Browsing by Author "Cardemil Iglesias, José Miguel"
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- ItemAnalyzing regional and local changes in irradiance during the 2019 total solar eclipse in Chile, using field observations and analytical modeling(MDPI, 2021) Castillejo Cuberos, Armando; Cardemil Iglesias, José Miguel; Escobar Moragas, RodrigoSolar eclipses are astronomic phenomena in which the Earth’s moon transits between the planet and the Sun, projecting a shadow onto the planet’s surface. As solar power installed capacity increases, detailed studies of this region-wide phenomenon’s effect in irradiance is of interest; how-ever, the literature mainly reports its effects on localized scales. A measurement campaign spanning over 1400 km was pursued for the 2 July 2019 total solar eclipse in Chile, to register the event and establish a modeling framework to assess solar eclipse effects in irradiance over wide regional scales. This work describes the event and presents an estimation framework to decompose atmospheric and eclipse effects on irradiance. An analytical model was applied to study irradiance attenuation throughout the Chilean mainland territory, using satellite-derived and astronomical data as inputs compared to ground measurements in eight stations. Results showed good agreement between model and observations, with Mean Bias Errors of −0.008 to 0.98 W/m2 for Global Horizontal Irradiance and −0.004 to −4.664 W/m2 for Direct Normal Irradiance, with Normalized Root Mean Squared Errors of 0.7–5.8% and 1.4–12.2%, respectively. Energy losses due to obscuration corre-sponded between 20–40% for Global Horizontal Irradiance and 25–50% for Direct Normal Irradi-ance over Chilean territory.
- ItemAssessing 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 AlfonsoThis 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.
- ItemAssessing the performance of novel molten salt mixtures on CSP applications(2024) Starke, Allan R.; Cardemil Iglesias, José Miguel; Bonini, Vinicius R.B.; Escobar Moragas, Rodrigo; Castro Quijada, Matías Daniel; Videla Leiva, Álvaro RodrigoThe use of molten salt mixtures as a storage medium in Concentrating Solar Power (CSP) plants has been shown to have a significant impact on increasing the reliability of CSP plants and reducing the levelized cost of energy. In this context, the present work presents the implementation of a detailed simulation procedure that contemplates different design considerations for the Rankine cycle to maximize its efficiency according to the temperature constraints established by utilizing different molten salt mixtures. To achieve this, three commercial CSP plant configurations were considered: an indirect coupling using parabolic trough collectors (PTC) with thermal oil as field heat transfer fluid (HTF) and molten salts as the storage medium, a direct coupling of PTC using molten salt as HTF and storage medium, and a central receiver plant (solar tower). The analysis considers the integration strategy between the solar system and the thermal storage, where all of those configurations considered the integration of the two-tank (hot/cold) approach. The analysis enables the development of an accurate estimation of the economic performance of changing the HTF in CSP plants, as well as the assessment of the parasitic consumption due to freezing protection systems, the effect of increasing the current field temperature, and the effect on the plant’s capacity factor. The results show that the improvement in conversion efficiencies associated with salt mixtures operating at higher temperatures induces a higher electricity generation; however, such improvement is not compensated by the material change costs within the specified considerations.
- ItemAssessment of time resolution impact on the modeling of a hybrid CSP-PV plant(2020) Zurita Villamizar, Adriana; Mata Torres, Carlos Enrique; Cardemil Iglesias, José Miguel; Escobar Moragas, Rodrigo
- ItemCompatibility assessment of thermal energy storage integration into industrial heat supply and recovery systems(2024) Wolde Ponce, Ian; Cardemil Iglesias, José Miguel; Escobar Moragas, RodrigoThermal energy storage (TES) systems can be used for recovering industrial waste heat and increasing energy efficiency, especially when coupled to batch thermal processes. Stratified water thermal storage tanks are the preferred technology for low-temperature applications, while molten salts are commonly used in medium and high-temperature applications with large storage capacities. No clear consensus exists on the appropriate TES technology for different industrial demands characteristics and their respective heat supply systems for medium and high-temperature applications. The present study analyzes several industrial sectors and their thermal processes, analyzing their temperature ranges, heat demands, and available TES technologies, which are classified by their operational conditions. The study presents two novel indicators for a preliminar compatibility assessment between TES and industrial sectors: a temperature compatibility indicator and exergy efficiency for TES and thermal processes. The results show that low and medium-temperature applications such as food, chemical, or textile industries exhibit high compatibilities with water (over 64%), high-temperature PCM (over 61%), and solid-state TES (100%), whereas molten salts and chemical looping demonstrate lower compatibility (below 24%). The exergy analysis for industrial cases shows that a lower temperature operating range for a TES induces low exergy efficiency. Regarding this scenario, high-temperature cPCM reaches efficiencies of over 44% for mid and high-temperature processes. Conversely, solid-state TES emerges as the most viable option for integration in high-temperature industries, exhibiting an efficiency of 62% with minimal exergy losses. The indicators defined in this study can be used for an early evaluation of TES integration in industrial applications, thus promoting emerging technologies selection through a quantitative comparison of the compatibility metrics.
- ItemEnhancing the estimation of direct normal irradiance for six climate zones through machine learning models(2024) Rodríguez, Eduardo; López Droguett, Enrique; Cardemil Iglesias, José Miguel; Starke, Allan R.; Cornejo-Ponce, LorenaThe evaluation of solar radiation is essential for large-scale solar energy systems, as assessing economic feasibility early on depends on accurate solar radiation data. Accurate sensors are needed to characterize the solar resource. Due to a scarcity of solar radiation data, numerical models are commonly used to estimate solar radiation components using meteorological variables that are simple or cheap to measure. In recent years, the use of machine learning (ML) algorithms has gained significant popularity in the estimation of solar radiation components. In this study it is proposed a post-processing approach using the separation model outcomes as input variables to estimate the diffuse fraction. Three ML models are employed (XGBoost, Random Forest, and Multilayer Perceptron) to boost the accuracy in terms of three statistical indicators: nRMSE, nMBE, and . The employed technique takes a distinctive approach by using reference stations to train the machine learning models and, afterward, make the assessment at the site under study. The results show an improvement in terms of precision of individual separation model outcomes. Thus, the proposed methodology may serve as a reliable approach for estimating solar radiation components in cases where historical data for a specific place of interest is not accessible.