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Publikācija: Supporting Energy Efficiency Decisions with IT: Initial Experiences from the EnRiMa Project

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Nosaukums oriģinālvalodā Supporting Energy Efficiency Decisions with IT: Initial Experiences from the EnRiMa Project
Rakstu krājuma / Monogrāfijas nosaukums The Practice of Enterprise Modeling: Lecture Notes in Business Information Processing. Vol.158
Pētniecības nozare 2. Inženierzinātnes un tehnoloģijas
Pētniecības apakšnozare 2.2. Elektrotehnika, elektronika, informācijas un komunikāciju tehnoloģijas
Autori Jānis Stirna
Martin Henkel
Markus Groissbock
Michael Stadler
Atslēgas vārdi Sustainability Green IT Energy Efficiency Decision Support System
Anotācija IT solutions can aid decision makers in making informed decisions that lower the energy consumption in buildings. However, in order to design and implement an IT solution there are a number of issues that need to be resolved, for example, adequately handling sometimes contradicting goals of the decision makers and integrating the Decision Support System with the existing building IT infrastructure in the form of building management systems. In this paper we report on our initial experiences from implementing a decision support system for the management of energy consumption in public buildings. The experiences are based on our work with the EnRiMa project that aims to develop a state-of art decision support system for lowering the energy consumption and CO2 emissions of public buildings. We divide our experiences into two areas, namely, business concerns and software architectural, and provide our initial solutions and lessons learned with respect to these areas. Furthermore, we discuss a number of challenges for future work in the area of IT support for energy efficiency.
DOI: 10.1007/978-3-642-40823-6_25
Hipersaite: http://link.springer.com/chapter/10.1007/978-3-642-40823-6_25 
Atsauce Stirna, J., Henkel, M., Groissbock, M., Stadler, M. Supporting Energy Efficiency Decisions with IT: Initial Experiences from the EnRiMa Project. No: The Practice of Enterprise Modeling: Lecture Notes in Business Information Processing. Vol.158. Berlin: Springer Berlin Heidelberg, 2013. 315.-326.lpp. ISBN 9783642408229.
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