TY - JOUR
T1 - Uncertainty analysis of the impact of increasing levels of gas and electricity network integration and storage on Techno-Economic-Environmental performance
AU - Hosseini, Seyed Hamid Reza
AU - Allahham, Adib
AU - Walker, Sara Louise
AU - Taylor, Phil
PY - 2021/5/1
Y1 - 2021/5/1
N2 - This paper presents an evaluation framework for Techno-Economic-Environmental (TEE) impact of different networks integration levels and storage devices on performance of Integrated Gas and Electricity Networks (IGENs). Probabilistic distributions for modelling sources of uncertainty (loads, Renewable Energy Sources (RESs), economic and environmental analysis) were sampled through Monte Carlo Simulation. The framework performs the TEE operational analysis of IGENs for future possible scenarios for different technology development status and different levels of load and RESs. Then, it calculates the energy imported from upstream networks, operational costs, and emissions. In this way, the framework provides a basis for making well-informed and risk-based decisions of design choices for meeting 2050 carbon targets in the presence of aforementioned sources of uncertainty. Analysis of the results of application of the framework to a real-world case study shows that as the electrical renewable generation grows with respect to the total demand, the value of integrated operation of the networks also grows as shown by the reduction in the TEE parameters. Given that demand reduction and decarbonisation of electricity and gas networks is a priority, the coupled configurations are likely to become more attractive between now and 2050, in the presence of the considered sources of uncertainty.
AB - This paper presents an evaluation framework for Techno-Economic-Environmental (TEE) impact of different networks integration levels and storage devices on performance of Integrated Gas and Electricity Networks (IGENs). Probabilistic distributions for modelling sources of uncertainty (loads, Renewable Energy Sources (RESs), economic and environmental analysis) were sampled through Monte Carlo Simulation. The framework performs the TEE operational analysis of IGENs for future possible scenarios for different technology development status and different levels of load and RESs. Then, it calculates the energy imported from upstream networks, operational costs, and emissions. In this way, the framework provides a basis for making well-informed and risk-based decisions of design choices for meeting 2050 carbon targets in the presence of aforementioned sources of uncertainty. Analysis of the results of application of the framework to a real-world case study shows that as the electrical renewable generation grows with respect to the total demand, the value of integrated operation of the networks also grows as shown by the reduction in the TEE parameters. Given that demand reduction and decarbonisation of electricity and gas networks is a priority, the coupled configurations are likely to become more attractive between now and 2050, in the presence of the considered sources of uncertainty.
KW - Gas and electricity storage devices
KW - Integrated gas and electricity networks
KW - Networks integration level
KW - Power-to-Gas
KW - Techno-economic-environmental
KW - Uncertainty analysis
UR - http://www.scopus.com/inward/record.url?scp=85100682414&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2021.119968
DO - 10.1016/j.energy.2021.119968
M3 - Article
AN - SCOPUS:85100682414
SN - 0360-5442
VL - 222
JO - Energy
JF - Energy
M1 - 119968
ER -