Natural Gas (NG) is odorless and therefore requires an odorizer to be injected into its flow to ensure detection when a gas leak occurs and thus provide satisfactory safety levels. The odorisation process is a delicate step that takes place within the City Gate Stations (CGS), which are key elements of the NG network infrastructure. This work aims to develop a method for offline monitoring of the odorization process within a CGS located in central Italy, based on the exploiting of the odorization station dataset through several machine learning models development, to evaluate the odorization process performance. An unsupervised machine learning method based on two different algorithms, the LOF (Local Outlier Factor) algorithm and the K-Means clustering, is developed, and then data mining is carried out on the dataset to extract useful information. The results show that the use of the algorithm made it possible to identify anomalous points in the dataset and their dependence on the main operating parameters of the CGS, as well as some clusters of under-odor and over-odor tendencies for the system under consideration.
Natural gas, pumped by compressors in the high-pressure network, arrives at CGS stations with known composition, tending to consist of about 95 % methane and the rest of a mixture of various hydrocarbons and other gases . This mixture is odorless, colorless, and flammable, so it is important to ensure the addition of an odorant into gas that makes the mixture identifiable in the event of a leak , before it is sent to regional and local distribution networks.
From a technical point of view, odorizing systems can be divided into injection systems and vaporization systems, depending on the different types of equipment and physical principles used to insert the odorizing substance into the gas flow. The former injects directly an odorant into the flowing NG stream, while the latter is based on the diffusion of odorant into the gas stream , , . In a study by MARCOGAZ , the Technical Association of the European Natural Gas Industry, the requirements, characteristics of the various odorants, processes, and regulations related to NG odorization of 19 different European countries, including Italy, were summarized.