid prototyping, technology validation, and transitioning from research to market-ready products.

02 PETROLEUM

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence

Hydrogen and its Vital Role in a Clean Energy Future

Large-scale, low -cost hydrogen production can enable an economically competitive, secure, and environmentally beneficial future energy system across multiple sectors. Furthermore, clean hydrogen can address specific sectors that are hard to decarbonize (e.g., heavy-duty trucking, load-following electricity, iron, steel, and cement) and can help the U.S. meet the net zero carbon goal by 2050. To achieve this goal, tens of millions of metric tons of clean, reliable, and affordable hydrogen will be needed annually1. In 2021, the Hydrogen Energy Earthshot was launched, and its goal is to reduce the cost of clean hydrogen to $1 per $1 kilogram in 1 decade (1 1 1) 2. One very promising pathway for large-scale hydrogen production is water splitting. Water splitting technologies range from commercial technologies such as electrolyzers to approaches that are at a much earlier stage of development, such as photoelectrochemical (PEC) and thermochemical (TCH) processes. All these water splitting pathways offer diverse benefits in energy storage, grid services, and cross-sector emissions reductions while taking advantage of the diverse domestic resources. However, critical materials-, component- and system-level challenges must be addressed to improve efficiency and durability and reduce cost. To address these barriers and move these promising and high impact technologies forward, the HydroGEN Advanced Water Splitting Materials (AWSM) and the H2 from the Next-generation of Electrolyzers of Water (H2NEW) consortia were formed and supported by the Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO). HydroGEN (https://www.energy.gov/eere/h2awsm/) consortium, established in 2016, is an Energy Materials Network (EMN) that aims to accelerate the materials R&D of low technology readiness level (TRL) advanced water splitting (AWS) technologies. The consortium comprises five core national laboratories and focuses on four early-stage AWS pathways: alkaline exchange membrane (AEM) electrolysis, proton conducting solid oxide electrolysis (p-SOEC), photoelectrochemical, and thermochemical water splitting. Liquid alkaline and PEM electrolyzers are already commercial and significant advancements in oxygen conducting solid oxide electrolysis cells (o-SOECs) have been realized. Yet, these systems are still too expensive and not sufficiently durable for wide-scale commercialization. To enable high-volume manufacturing of affordable, durable, efficient electrolyzers, H2NEW (https://h2new.energy.gov/), another multi-lab consortium, was established in 2020. This comprehensive, concerted effort is focused on overcoming barriers related to components and materials integration and scale-up to achieve performance, durability, with an initial focus to achieve $2/kg H2 by 2026.

AEM

Building a Clean Energy Workforce: Best Practices for State Energy Offices

As federal investments into the clean energy economy are underway, State Energy Offices (SEOs) are engaging in efforts to grow the workforce through the creation and/or funding of workforce initiatives that recruit, train and support pathways into energy efficiency and clean energy jobs. This report provides a summary of clean energy workforce development best practices, supplemented by case studies and lessons learned from several SEOs that showcase these strategies in practice. SEOs can reference this resource as they implement, manage, oversee, and/or evaluate efforts their offices are undertaking through various federally funded programs.

clean energy

Measurement and analysis of the Doppler broadened energy spectra of gamma radiation originating from the annihilation of positrons incident on clean and adsorbate-covered surfaces

We present measurements and theoretical modeling demonstrating the capability of coincidence Doppler broadened (CDB) annihilation gamma spectroscopy to provide element-specific information from the topmost atomic layer of surfaces. Our measurements show that the energy spectra of Doppler-shifted annihilation gamma photons emitted following the annihilation of positrons from the topmost atomic layers of clean and adsorbate covered surfaces of gold (Au), silver (Ag) and copper (Cu) differ significantly. The shape of the Doppler-broadened gamma spectrum, as analyzed using ratio curves, indicates that the elemental composition of the surface can still be identified despite contributions from positronium annihilation and a significant reduction in core electron annihilation. We estimate the chemical composition of the various probed surfaces by modeling the ratios of the measured Doppler spectra with respect to the Doppler spectra from a clean Cu surface using a linear combination of calculated ratio curves. The fitting of the experimental ratio curves was used to obtain an estimate of the elemental composition of Cu surfaces with sulfur segregation, oxygen adsorption, a thin film of Selenium (Se), and a single layer of graphene (SLG). A similar analysis was performed on the Ag surface with environmental adsorbates, the same surface after argon ion sputtering, as well as a sputter cleaned Au surface. The surface compositions obtained from the analysis of the CDB data were compared to the compositions obtained using positron annihilation induced Auger electron spectroscopy (PAES). Our results show that CDB can detect, identify, and quantify, sub-monolayer adsorbates and a single atomic layer deposited on metal substrates.

