Nowadays, natural gas is one of the most important energy source in the world, either for residential or industrial consumers. These consumers need gas forecasting, so they will know how profitable it is to accumulate it at that very moment. The gas forecasting in the gas industry are usually mentioned as nomination.
My task is to manage the calculation part of the nomination forecasting system and insert it into an existing gas management framework. This component will make hourly nomination results in data-driven way for different customers.
First, I would like to explain the definition of nomination, and show the gas management framework, what I used. After that I will present some of my algorithms which are concentrated for temperature dependency, or consumption patterns. Then I will write about the components what I used for algorithm hosting and algorithms testing. In the end of the thesis, I will analyze the algorithms against each other and that if they are working by in cooperative ways.