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arxiv: 2606.03783 · v1 · pith:DKNW356Cnew · submitted 2026-06-02 · 📡 eess.SY · cs.SY

An Integrated Techno-Economic Framework for Optimal Microgrid Design: An Australian Case Study

Mohamed Atef , Sanath Alahakoon , Umme Mumtahina , Peter Wolfs , Tamer Khatib , Moslem Uddin This is my paper

Pith reviewed 2026-06-28 09:02 UTC · model grok-4.3

classification 📡 eess.SY cs.SY
keywords microgrid designtechno-economic analysisrenewable energyhydrogen storagesensitivity analysisoptimal designlifecycle costingAustralia case study
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The pith

Integrated framework links simulation, dispatch and costing to compare hydrogen and battery microgrids for an Australian community.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper proposes a framework that combines time-series simulation of renewable output, dispatch optimization for daily operations, and lifecycle costing to select the lowest-cost microgrid layout for a 1000-household town in Rockhampton, Queensland. Configurations include solar and wind generation, batteries, diesel backup, grid exchange, and an optional hydrogen subsystem, with results measured by net present cost, cost of energy, renewable share and emissions. Systematic sensitivity runs across discount rates, capital costs, fuel prices, load uncertainty, resource variability, carbon pricing and outage length show that several of these drivers produce nonlinear changes in the preferred design. A sympathetic reader would care because the method supplies concrete planning numbers for remote communities that need affordable, resilient, low-emission electricity without depending on one fixed set of assumptions.

Core claim

The integrated techno-economic framework links time-series simulation, dispatch-based operation and lifecycle costing to evaluate hybrid microgrid configurations comprising photovoltaic and wind generation, battery storage, diesel backup, grid exchange and an optional hydrogen subsystem, with systematic sensitivity analysis across financial, technical and policy drivers demonstrating nonlinear shifts in optimal design for a 1000-household Australian case study.

What carries the argument

Integrated techno-economic framework that connects time-series simulation, dispatch optimization and net present cost calculations to assess and compare microgrid configurations under multiple sensitivities.

If this is right

  • Several sensitivity dimensions induce nonlinear shifts in the optimal microgrid design.
  • Breakpoints appear where capital-intensive renewable-storage expansion becomes economically preferable.
  • Hydrogen-enabled and battery-centric solutions can be compared transparently on the same indicators.
  • The framework supplies planning guidance for resilient, low-emission community microgrids under Australian operating conditions.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same linkage of simulation, dispatch and costing could be reused to test microgrid designs in other regions with comparable renewable resources and grid reliability.
  • Policy makers could use the sensitivity breakpoints to set carbon-price thresholds that favor higher renewable penetration.
  • Adding more detailed modeling of grid outage statistics might further strengthen the robustness assessment for remote sites.
  • The no-hydrogen attribution case implies that excluding the hydrogen path may understate resilience value during extended outages.

Load-bearing premise

The time-series simulation and dispatch-based operation models accurately capture real-world performance and interactions of the hybrid components under the tested conditions.

What would settle it

Field measurements from a deployed microgrid matching the Rockhampton load and resource profile that show actual net present cost or emissions differing substantially from the framework's predicted values.

Figures

Figures reproduced from arXiv: 2606.03783 by Mohamed Atef, Moslem Uddin, Peter Wolfs, Sanath Alahakoon, Tamer Khatib, Umme Mumtahina.

Figure 1
Figure 1. Figure 1: Effect of discount rate on techno-economic performance and system sizing: (a) [PITH_FULL_IMAGE:figures/full_fig_p015_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Impact of technology capital cost assumptions on techno-economic performance [PITH_FULL_IMAGE:figures/full_fig_p016_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Impact of fuel price multiplier on techno-economic performance and system [PITH_FULL_IMAGE:figures/full_fig_p017_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Impact of load multiplier on techno-economic performance and system sizing. (a) [PITH_FULL_IMAGE:figures/full_fig_p018_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Impact of renewable resource variability on techno-economic performance and [PITH_FULL_IMAGE:figures/full_fig_p019_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Impact of carbon pricing on techno-economic performance, renewable deployment, [PITH_FULL_IMAGE:figures/full_fig_p020_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Impact of grid outage conditions on techno-economic performance and system [PITH_FULL_IMAGE:figures/full_fig_p021_7.png] view at source ↗
read the original abstract