Lotfimarangloo, Sima [Univ. of Texas, Arlington, T

A Reduced-Temperature Process for Preparing Atomically Clean Si(100) and SiGe(100) Surfaces with Vapor HF

Silicon processing techniques such as atomic precision advanced manufacturing (APAM) and epitaxial growth require surface preparations that activate oxide desorption (typically >1000 °C) and promote surface reconstruction toward atomically clean, flat, and ordered Si(100)-2 × 1. Here, in this study, we compare the aqueous and vapor phase cleaning of Si and Si/SiGe surfaces to prepare APAM-ready and epitaxy-ready surfaces at lower temperatures. Angle resolved X-ray photoelectron spectroscopy (ARXPS) and Fourier transform infrared (FTIR) spectroscopy indicate that vapor hydrogen fluoride (VHF) cleans dramatically reduce carbon surface contamination and allow the chemically prepared surface to reconstruct at lower temperatures, 600 °C for Si and 580 °C for a Si/Si 0.7 Ge 0.3 heterostructure, into an ordered atomic terrace structure indicated by scanning tunneling microscopy (STM). After thermal treatment and vacuum hydrogen termination, we demonstrate STM hydrogen desorption lithography (HDL) on VHF-treated Si samples, creating reactive zones that enable area-selective chemistry by using a thermal budget similar to CMOS process flows. We anticipate that these results will establish new pathways to integrate APAM with Si foundry processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Laboratory Testing of Portable Air Cleaner Products for Energy Efficiency and Clean Air Performance at Various Fan Settings [Slides]

This document contains the results of a product review and laboratory testing experiment of portable air cleaning devices (PACs). Thirty-four commercially available PACs were reviewed, and from those, 7 products were purchased and underwent AHAM AC-7 clean air delivery rate (CADR) testing. The following research questions were explored: 1) What is the relationship between clean air delivery rate (CADR) and energy across a range of products and what is the general decrement in CADR as a result of operating at lower fan speeds? 2) How might the multiple units at lower power compare to fewer, larger units at full power in terms of energy efficiency and total cost? 3) How do the measured CADR, power, and efficiency compare to the manufacturer specs? 4) Are there product attributes that can be identified that might contribute to better CADR/W performance?

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves

We compare multiple foreground-cleaning pipelines for estimating the tensor-to-scalar ratio, r, using simulated maps of the planned CMB-S4 experiment within the context of the South Pole Deep Patch. To evaluate robustness, we analyze bias and uncertainty on r across various foreground suites using map-based simulations. The foreground-cleaning methods include: a parametric maximum likelihood approach applied to auto- and cross-power spectra between frequency maps; a map-based parametric maximum-likelihood method; and a harmonic-space internal linear combination using frequency maps. We summarize the conceptual basis of each method to highlight their similarities and differences. To better probe the impact of foreground residuals, we implement an iterative internal delensing step, leveraging a map-based pipeline to generate a lensing B-mode template from the large aperture telescope frequency maps. Our results show that the performance of the three approaches is comparable for simple and intermediate-complexity foregrounds, with σ(r) ranging from 3–5 ×10 −4 . However, biases at the 1σ–2σ level appear when analyzing more complex forms of foreground emission. By extending the baseline pipelines to marginalize over foreground residuals, we demonstrate that contamination can be reduced to within statistical uncertainties, albeit with a pipeline-dependent impact on σ(r), which translates to a detection significance between 2σ and 4σ for an input value of r = 0.003. These findings suggest varying levels of maturity among the tested pipelines, with the auto- and cross-spectra-based approach demonstrating the best stability and overall performance. Moreover, given the extremely low noise levels, mutual validation of independent foreground-cleaning pipelines is essential to ensure the robustness of any potential detection.

astronomy data analysis

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI