| Title: |
Mathematical modelling of green energy storage capacities with different demand scenarios |
| Authors: |
Maqbool, Muhammad Anas; Rosales, Pablo Borja; Rizvi, Md Jahir; Lee, Yeaw Chu |
| Source: |
Journal of Physics: Conference Series ; volume 3185, issue 1, page 012007 ; ISSN 1742-6588 1742-6596 |
| Publisher Information: |
IOP Publishing |
| Publication Year: |
2026 |
| Description: |
The climate crisis has necessitated immediate and extensive research into sustainable, reliable, and cost-effective energy sources. The global energy shift has accelerated the integration of renewables with various industries and energy storage systems to address the challenges posed by the intermittent nature of renewable energy sources. The UK’s hydrogen strategy and zero-emission shipping mission demonstrate promising progress, including the development of green hydrogen and green ammonia production and storage. However, renewable-hydrogen or ammonia storage systems present challenges, including determining effective storage capacity and meeting extensive energy requirements. The authors of this study have previously explored the prospects and feasibility of renewable-hydrogen and ammonia storage at a massive scale by harnessing offshore wind power from Hornsea wind farms in the UK and analysed three different demand scenarios for this stored green energy, upon which the storage capacity depends. This study aims to report the development of a graphical user interface (GUI) based on an effective mathematical model with variable inputs, designed to inform decisions about the capacity sizing of green energy storage. The GUI and a live script of the model are developed using MATLAB and validated with hypothetical data. It can provide results in both graphical and tabular formats, aiding in determining the optimal storage capacity for green hydrogen and ammonia based on various inputs, such as total energy availability and equipment energy efficiency. The GUI’s efficacy and dependability are demonstrated by its implementation. The implementation of GUI demonstrates the efficacy and dependability of the application. Therefore, this mathematical model may have applications in optimising offshore green energy infrastructure and decision-making for storage sizing. Future planning for offshore green energy storage, including green ammonia and hydrogen, will also be aided by the proposed model in application. |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| DOI: |
10.1088/1742-6596/3185/1/012007 |
| DOI: |
10.1088/1742-6596/3185/1/012007/pdf |
| Availability: |
https://doi.org/10.1088/1742-6596/3185/1/012007; https://iopscience.iop.org/article/10.1088/1742-6596/3185/1/012007; https://iopscience.iop.org/article/10.1088/1742-6596/3185/1/012007/pdf |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ ; https://iopscience.iop.org/info/page/text-and-data-mining |
| Accession Number: |
edsbas.7676A8F5 |
| Database: |
BASE |