Parametric performance optimization of three sides roughened solar air heater

Mohanty, Chinmaya P.; Kumar, Ashwini; Singh, Manas Ranjan; Prasad, B.N.; Dwivedi, Gaurav; Verma, Puneet

doi:10.1080/15567036.2020.1752855

Cited by 29 publications

(12 citation statements)

References 61 publications

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“…Motivated by the PSO's flexibility and adaptability to any difficult problem of optimization, researchers have proposed many different variations of PSO to deal with SAH optimization. In this situation, the authors in [194] proposed a parametric three-sided roughened SAH multiobjective particle swarm optimization (MOPSO) algorithm. Their affirmatively validated optimal results indicate a 3.39% error.…”

Section: Particle Swarm Optimization For Solar Airmentioning

confidence: 99%

“…Furthermore, the study can be extended to perform thermal performance optimization for solar air heaters. The following references show specific published papers on the use of metaheuristic algorithms in SAH optimization: [202] in 2010, [14] in 2012, [210] in 2012, [203] in 2012, [24] in 2015, [200] in 2016, [23] in 2017, [84,204] in 2019, and [159,194] in 2020. Hence, it can be observed that the total number of publications on this topic has increased slightly since 2010 (even though information for 2020 is not yet complete at the moment).…”

Section: Conclusion and Future Outlookmentioning

confidence: 99%

“…The aim of this article is to undertake a detailed survey of six promising metaheuristic algorithms and their application in SAH optimization. Studies [14,23,24,84,159,194,200,[202][203][204]210]from Table 4 below show that metaheuristic algorithms are particularly effective and powerful tools for finding optimal performance efficiencies of SAHs. Moreover, Table 5 illustrates the main advantages and disadvantages of these six metaheuristic algorithms.…”

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confidence: 99%

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Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects

Niyonteze

Zou

Asemota

et al. 2021

International Journal of Photoenergy

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A transition to solar energy systems is considered one of the most important alternatives to conventional fossil fuels. Until recently, solar air heaters (SAHs) were among the other solar energy systems that have been widely used in various households and industrial applications. However, the recent literature reveals that efficiencies of SAHs are still low. Some metaheuristic algorithms have been used to enhance the efficiencies of these SAH systems. In the paper, we do not only discuss the techniques used to enhance the performance of SAHs, but we also reviewed a majority of published papers on the applications of SAH optimization. The metaheuristic algorithms include simulated annealing (SA), particle swarm optimization (PSO), genetic algorithm (GA), artificial bee colony (ABC), teaching-learning-based optimization (TLBO), and elitist teaching-learning-based optimization (ETLBO). For this research, it should be noted that this study is mostly based on the literature published in the last ten years in good energy top journals. Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. Based on the past literature and on the outcomes of this paper, ETLBO is unquestionably more competitive than ABC, GA, PSO, SA, and TLBO for the optimization of SAHs for the same considered problem. Finally, based on the covered six state-of-the-art metaheuristic techniques, some perspectives and recommendations for the future outlook of SAH optimization are proposed. This paper is the first-ever attempt to present the current developments to a large audience on the applications of metaheuristic methods in SAH optimization. Thus, researchers can use this paper for further research and for the advancement of the proposed and other recommended algorithms to generate the best performance for the various SAHs.

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Section: Particle Swarm Optimization For Solar Airmentioning

confidence: 99%

Section: Conclusion and Future Outlookmentioning

confidence: 99%

mentioning

confidence: 99%

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Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects

Niyonteze

Zou

Asemota

et al. 2021

International Journal of Photoenergy

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“…The photovoltaic system has the ability to transform solar energy into electricity. The important aspect here is the need to store the electrical energy obtained from the sun in order to feed the system during non-sunny hours [5,6]. This objective could be achieved using a battery bank or connecting the PV systems to the utility system [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Designing of a Hybrid Photovoltaic Structure for an Energy-Efficient Street Lightning System Using PVsyst Software

