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Dissertation
HVAC Optimization by datamining: Implementation of ISO 50001

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Abstract

Porta Capena is specialised in data mining for energy management. Data analysis of public buildings can shows potential savings before and after opening hours of the building. One of the actions for energy reduction that Porta Capena often recommends, is the integrating of an optimal start-stop controller for the HVAC system of the building. The integration of the start-stop algorithm must be in line within the standard ISO 50001. The data collected from the building is used to generate heating and cooling profiles for the calculation of optimal start-stop. To ensure the thermal comfort, air temperature must be measured and added to the data in addition to the energy measurements of electricity, water and gas. The algorithms deliver their results in Microsoft Excel for further analysis. Graphs are made to visualize potential savings with the effect of the optimal start-stop integrated in the HVAC control system. The optimal stop of the HVAC results in energy savings after opening hours of the building. The optimal stop depends on a lot of parameters, including weather forecast, that are integrated in the cooling profile. Optimal start will prevent energy consumption before opening hours. The optimal start control needs the preheating curve of the building to calculate the optimal start moment. Optimization of the start-stop system can be integrated in the control system by three strategies: • Install a new control system of the HVAC unit with integrated start-stop algorithm • Improve the configuration of the current HVAC controller • Expand the control system with new controllers Based on the benefits and disadvantages of each strategy, the energy management team can decide the best strategy for their building.

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