To digitise existing energy processes within urban environments is fundamental to achieving greenhouse gas emissions reduction and energy efficiency improvement. As the modernisation of Information Technology infrastructure progresses, it still presents challenges in modelling and forecasting the future demands for energy systems and infrastructure expansion. Additionally, despite the improved capability to store and process data digitally, there is often a necessity for an intermediate level of secondary processing before actual simulations can be conducted. This research concentrates on collecting and incorporating data from an urban natural gas distribution network that is not entirely digitised, aiming to dynamically replicate and simulate the network's operations. The methodology applied in a real Italian scenario is designed to accurately estimate hourly gas demand and determine the altitude of network nodes to investigate the effects of potential energy differences. Additionally, the method efficiently distributes the demand from multiple users to their corresponding nodes. Starting from the yearly and daily demands recorded by the Distribution System Operator, with these techniques it could be possible to implement a dynamic simulation of the hydraulic properties of the natural gas. The digital simulation of gas networks is becoming more crucial, especially with the rising emphasis on incorporating hydrogen throughout gas distribution systems. Therefore, understanding network natural gas flows is essential for evaluating the potential impacts and opportunities of utilizing hydrogen as an energy vector for its optimal injection into the gas networks.
Digitalizing Pipeline Network for Hydrogen-Blended Natural Gas Distribution Assessments
Ferraro M.;
2024
Abstract
To digitise existing energy processes within urban environments is fundamental to achieving greenhouse gas emissions reduction and energy efficiency improvement. As the modernisation of Information Technology infrastructure progresses, it still presents challenges in modelling and forecasting the future demands for energy systems and infrastructure expansion. Additionally, despite the improved capability to store and process data digitally, there is often a necessity for an intermediate level of secondary processing before actual simulations can be conducted. This research concentrates on collecting and incorporating data from an urban natural gas distribution network that is not entirely digitised, aiming to dynamically replicate and simulate the network's operations. The methodology applied in a real Italian scenario is designed to accurately estimate hourly gas demand and determine the altitude of network nodes to investigate the effects of potential energy differences. Additionally, the method efficiently distributes the demand from multiple users to their corresponding nodes. Starting from the yearly and daily demands recorded by the Distribution System Operator, with these techniques it could be possible to implement a dynamic simulation of the hydraulic properties of the natural gas. The digital simulation of gas networks is becoming more crucial, especially with the rising emphasis on incorporating hydrogen throughout gas distribution systems. Therefore, understanding network natural gas flows is essential for evaluating the potential impacts and opportunities of utilizing hydrogen as an energy vector for its optimal injection into the gas networks.File | Dimensione | Formato | |
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