Tamoor

Bhatti

Farhan

et al. 2021

The 1st International Conference on Energy, Power and Environment

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With the depletion of traditional fossil fuels, their disastrous impact on the environment and rising costs, renewable energy sources such as photovoltaic (PV) energy are rapidly emerging as sustainable and clean sources of power generation. The performance of photovoltaic systems is based on different factors such as the type of photovoltaic modules, irradiation potential and geographic location. In this research, PVsyst simulation software is used to design and simulate a hybrid photovoltaic system used to operate energy-efficient street lightning system. The simulation is performed to analyze the monthly/annual energy generated (kWh) by the hybrid system and specific power production (kWh/KWp). Additionally, various PV system losses are also investigated. The hybrid PV system has 4 parallel strings, and each string has 13 series-connected (mono crystalline 400 W Canadian Solar) PV modules. The energy storage system consists of 16 Narada (AcmeG 12 V 200) batteries with a nominal capacity of 1600 Ah. The simulation results show that the total annual energy production and specific energy production, were calculated to be 26.68 MWh/year and 1283 kWh/kWp/year, respectively. Simulation results also show the maximum energy injected into the utility grid in the month of June (1.814 MWh) and the minimum energy injected into the utility grid in the month of January (0.848 MWh). The battery cycle state of wear is 84.8%, and the static state of wear is 91.7%. Performance ratio (PR) analysis shows that the highest performance ratio of the hybrid system was 68.2% in December, the lowest performance ratio was 62.7% in May and the annual average performance ratio of a hybrid PV system is 65.57%. After identifying the major source of energy losses, the detailed losses for the whole year were computed and shown by the loss diagrams. To evaluate the cost effectiveness of the proposed system, a simple payback period calculation was performed.

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“…In the search domain, particles move their position and the velocity updated according to its own flying experience toward its pbest and gbest locations [31]. The application of PSO is found out in many engineering optimization problems due to its certain characteristic, such as fast convergence capability, less number of controlled parameters used for optimization and convergence guaranteed [32][33][34][35]. Ali et al optimized EDM process by machining AISI2312 hot worked steel alloy using neural network and PSO [43].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy based multi-response optimization: a case study on EDM machining process

Sahu

Shrivastava

2021

SN Appl. Sci.

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The current study challenges the multi-objective optimization of electric discharge machining (EDM) parameters. EDM is used for creating profiles by machining of workpiece that are difficult to machine by conventional method. In the current work four responses such as material removal rate (production rate), tool wear rate, surface roughness (quality) and circularity (profile) are collectively investigated with varying controlling parameters. The human decision for best combination of controlling parameters for highest performance has uncertainties, which results in inferior solution. The multiple responses along with uncertainties and impreciseness can be addressed by combining a neuro-fuzzy system with particle swarm optimization (PSO). To illustrate the superiority of the proposed approach a set of experiment have been conducted in EDM process using AISI D2 tool steel as workpiece and brass tool. The experimental plan was made according to the Box-Behnken response surface methodology design with four process parameters namely discharge current, pulse-on-time, duty factor, and flushing pressure. The four response parameters such as material removal rate, tool wear rate, surface roughness, and circularity of machined components were optimized simultaneously. One unique Multi-response Performance Characteristic Index was obtained by combining the four responses using the proposed neuro-fuzzy technique. A regression model was developed on single response and optimized by PSO to obtain the optimal parameter setting. An experiment was conducted on optimal parameter to test the optimum performance. It is observed that the EDM responses were affected significantly by discharge current and pulse-on-time. The increase in pulse-on-time leads to larger surface cracks and more micro-pores on the machined surface. Article Highlights RSM was proven to be an effective statistical tool for reducing the experimental runs, and also establishes the relation between multiple inputs and single output. The neuro-fuzzy system combined with PSO results a suitable model to convert multiple response into an equivalent single response. The presented approach can be a practical method for situations where multiple conflicting objectives are needed to be optimized at the same time.

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Parametric performance optimization of three sides roughened solar air heater

Cited by 29 publications

References 61 publications

Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects

Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects

Designing of a Hybrid Photovoltaic Structure for an Energy-Efficient Street Lightning System Using PVsyst Software

Fuzzy based multi-response optimization: a case study on EDM machining process

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