Browsing by Author "Escobar Moragas, Rodrigo Alfonso"

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    Assessing system-level synergies between photovoltaic and proton exchange membrane electrolyzers for solar-powered hydrogen production
    (2024) Arias Olivares, Ignacio Javier; G. Battisti, Felipe; Romero Ramos, J. A.; Pérez, Manuel; Valenzuela, Loreto; Cardemil Iglesias, José Miguel; Escobar Moragas, Rodrigo Alfonso
    This study delves into the techno-economic benefits of integrating Proton Exchange Membrane electrolyzers with photovoltaic systems for hydrogen production, with a keen focus on cost optimization strategies. A comprehensive analysis of several system scales and cost scenarios unveils the critical roles of Proton Exchange Membrane stack systems and the Balance of Plant components in influencing capital expenditures. Notably, the research identifies that incorporating the grid via a complementary Power Purchase Agreement, alongside clipped solar energy, innovatively redistributes cost elements. This approach significantly reduces the levelized cost of hydrogen, thereby enabling the feasibility of hydrogen production in regions characterized by low solar radiation at the cost of high grid electricity penetration. Sensitivity to energy costs, accentuated by different integration schemes, highlights the pivotal role of the stack cost and the Balance of Plant cost reductions in achieving economic viability for large-scale deployments. The study underscores the necessity of holistic cost optimization, revealing that strategic grid support coupled with solar energy enhances the techno-economic performance and broadens the scope for renewable hydrogen production in less favorable locales. These insights offer invaluable guidance to stakeholders, advocating for advanced integration strategies that promise both efficiency and financial sustainability in the burgeoning field of renewable hydrogen production systems.
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    Assessing the integration of solar process heat in the dairy industry: A case study in Chile
    (2024) Fuentes, Francisco; Pailahueque, Nicolás; Muñoz, Iván; Escobar Moragas, Rodrigo Alfonso; Cardemil Iglesias, José Miguel
    Solar heat for industrial processes (SHIP) in the dairy industry has attracted considerable interest during the last few years. The present study assesses the use of solar heat in dairy factories applying Ultra High Temperature pasteurization, using three locations in Chilean central and southern regions as case studies. The analysis utilizes numerical simulations considering annual energy performance, economic feasibility, size of thermal energy storage (TES), and the economic competitiveness for four different solar thermal collector technologies: Flat Plate Collector (FPC), Evacuated Tube Collector, Parabolic Trough Collector (PTC), and Linear Fresnel Reflector. The numerical simulations were conducted using the TRNSYS software for varying meteorological parameters and hourly heat load profile. The integration scheme selected for the implementation of the SHIP systems considers supply level to reheat the boiler's feedwater. The results show that the minimum levelized cost of heat ranges between 78 USD/MWh - 79 USD/MWh, with FPC and PTC showing the lower values. For all the companies analyzed, the minimums values of LCoH were observed when considering specific storage volumes between 75 l/m2-120 l/m2, 2 - 120 l/m 2 , indicating a strong relationship between solar resource availability and financial performance.
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    Irradiance separation model parameter estimation from historical cloud cover statistical properties
    (2024) Castillejo Cuberos, Armando; Cardemil Iglesias, José Miguel; Boland, J.; Escobar Moragas, Rodrigo Alfonso
    Irradiance separation models allow the decomposition of Global Horizontal Irradiance into Diffuse Horizontal and Direct Normal Irradiances. These models need fitting to the irradiance characteristics of the location of interest using locally measured ground data. For locations that only measure Global Horizontal Irradiance, current state of the art establishes the use of parameters obtained for another location that measures the three components, with similar climate characteristics. Nevertheless, this results in a lack of localized character for estimates and requires fitting model parameters for all possible climates, which can be infeasible given data availability. This work presents a novel approach based on the hypothesis that the separation model's parameters are a function of the statistical properties of satellite-derived cloud cover estimates. The proposed methodology was evaluated in 23 sites covering all main Koppen-Geiger climatic types and different cloud coverage properties using the Boland-Ridley-Lauret diffuse fraction model. The model performs similarly as locally adjusting the model, with Root Mean Square Errors of 0.087-0.15 diffuse fraction units versus 0.077-0.127 for locally optimized parameters, and offers adequate performance across climates and cloud characteristics. These results encourage future research by generalizing parameter estimation for other diffuse fraction models. The main applications for this research are the estimation of irradiance components where no local data is available for model fitting and the enhancement or complementarity of satellite estimates of surface irradiance. Furthermore, it allows the estimation of missing irradiance components due to equipment failure in locations with insufficient data for a representative, locally adapted model.
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    Temporal upscaling of solar radiation components using an analytical model for variability modeling
    (2024) Castillejo Cuberos, Armando; Cardemil Iglesias, José Miguel; Escobar Moragas, Rodrigo Alfonso
    To properly design systems that harness the solar resource, reliable measurements or estimates of its availability are needed. Often, this data is only available at temporal resolutions that are not sufficiently fine to capture the short-term fluctuations of the solar resource, creating uncertainty in the design and performance assessment of solar-powered systems. Synthetic irradiance generation techniques aim to create high temporal resolution estimates starting from lower resolution data, however, a literature review on the topic shows opportunities for improvement regarding the generality of the generation and evaluation approaches. This work proposes novel methods to estimate a quantifiable indicator of short-term variability from hourly data, a new temporal upscaling methodology for time series of arbitrary origin and destination temporal resolution, based on explicit mathematical functions and sufficient generality for application in different contexts, and an improved assessment methodology. The method was applied tor ground and satellite upscaling up to 1 min, resulting in time series with characteristics consistent with those of a higher temporal resolution and exhibit minimum deviations against the original time series characteristics. This method has applications not only for upscaling of low temporal resolution data, but also for gap-filling techniques and the upscaling of hourly solar radiation forecasts.