This report is a final thesis documenting the finalization of a degree in Master of Science in Indoor Environmental Engineering at The Faculties of Engineering, Science and Medicine at Aalborg University. The report begins with a thorough literature review on existing methods for evaluation of the performance of the indoor environment. The focus in mainly directed at the evaluation of the thermal indoor environment, but also indoor air quality together with the influence from the indoor climate on energy consumption, productivity and economy are dealt with. Based on the literature review, existing methods for evaluation of a buildings indoor climate performance, momentary as well as long-term, has been expanded and optimized. The methods consists of performance indicators for the thermal and atmospheric indoor climate as well as energy consumption based on the Eco-factor method. The extension of the Eco-factor method for long-term evaluation of thermal comfort gives more detailed information on the perceived indoor climate, and has in this project been applied on to buildings. Using data from thermal building simulation programmes, the extended Eco-factor contains furthermore statistical evaluation methods. Furthermore, a coupling between the programmes BSim and Matlab has been carried out in cooperation with the Danish Building Research Institute (SBi). This coupling has, besides sensitivity and uncertainty analysis on the chosen buildings, been used for investigating an adaptive control algorithm that calculates the set point for heating and cooling as a function of the outdoor air temperature. The background for this are empirical investigations which has shown a large energy saving potential without reducing the thermal indoor climate. Potential energy savings together with the theoretical influence on thermal indoor environment has been investigated through simulations of a chosen building. Is was found, that calculating the set points for heating and cooling after this algorithm will lead to an increased energy consumption for the chosen building compared with a traditional control strategy. The simulations however showed a decrease in the predicted percentage of dissatisfied with the thermal indoor environment when using the adaptive control algorithm compared with conventional heating and cooling set points.