Inverse prediction and optimization analysis of a solar pond powering a thermoelectric generator. (15th July 2018)
- Record Type:
- Journal Article
- Title:
- Inverse prediction and optimization analysis of a solar pond powering a thermoelectric generator. (15th July 2018)
- Main Title:
- Inverse prediction and optimization analysis of a solar pond powering a thermoelectric generator
- Authors:
- Kumar, Abhishek
Singh, Kuljeet
Verma, Sunirmit
Das, Ranjan - Abstract:
- Highlights: Inverse optimization study of solar pond assisted thermoelectric system is done. Optimization study reduces pond's height by 18.11% as compared to literature data. Even with reduced height, better thermal performance of solar pond is achieved. Genetic algorithm is found to yield better performance for solar pond selection. Sensitivity analysis revealed important features concerning the solar pond. Abstract: A given temperature difference across the upper and the lower convective zone of a solar pond is commonly sought in thermoelectric power generation. Based on this consideration, this work is aimed at predicting the lengths of various zones of a solar pond to ensure a minimum temperature potential throughout the year between its upper and lower convective zones. For predicting the critical lengths of various zones of the solar pond, at first, the heat energy conservation-based model available in the literature is modified by accounting the effect of salinity and temperature on various thermal parameters. The model is satisfactorily-validated with similar model and experimental data reported in the literature. Thereafter, considering the requirement of a thermoelectric power generator ( TEG ), an inverse problem is solved with the aid of a genetic algorithm-based optimization method to predict feasible lengths of various zones satisfying a minimum temperature potential across TEG considering suitable thermal resistances. The present results reveal improved pondHighlights: Inverse optimization study of solar pond assisted thermoelectric system is done. Optimization study reduces pond's height by 18.11% as compared to literature data. Even with reduced height, better thermal performance of solar pond is achieved. Genetic algorithm is found to yield better performance for solar pond selection. Sensitivity analysis revealed important features concerning the solar pond. Abstract: A given temperature difference across the upper and the lower convective zone of a solar pond is commonly sought in thermoelectric power generation. Based on this consideration, this work is aimed at predicting the lengths of various zones of a solar pond to ensure a minimum temperature potential throughout the year between its upper and lower convective zones. For predicting the critical lengths of various zones of the solar pond, at first, the heat energy conservation-based model available in the literature is modified by accounting the effect of salinity and temperature on various thermal parameters. The model is satisfactorily-validated with similar model and experimental data reported in the literature. Thereafter, considering the requirement of a thermoelectric power generator ( TEG ), an inverse problem is solved with the aid of a genetic algorithm-based optimization method to predict feasible lengths of various zones satisfying a minimum temperature potential across TEG considering suitable thermal resistances. The present results reveal improved pond dimensions achieving a better temperature profile at a lower total height than that available in the literature. Further, case studies of diverse meteorological conditions of India are carried out and it becomes apparent that, around the year, multiple combinations of convective and non-convective regions of the solar pond can ensure the required minimum (or more) temperature difference across relevant zones of the solar pond. Finally, the present study also reveals that the temperature of the upper convective zone is largely governed by the thickness of this zone, whereas, the thickness of the non-convective zone is largely responsible for the temperature within the storage zone. The present study provides a novel inverse methodology to predict and optimize the suitable dimensions of various regions of a salt-gradient solar pond to ensure a minimum temperature potential across the year for thermoelectric power generation. … (more)
- Is Part Of:
- Solar energy. Volume 169(2018)
- Journal:
- Solar energy
- Issue:
- Volume 169(2018)
- Issue Display:
- Volume 169, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 169
- Issue:
- 2018
- Issue Sort Value:
- 2018-0169-2018-0000
- Page Start:
- 658
- Page End:
- 672
- Publication Date:
- 2018-07-15
- Subjects:
- Solar pond -- Inverse optimization -- Thermoelectric generation -- Sensitivity analysis
Solar energy -- Periodicals
Solar engines -- Periodicals
621.47 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0038092X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.solener.2018.05.035 ↗
- Languages:
- English
- ISSNs:
- 0038-092X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8327.200000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21515.xml