Optimizing the thermal performance of solar energy devices using meta-heuristic algorithms: A critical review

Afzal, Asif; Buradi, Abdulrajak; Jilte, Ravindra; Shaik, Saboor; Kaladgi, Abdul Razak; Arıcı, Müslüm; Lee, Chew Tin; Nižetić, Sandro

doi:10.1016/j.rser.2022.112903

Cited by 52 publications

(9 citation statements)

References 93 publications

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“…Additionally, depending on the need for an exact solution and the level of satisfaction needed, such hybrid approaches can significantly reduce the computational cost of finding solutions (Twaha and Ramli, 2018). Hybrid algorithms incorporating emerging AI techniques demonstrate robust calculations, improved convergence, and enhanced accuracy (Afzal et al, 2023).…”

Section: Hybrid Methodsmentioning

confidence: 99%

A review of optimization modeling and solution methods in renewable energy systems

Yu,

You,

Zhou

2023

Front. Eng. Manag.

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The advancement of renewable energy (RE) represents a pivotal strategy in mitigating climate change and advancing energy transition efforts. A current of research pertains to strategies for fostering RE growth. Among the frequently proposed approaches, employing optimization models to facilitate decision-making stands out prominently. Drawing from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems (RES) from 1990 to 2023 within the Web of Science database, this study reviews the decision-making optimization problems, models, and solution methods thereof throughout the renewable energy development and utilization chain (REDUC) process. This review also endeavors to structure and assess the contextual landscape of RES optimization modeling research. As evidenced by the literature review, optimization modeling effectively resolves decision-making predicaments spanning RE investment, construction, operation and maintenance, and scheduling. Predominantly, a hybrid model that combines prediction, optimization, simulation, and assessment methodologies emerges as the favored approach for optimizing RES-related decisions. The primary framework prevalent in extant research solutions entails the dissection and linearization of established models, in combination with hybrid analytical strategies and artificial intelligence algorithms. Noteworthy advancements within modeling encompass domains such as uncertainty, multienergy carrier considerations, and the refinement of spatiotemporal resolution. In the realm of algorithmic solutions for RES optimization models, a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven optimization. Furthermore, this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps, expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.

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Section: Hybrid Methodsmentioning

confidence: 99%

A review of optimization modeling and solution methods in renewable energy systems

Yu,

You,

Zhou

2023

Front. Eng. Manag.

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“…Intelligent optimization algorithms provide another way to improve search efficiency and accuracy by learning or simulating various optimization behaviors and phenomena in the natural world, which include evolutionary and population algorithms [15][16][17][18], natureinspired algorithms [19], metaheuristic algorithms [20], learning-based algorithms [21], etc. A large number of applications [22][23][24] show that intelligent methods have the abilities to achieve excellent results, especially for complex optimization, which is difficult for traditional optimization algorithms.…”

Section: Solution Of Optimizationmentioning

confidence: 99%

Progress of Optimization in Manufacturing Industries and Energy System

Zhang,

Yang,

You

2024

Processes

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“…The results of the research showed that when there is only limited data, the SVR model is the preferred model. Optimizing models using meta-heuristic algorithms has been widely used in recent years (Afzal et al 2023;Wu et al 2023). One of the precise and valuable optimizations is the concept theory of re ies (FFA), which is based on the ashing manner of re ies and was presented by Yang (2010).…”

Section: Introductionmentioning

confidence: 99%

Can hybrid models predict actual evapotranspiration instead of weighting lysimeters?

Sharafi

Rezaverdinejad

Behmanesh

2023

Preprint

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Actual daily evapotranspiration (ET) can be considered as one of the most important meteorological parameters. One of the main ways to measure ET is using lysimeters, which are expensive tools, and the data obtained from them are not available in most parts of the world. Therefore, the purpose of this research is to provide an intelligent model that can predict ET using data obtained from cheap and available tools. To do this, data from two NE and SE lysimeters located in Potter County, Texas between 1996-1999 were used as input for SVR and SVR-FFA models in 13 scenarios. The results of this study showed that the SVR-FFA model with an error value of 1.22 mm/day for 1996, 1.14 mm/day for 1997, 1.56 mm/day for 1998, and 1.54 mm/day for 1999 has the highest accuracy for all combinations. Among the standalone SVR models, the SVR-13 model has performed better than other SVR combinations for all years with a Willmott's index of agreement above 0.87. The comparison between the inputs used for the models showed that the Rn and PAR parameters had the greatest impact on the accuracy of the SVR and SVR-FFA models, so they increased the accuracy of the models in every four years. One of the limitations of this study is the lack of access to some parameters such as minimum and maximum temperature in the study area. Therefore, it is suggested to measure these parameters and consider them as other inputs to measure the performance of the models.

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Optimizing the thermal performance of solar energy devices using meta-heuristic algorithms: A critical review

Cited by 52 publications

References 93 publications

A review of optimization modeling and solution methods in renewable energy systems

A review of optimization modeling and solution methods in renewable energy systems

Progress of Optimization in Manufacturing Industries and Energy System

Can hybrid models predict actual evapotranspiration instead of weighting lysimeters?

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