D
D. Kolokotsa
Researcher at Technical University of Crete
Publications - 21
Citations - 2310
D. Kolokotsa is an academic researcher from Technical University of Crete. The author has contributed to research in topics: Efficient energy use & Building management system. The author has an hindex of 12, co-authored 20 publications receiving 1954 citations. Previous affiliations of D. Kolokotsa include Technological Educational Institute of Crete.
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On the impact of urban heat island and global warming on the power demand and electricity consumption of buildings—A review
Mattheos Santamouris,Mattheos Santamouris,Constantinos Cartalis,Afroditi Synnefa,D. Kolokotsa +4 more
TL;DR: In this article, the impact of ambient temperature on the peak electricity demand was analyzed and it was shown that higher temperatures have a serious impact on the electricity consumption of the building sector increasing considerably the peak and the total electricity demand.
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A roadmap towards intelligent net zero- and positive-energy buildings
TL;DR: A review on the technological developments in each of the essential ingredients that may support the future integration of successful NZEB/PEB, i.e. accurate simulation models, sensors and actuators and last but not least the building optimization and control are presented.
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Towards a multi-objective optimization approach for improving energy efficiency in buildings
TL;DR: In this article, the feasibility of the application of multi-objective optimization techniques to the problem of the improvement of the energy efficiency in buildings, so that the maximum possible number of alternative solutions and energy efficiency measures may be considered.
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A multi-objective decision model for the improvement of energy efficiency in buildings
Christina Diakaki,Evangelos Grigoroudis,Nikos Kabelis,D. Kolokotsa,Kostas Kalaitzakis,George S. Stavrakakis +5 more
TL;DR: In this paper, the authors propose a multi-objective decision model, which allows the examination of a potentially infinite number of alternative measures, evaluated according to a set of criteria, which include the annual primary energy consumption of the building, the annual carbon dioxide emissions and the initial investment cost.
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Predictive control techniques for energy and indoor environmental quality management in buildings
TL;DR: A model-based predictive controller, combined with a Building Energy Management System (BEMS), that predicts the indoor environmental conditions of a specific building and selects the most appropriate actions so as to reach the set points and contribute to the indoors environmental quality by minimizing energy costs.