A Digital Twin Framework Integrating Marine Microclimate Modeling for Reliable and Cost-Effective Design of 100% Renewable Coastal Energy Systems

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a methodology integrating microclimate modeling with optimization for coastal renewable system design, useful for further development of digital twin applications.

🏢実務担当者:Offers a decision-support tool for designing cost-effective and reliable coastal renewable energy systems, with explicit handling of marine environmental factors.

🏛政策担当者:Highlights the importance of microclimate effects in renewable energy planning, especially for island and coastal regions pursuing energy independence.

<title>Abstract</title> <p>Coastal hybrid renewable energy systems (HRES) are subject to significant performance uncertainty due to harsh marine microclimatic conditions, which distort both technical evaluations and long-term economic projections when neglected. This study proposes a dynamic digital twin framework that integrates high-resolution marine microclimate modeling with a comprehensive techno-economic optimization engine to enable reliable capacity planning of coastal PV–wind–battery systems. The framework explicitly captures key coastal stressors—including salt deposition, humidity-driven thermal loading, and sea-breeze-induced wind enhancement—and dynamically updates the operational behavior of individual system components. The proposed approach is applied to Kish Island in the Persian Gulf using one year of hourly meteorological and electricity demand data (8,760 time steps). A genetic algorithm is employed to evaluate 125 candidate system configurations. The optimal design consists of 2,000 kW of photovoltaic capacity, 1,500 kW of wind power, and 4,000 kWh of battery storage, achieving full renewable energy supply (100% penetration) with a levelized cost of energy (LCOE) of 0.178 $/kWh while satisfying a strict zero loss-of-power-supply probability constraint (LPSP = 0%). The results indicate that salt accumulation reduces average annual PV efficiency by 2.1%, whereas sea-breeze effects increase wind energy production by 3.1%. Ignoring these microclimatic influences leads to a 7.9% underestimation of the LCOE and the selection of an under-sized and unreliable system in the baseline scenario. Overall, the findings demonstrate that marine microclimate effects play a decisive role in coastal system design and lifecycle cost estimation. The proposed digital twin framework provides a transferable and decision-oriented tool for improving forecasting accuracy, reducing investment risk, and enhancing the reliability and robustness of coastal renewable energy infrastructures.</p>

• Research Square https://doi.org/10.21203/rs.3.rs-8823465/v1first seen 2026-06-15 04:42:18