Development of the optimum control and mechanical design algorithm for the rational use of energy in high performance buildings

In this study, a method of analysis is developed for the rational use of energy in terms of quality and quantity, on the basis of 2nd Law of Thermodynamics for optimum design and operation of hybrid electromechanical systems supported by renewable energy systems in high performance buildings. This method, performs the optimum decision making mechanism, the operation proportions and priorities within dynamic exergy platform of various electromechanical installation systems, depending upon the instant building and outdoor environmental conditions. In development of the method, REMM is used to develop an optimum design and operation algorithm. The existing installation and automation system of the building is studied within computer platform multiple and simultaneous performance of the systems is monitored in virtual medium and optimum system options are determined. Upon not observing a discernible performance in the first year operation, before using the model in real time and physically in the subject building, it has been observed that optimum system selection is not the only criteria and that an optimum control mechanism is needed as a prerequisite, and an innovative exergy based optimum system control algorithm is developed within the scope of TUBITAK project. This made it possible to achieve integrating design and operation under the roof of the same model. The model developed has added value to industry in two domains. First, for a specific building by performing climatic and operational simulations, with an iterative approach in addition to energy and exergy efficiency, it is possible to optimize minimum CO2 emission. Second, by working on the model with real time obtained data a dynamic optimum building automation can be realized. The results evaluated at exergy and common climate base, showed that energy consumption decreased by 33% on average below the results of existing conventional algorithm.