The paper deals with an optimization of parameters, which influence the energy and investment cost as well as the thermal comfort. The parameters considered in this study are: the insulation thickness of the building envelope, the supply-water temperature and the heat exchange area of the radiators. A combination of the building energy simulation software EnergyPlus 1 and the generic optimization program GenOpt 1 has been used for this purpose. The paper presents the application of a one-objective optimization algorithm solving the problems with two objectives, because the optimization algorithm is one-objective and the problem has two objectives, which are minimal total costs and

The article presents review of possibilities and necessities for a practical application of lifetime commissioning in building facilities. The implementation of lifelong commissioning of buildings implies energy efficiency, ensures a rational use of energy and thereby decreases CO 2 emissions. Therefore, first the term "commissioning" is explained in the article. Commissioning necessities, which are induced by different operational faults, the new laws driven by idea for decreasing CO 2 emission, and benefits, are explained, too. Besides USA's and European laws for the energy performance of buildings, the Norwegian state of the art in this area is also presented. The difference in terms and methods for fault detection and diagnosis are elaborated in the article. Finally, examples of different commissioning tools are briefly introduced and compared. In order to make building sustainable and encourage energy savings, potential commissioning users are suggested.

The aim of the study was to indentify driving variables that contributed to energy use in a low energy office building by integrating building energy management system (BEMS) and energy use data. To take a further step towards zero emission buildings, it is necessary to identify what contributes the most to building energy use. Further, the idea was to encourage a smart use of BEMS data for energy use analysis. Principal component regression and partial least squares regression were used for the data analysis. Databases of 76 and 41 variables respectively, which included occupancy level, control signals, and water and air temperatures, were used to explain heating, electricity, and fan energy use. Variable contributions to the principal components were used to simplify the model and to find the most important variables. In this way, energy use was defined indirectly by using available variables in BEMS. The approach was tested on a low energy office building. The results showed that important variables were different for different months in the case of heating energy use. The total electricity and fan electricity use could be defined with the same variables in different months. The total electricity use could be defined by using occupancy level and input fan signals. The suggested approach could be used by building operators to identify opportunities for decreasing energy use and for energy use estimation when data are lost due to data transmission issues or other problems. A relationship between building information and energy use was established.

This paper reviews the applicability and drawbacks of available European and international standards related to lifetime commissioning, by structuring them into Norwegian commissioning procedures. The work describes research on lifetime commissioning that proposes a generic framework on building performances. The generic framework describes a component in HVAC system by performances. The results of the standard review show that there is a need for measurement and testing standards in hydronic systems. In addition, there is no generic framework on the definition of energyefficiency measure in the reviewed standards. Findings on a case study, where lifetime commissioning procedures were tested, are presented. After the performances of the case study were defined by the generic framework, it was found that 20% of all the performances can be monitored by a building energy management system. Due to good operation, the building managed to achieve 3% lower energy consumption than design a year after the building was taken in use. In addition, results show that energy signature curves can be used only in a modified way to predict heating consumption, while electricity consumption can not be described in that way.

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