Energy expansion planning with a human evolutionary model

This study presents a novel method for planning the expansion of transmission lines and energy storage systems while considering the interconnectedness of electricity and gas networks. We developed a two-level stochastic planning model that addresses both the expansion of transmission and battery systems in the electrical grid and the behavior of the gas network. This research explores the challenges and effects of integrating high levels of renewable energy sources while ensuring security within both networks. Our model uses a stochastic mixed-integer non-linear programming approach. To solve this complex model, we applied the Human Evolutionary Model (HEM). We tested our approach on two case studies: a simple 6-node network and the more complex IEEE RTS 24-bus network for the electricity grid, combined with 5-node and 10-node gas networks, respectively. The results demonstrate the effectiveness of our model, particularly in scenarios where connections in the power and gas networks are disrupted, preventing load shedding even when integrated network connections are cut.

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Publication Details

Journal
Energy Informatics
Published
2024-08-05
DOI
https://doi.org/10.1186/s42162-024-00371-x
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.21
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article

Energy expansion planning with a human evolutionary model

Mehdi Radmehr, Mahmoud Samiei Moghaddam, Reza Ebrahimi, Hosein Farokhzad Rostami
1 citations
Energy Informatics
Integrated Energy Systems Optimization
0.21
article

Energy expansion planning with a human evolutionary model

Mehdi Radmehr, Mahmoud Samiei Moghaddam, Reza Ebrahimi, Hosein Farokhzad Rostami
article en
1 citations

Abstract

This study presents a novel method for planning the expansion of transmission lines and energy storage systems while considering the interconnectedness of electricity and gas networks. We developed a two-level stochastic planning model that addresses both the expansion of transmission and battery systems in the electrical grid and the behavior of the gas network. This research explores the challenges and effects of integrating high levels of renewable energy sources while ensuring security within both networks. Our model uses a stochastic mixed-integer non-linear programming approach. To solve this complex model, we applied the Human Evolutionary Model (HEM). We tested our approach on two case studies: a simple 6-node network and the more complex IEEE RTS 24-bus network for the electricity grid, combined with 5-node and 10-node gas networks, respectively. The results demonstrate the effectiveness of our model, particularly in scenarios where connections in the power and gas networks are disrupted, preventing load shedding even when integrated network connections are cut.

Energy InformaticsVol. 7(1)
Islamic Azad University Sari Branch (IR), Islamic Azad University of Gorgan (IR), Islamic Azad University, Damghan Branch (IR)
Affordable and clean energy
Openalex Percentile: Top 50%
Integrated Energy Systems Optimization
0.21
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Energy expansion planning with a human evolutionary model — Mehdi Radmehr, Mahmoud Samiei Moghaddam, et al. · Energy Informatics (2024) | TGRS Research Map | TGRS