Author
Soteris A. Kalogirou
Other affiliations: Higher Technical Institute of Cyprus
Bio: Soteris A. Kalogirou is an academic researcher from Cyprus University of Technology. The author has contributed to research in topics: Solar energy & Renewable energy. The author has an hindex of 72, co-authored 229 publications receiving 22731 citations. Previous affiliations of Soteris A. Kalogirou include Higher Technical Institute of Cyprus.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a detailed thermal model of a parabolic trough collector is presented, which takes into account all modes of heat transfer, including convection into the receiver pipe, in the annulus between the receiver and the glass cover, and from the receiver to ambient air; conduction through the metal receiver pipe and glass cover walls; and radiation from the metal receiving surface to the glass surface and the sky respectively.
253 citations
TL;DR: In this paper, the results of the determination of the overall heat transfer coefficient (U-value) with the use of IR thermography for building envelopes are presented, and the obtained U-values are validated by means of measurements performed using a thermohygrometer for two seasons (summer and winter).
251 citations
TL;DR: The near optimum design for membership functions and control rules were found simultaneously by genetic algorithms (GAs) which are search algorithms based on the mechanism of natural selection and genetics which are easy to implement and efficient for multivariable optimization problems such as in fuzzy controller design.
240 citations
TL;DR: In this paper, an artificial neural network is trained using the results of a small number of TRNSYS simulations, to learn the correlation of collector area and storage-tank size on the auxiliary energy required by the system from which the life-cycle savings can be estimated.
222 citations
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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 paper, a review has been done on scope of CO2 mitigation through solar cooker, water heater, dryer, biofuel, improved cookstove and by hydrogen, which provides an excellent opportunity for mitigation of greenhouse gas emission and reducing global warming through substituting conventional energy sources.
Abstract: Renewable technologies are considered as clean sources of energy and optimal use of these resources minimize environmental impacts, produce minimum secondary wastes and are sustainable based on current and future economic and social societal needs. Sun is the source of all energies. The primary forms of solar energy are heat and light. Sunlight and heat are transformed and absorbed by the environment in a multitude of ways. Some of these transformations result in renewable energy flows such as biomass and wind energy. Renewable energy technologies provide an excellent opportunity for mitigation of greenhouse gas emission and reducing global warming through substituting conventional energy sources. In this article a review has been done on scope of CO2 mitigation through solar cooker, water heater, dryer, biofuel, improved cookstoves and by hydrogen.
2,584 citations
09 Mar 2012
TL;DR: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems as mentioned in this paper, and they have been widely used in computer vision applications.
Abstract: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.
2,069 citations
TL;DR: In this paper, the authors present a review of recent developed models for predicting building energy consumption, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods, and further prospects are proposed for additional research reference.
Abstract: The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, the operation of sub-level components like lighting and HVAC systems, occupancy and their behavior. This complex situation makes it very difficult to accurately implement the prediction of building energy consumption. This paper reviews recently developed models for solving this problem, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods. Previous research work concerning these models and relevant applications are introduced. Based on the analysis of previous work, further prospects are proposed for additional research reference.
1,509 citations
TL;DR: In this paper, a review of the different computer tools that can be used to analyse the integration of renewable energy is presented, and the results in this paper provide the information necessary to identify a suitable energy tool for analysing the integration into various energy-systems under different objectives.
1,480 citations