A Differentiable Model for Optimizing Hybridization of Industrial Process Heat Systems with Concentrating Solar Thermal Power

Stuber, Matthew D.

doi:10.3390/pr6070076

Cited by 8 publications

(3 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Branch-and-bound methods [24,43,44] are deterministic global optimization algorithms that guarantee the location of a global minimum for a nonlinear program (NLP) to within a specified tolerance. These methods proceed by evaluating upper and lower bounds of the objective function, which are refined progressively as the domain is subdivided.…”

Section: Branch-and-bound Optimization Using Convex Relaxationsmentioning

confidence: 99%

Convergence of Subtangent-Based Relaxations of Nonlinear Programs

2019

View full text Add to dashboard Cite

Convex relaxations of functions are used to provide bounding information to deterministic global optimization methods for nonconvex systems. To be useful, these relaxations must converge rapidly to the original system as the considered domain shrinks. This article examines the convergence rates of convex outer approximations for functions and nonlinear programs (NLPs), constructed using affine subtangents of an existing convex relaxation scheme. It is shown that these outer approximations inherit rapid second-order pointwise convergence from the original scheme under certain assumptions. To support this analysis, the notion of second-order pointwise convergence is extended to constrained optimization problems, and general sufficient conditions for guaranteeing this convergence are developed. The implications are discussed. An implementation of subtangent-based relaxations of NLPs in Julia is discussed and is applied to example problems for illustration.

show abstract

Section: Branch-and-bound Optimization Using Convex Relaxationsmentioning

confidence: 99%

Convergence of Subtangent-Based Relaxations of Nonlinear Programs

2019

View full text Add to dashboard Cite

show abstract

“…They mentioned the time series forecasting for PV power plants is only reliable for one hour ahead prediction. Planning and procedures must adjust according to these changes in the forecast LSS PV condition [11]. Several writers have explored the forecasting of PV output power based on the classifications of meteorological factors [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting

Kassim,

Santhiran,

Alkahtani

et al. 2023

Sustainability

View full text Add to dashboard Cite

The installation of large-scale solar (LSS) photovoltaic (PV) power plants continues to rise globally as well as in Malaysia. The data provided by LSS PV consist of five weather stations with seven parameters, a 22-unit inverter, and 1-unit PQM Meter Grid as a big dataset. These big data are rapidly changing every minute, they lack data quality when missing data, and need to be analyzed for a longer duration to leverage their benefits to prevent misleading information. This paper proposed the forecasting power LSS PV using decision tree regression from three types of input data. Case 1 used all 35 parameters from five weather stations. For Case 2, only seven parameters were used by calculating the mean of five weather stations. While Case 3 was chosen from an index correlation of more than 0.8. The analysis of the historical data was carried out from June 2019 until December 2020. Moreover, the mean absolute error (MAE) was also calculated. A reliability test using the Pearson correlation coefficient (r) and coefficient of determination (R2) was done upon comparing with actual historical data. As a result, Case 2 was proposed to be the best input dataset for the forecasting algorithm.

show abstract

“…The coupling of concentrated solar thermal power to industrial processes (hybridization) is a technology under development with a very high potential to reduce greenhouse gas emissions [1], but concentrated solar power can also be used for the production of fuels. The different technologies involving high temperature concentrated solar power aimed at the conversion of solar energy to chemical fuels are currently being thoroughly investigated.…”

Section: Introductionmentioning

confidence: 99%

Multi-Tubular Reactor for Hydrogen Production: CFD Thermal Design and Experimental Testing

Tapia

González-Pardo²,

Iranzo

et al. 2019

Processes

View full text Add to dashboard Cite

This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for the solar reactor design is described, as well as the experimental tests carried out during the testing campaign and characterization of the reactor. The CFD model developed for the thermal design of the solar reactor has been validated against the experimental measurements, with a temperature error ranging from 1% to around 10% depending on the location within the reactor. The thermal balance in the reactor (cavity and tubes) has been also solved by the CFD model, showing a 7.9% thermal efficiency of the reactor. CFD results also show the percentage of reacting media inside the tubes which achieve the required temperature for the endothermic reaction process, with 90% of the ferrite pellets inside the tubes above the required temperature of 900 °C. The multi-tubular solar reactor designed with aid of CFD modelling and simulations has been built and operated successfully.

show abstract

A Differentiable Model for Optimizing Hybridization of Industrial Process Heat Systems with Concentrating Solar Thermal Power

Cited by 8 publications

References 41 publications

Convergence of Subtangent-Based Relaxations of Nonlinear Programs

Convergence of Subtangent-Based Relaxations of Nonlinear Programs

An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting

Multi-Tubular Reactor for Hydrogen Production: CFD Thermal Design and Experimental Testing

Contact Info

Product

Resources

About