Papers published on a yearly basis
Papers
More filters
••
TL;DR: A survey of the various types of solar thermal collectors and applications is presented in this paper, where an analysis of the environmental problems related to the use of conventional sources of energy is presented and the benefits offered by renewable energy systems are outlined.
2,620 citations
••
TL;DR: In this article, the authors present various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use.
Abstract: Artificial neural networks are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and, once trained, can perform prediction and generalisation at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimisation, signal processing and social/psychological sciences. They are particularly useful in system modelling such as in implementing complex mappings and system identification. This paper presents various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order. Artificial neural networks have been used by the author in the field of solar energy; for modelling and design of a solar steam generating plant, for the estimation of a parabolic trough collector intercept factor and local concentration ratio and for the modelling and performance prediction of solar water heating systems. They have also been used for the estimation of heating loads of buildings, for the prediction of air flow in a naturally ventilated test room and for the prediction of the energy consumption of a passive solar building. In all those models a multiple hidden layer architecture has been used. Errors reported in these models are well within acceptable limits, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use. The work of other researchers in the field of renewable energy and other energy systems is also reported. This includes the use of artificial neural networks in solar radiation and wind speed prediction, photovoltaic systems, building services systems and load forecasting and prediction.
1,016 citations
••
TL;DR: In this article, the authors present a review of various systems that use renewable energy sources for desalination, including solar collectors, photovoltaics, solar ponds and geothermal energy.
949 citations
••
TL;DR: In this paper, the authors present various applications of neural networks in energy problems in a thematic rather than a chronological or any other way, including modeling and design of a solar steam generating plant, estimation of a parabolic-trough collector's intercept factor and local concentration ratio, and performance prediction of solar water-heating systems.
833 citations
••
TL;DR: In the literature, several calculation models are found for ground heat exchangers as discussed by the authors, which can accommodate for any type of grid geometry that may give greater detail of the temperature variation around the pipes and in the ground.
627 citations
Authors
Showing all 134 results
Name | H-index | Papers | Citations |
---|---|---|---|
Soteris A. Kalogirou | 72 | 229 | 22731 |
Isabel Sá-Correia | 59 | 268 | 11466 |
Eduardo Alves | 52 | 818 | 12607 |
Pedro Fernandes | 43 | 289 | 7122 |
João Borges de Sousa | 38 | 333 | 5014 |
Robert S. H. Istepanian | 38 | 180 | 5911 |
Kyriacos Kalli | 36 | 273 | 6618 |
Arlindo L. Oliveira | 34 | 154 | 6991 |
Georgios A. Florides | 26 | 77 | 3188 |
Ermelinda M. S. Maçôas | 25 | 62 | 1825 |
Luis F. Vieira Ferreira | 24 | 89 | 1899 |
Mohamed Bassyouni | 23 | 85 | 1312 |
George N. Philippou | 22 | 39 | 1695 |
Manuel Duarte Pinheiro | 21 | 59 | 1282 |
Fernando Manuel Lourenço Martins | 21 | 138 | 1770 |