Performance driven energy costing: A novel analysis of solar photovoltaic cost performance and generation dynamics feeding hydrogen production
Alex Rozycki, Yuanshen Lu, A. Y. Klimenko
Abstract
Background Accurate assessments of levelized unit costs are essential for cost-effective decisions and transitioning to renewable energy and hydrogen production. Balancing short-term returns with long-term decarbonisation is challenging. This model evaluates energy and loss patterns, considers climate and economic trends, and validates the current value of LCOE 30 is €$53.21 ± €6.13 (US$56.61 ± $6.52) per MWh. This to facilitate costs of €38 (US$40) by 2030 and €38 (US$20) by 2050 to reduce hydrogen costs ranging between €7.5 and €13 (US$8 and $14), to €0.95 and €1.90 (US$1 and $2) per kilogram. The novel approach combines production modeling, cost standardization and an iterative performance model based on techno-economic analysis to extend beyond current SOTA methods as promoted. This is done by using VALCOE and OEE with its treatment of capital, configurational scenarios, efficiency, currency fluctuations and governing devaluation rates. It uses this to build a continuous cost function (to improve computational efficiency), that through enhanced sensitivity reveals hidden costs through improved astronomical models paired with continuous solar irradiance functions. This increases accuracy to allow for improved energy and hydrogen cost estimates, which produce a cross-comparable unit-cost function, assessed and validated through various scenarios. This study is part of the Global Techonomics of the Multi-Source Hydrogen Supply Chain, evaluating energy and cost models focusing on Solar in Australia. Results Enhanced performance is achievable through regular maintenance using advanced monitoring systems, drone inspections, and panel cleaning, standardized efficiency, optimized STU based costing, and BIM 6D design especially in areas with high dust and bird populations. Improving on the current SOTA methodology, to incorporate variable devaluation rates, devalued capital, externalities, and standardized costing, enables cross-comparison and reduces the impact of incorrectly devalued components. Also, optimizing panel tilt and reducing shading can significantly boost energy capture. Efficient monitoring and automated analysis ensure initiative-taking maintenance, tracking options and cost reduction, potentially saving up to 3.1% 1 per MWh in operational costs. Conclusions Integrating engineering and techno-economic analysis offers a thorough method for evaluating energy infrastructure, addressing traditional LCOE 30 cost overestimation, via a novel metric called GCOE 30 . The limitation of the current SOTA methodology needing further research to determine how they can be optimized to develop comparable results, particularly in non-steady state markets. Advanced monitoring technologies, BIM and drones reduce costs and extend solar panel lifespan. Site-specific factors such as community impact and connectivity are crucial for cost management and efficiency. This allows the successful integration of storage and smart trading to boosts system output and returns. Finally, Emerging technologies, like perovskite cells with silicon, have the potential to enhance yields altering the viability of generation assets undergoing a typical LTO continuous upgrade. The authors’ plan to extend this research by focusing on dynamic cost modeling and predicting energy transitions to support sustainability goals in non-steady state markets.