Energy conservation potential, HVAC installations and operational issues in Hellenic airports
ABSTRACT This paper presents an overview of the results from a recently completed study on the assessment of the characteristics, current energy consumption and the potential for energy conservation in 29 Hellenic airports. The average annual total energy consumption at the airport terminals is 234 kWh/m2. A more detailed investigation for three representative airports, at different climatic zones, was also performed. Data was collected through energy audits of the three terminal buildings, thermal infrared (IR) inspections of the building envelopes and HVAC installations, an assessment of indoor environmental quality (IEQ) through long term monitoring and spot measurements of indoor thermal and visual conditions, as well as personnel and passenger questionnaires. The collected information was used to perform a detailed analysis using thermal simulations for assessing specific measures to reduce energy use without compromising comfort, and to identify possible actions for improving IEQ. For the three airports, potential energy savings range at 15–35%, while improving and maintaining indoor environmental quality.
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ABSTRACT: Energy management systems provide an opportunity to collect vast amounts of building-related data. The data contain abundant knowledge about the interactions between a building’s energy consumption and the influencing factors. It is highly desirable that the hidden knowledge can be extracted from the data in order to help improve building energy performance. However, the data are rarely translated into useful knowledge due to their complexity and a lack of effective data analysis techniques. This paper first conducts a comprehensive review of the commonly used data analysis methods applied to building-related data. Both the strengths and weaknesses of each method are discussed. Then, the critical analysis of the previous solutions to three fundamental problems of building energy performance improvement that remain significant barriers is performed. Considering the limitations of those commonly used data analysis methods, data mining techniques are proposed as a primary tool to analyze building-related data. Moreover, a data analysis process and a data mining framework are proposed that enable building-related data to be analyzed more efficiently. The process refers to a series of sequential steps in analyzing data. The framework includes different data mining techniques and algorithms, from which a set of efficient data analysis methodologies can be developed. The applications of the process and framework to two sets of collected data demonstrate their applicability and abilities to extract useful knowledge. Particularly, four data analysis methodologies were developed to solve the three problems. For demonstration purposes, these methodologies were applied to the collected data. These methodologies are introduced in the published papers and are summarized in this paper. More extensive investigations will be performed in order to further evaluate the effectiveness of the framework.Building Simulation 06/2013; 6(2). DOI:10.1007/s12273-013-0117-8 · 0.63 Impact Factor
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ABSTRACT: Airport terminal buildings are used to be treated as stand-alone buildings for their energy performance. Previous studies in the literature fall short of recognizing functional and physical relations of terminal buildings with landside and airside airport operations. In order to avoid these shortcomings, this paper extends the terminal building energy performance analysis to a broader context and expands the analysis envelope to expose the true impact of a terminal building on energy consumption and the combined emissions that it is responsible for. In this respect, this study investigates whether a green terminal building in a new airport planned for the city of Istanbul with an annual 150 million passenger capacity may off-set the loss of CO2 sequestration potential from cutting at least 657000 trees for the airport construction or not. Additional CO2 emissions corresponding to the estimated longer approach and climb out flights due to the unfavorable site selection have also been considered. This article compares a business as usual type of terminal building with four green terminal building scenarios having different CO2 emission reduction potentials. The first-law and the second-law analysis of thermodynamics have shown that constructing a green terminal building complex may not offset its CO2 emissions responsibility unless a very intensive re-forestation activity is implemented and the site is properly re-selected. As a result, this study has exemplified the essential boundaries for energy consumption analysis envelope for an airport terminal building and its true emissions responsibility.Energy and Buildings 06/2014; 76:109–118. DOI:10.1016/j.enbuild.2014.02.049 · 2.47 Impact Factor
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ABSTRACT: The need to increase the diffusion of energy efficiency measures (EEMs) is of crucial importance to achieve a consistent reduction of energy consumption and green house gases (GHG) emissions. A clear comprehension of the characteristics of such EEMs could assist in gathering and capitalizing all the information needed by industrial firms in selecting and adopting technologies, as well as by policy-makers in designing appropriate policies for their diffusion. Therefore, in this study, starting from a literature review of the studies analyzing the attributes of EEMs, we aim at providing an innovative and comprehensive framework to characterize such measures, based on 17 attributes grouped according to six categories, such as: economic, energy, environmental, production-related, implementation-related and the possible interaction with other systems. We applied this scheme to an extensive range of EEMs in cross-cutting technologies, i.e. motors, compressed air, lighting and HVAC systems. The analysis provides a relevant contribution firstly to the structuring and the sharing of knowledge on EEMs and hence to the comprehension of the barriers currently hindering their adoption; secondly, it provides a structured basis for the analysis of the drivers that policy-makers should develop in order to promote industrial energy efficiency.Applied Energy 04/2014; 118:207-220. DOI:10.1016/j.apenergy.2013.12.042 · 5.26 Impact Factor