Reliable and affordable electricity supply remains a challenge for remote and regional communities, motivating the deployment of renewable-based microgrids supported by flexible storage and advanced planning methods. This paper proposes an integrated techno-economic framework for optimal microgrid design and robustness assessment, and applies it to a 1000-household residential community in Rockhampton, Queensland (Australia). The framework links time-series simulation, dispatch-based operation, and lifecycle costing to evaluate hybrid configurations comprising photovoltaic and wind generation, battery storage, diesel backup, grid exchange, and an optional hydrogen subsystem (electrolyzer--hydrogen storage--fuel cell). Key indicators include net present cost (NPC), cost of energy (COE), renewable penetration, energy purchased/sold, and emissions-related outcomes. To avoid conclusions that depend on a single set of assumptions, the study performs systematic sensitivity analysis across financial, technical and policy drivers: discount rate, technology capital costs, fuel price, load uncertainty, renewable resource variability, carbon pricing/emissions cost, and grid outage duration, supplemented by a no-hydrogen attribution case. The results demonstrate that several sensitivity dimensions induce nonlinear shifts in the optimal design, including breakpoints where capital-intensive renewable--storage expansion becomes economically preferable. The proposed framework enables transparent comparison of hydrogen-enabled and battery-centric solutions and provides planning guidance for resilient, low-emission community microgrids under Australian operating conditions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript proposes an integrated techno-economic framework that links time-series simulation, dispatch-based operation, and lifecycle costing to optimize hybrid microgrid designs (PV/wind/battery/diesel/grid exchange with optional hydrogen subsystem) for a 1000-household residential community in Rockhampton, Queensland. Key outputs are net present cost (NPC), cost of energy (COE), renewable penetration, energy exchange, and emissions metrics, evaluated under systematic sensitivity analysis on discount rate, capital costs, fuel price, load uncertainty, resource variability, carbon pricing, grid outage duration, and a no-hydrogen case. The central claim is that the framework enables transparent hydrogen-versus-battery comparisons and supplies planning guidance for resilient, low-emission Australian community microgrids.

Significance. If the underlying models prove accurate, the work supplies actionable, scenario-robust guidance for microgrid planners by identifying nonlinear design breakpoints and quantifying trade-offs between hydrogen and battery storage under Australian conditions.

major comments (2)
  1. [Abstract / framework linkage] Abstract and framework description: The linkage of time-series simulation, dispatch-based operation, and lifecycle costing is asserted, yet no specification is given for dispatch assumptions (perfect foresight vs. rolling horizon, ramp-rate limits, hydrogen round-trip efficiency curves). These assumptions are load-bearing for the hydrogen-enabled versus battery-centric comparison and the resulting planning guidance.
  2. [Methods] Methods / validation: No validation of the time-series simulation or dispatch models against measured data, no benchmark comparison to established microgrid test cases, and no sensitivity of the models themselves to structural assumptions (e.g., efficiency curves) is reported. Parameter sensitivity alone does not test whether the dispatch logic systematically over- or under-estimates renewable penetration or hydrogen losses.
minor comments (1)
  1. [Abstract] Abstract: The phrase 'systematic sensitivity analysis across financial, technical and policy drivers' would benefit from an explicit list or table reference to the exact parameter ranges and scenario counts.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for their thorough review and constructive feedback on our manuscript. We address each of the major comments below and outline the revisions we will make to strengthen the paper.

read point-by-point responses

  1. Referee: [Abstract / framework linkage] Abstract and framework description: The linkage of time-series simulation, dispatch-based operation, and lifecycle costing is asserted, yet no specification is given for dispatch assumptions (perfect foresight vs. rolling horizon, ramp-rate limits, hydrogen round-trip efficiency curves). These assumptions are load-bearing for the hydrogen-enabled versus battery-centric comparison and the resulting planning guidance.

    Authors: We agree that explicit specification of the dispatch assumptions is necessary for transparency, particularly given their importance to the hydrogen versus battery comparisons. Although the methods section of the manuscript outlines the overall framework, we will revise the abstract and expand the methods to clearly state that the dispatch optimization employs a perfect-foresight linear programming approach over hourly time steps. Hydrogen round-trip efficiency is modeled using a fixed 65% value based on literature values for the electrolyzer-fuel cell chain, with no ramp-rate constraints applied due to the hourly resolution. These details will be added, along with a note on the assumption of perfect foresight as a limitation. revision: yes

  2. Referee: [Methods] Methods / validation: No validation of the time-series simulation or dispatch models against measured data, no benchmark comparison to established microgrid test cases, and no sensitivity of the models themselves to structural assumptions (e.g., efficiency curves) is reported. Parameter sensitivity alone does not test whether the dispatch logic systematically over- or under-estimates renewable penetration or hydrogen losses.

    Authors: The study is a modeling exercise using synthetic load data and typical meteorological year resource profiles, so direct validation against measured microgrid data is not feasible within the current scope. We will, however, add a dedicated limitations subsection that discusses the structural assumptions, including the fixed efficiency curves, and conduct additional sensitivity analyses on the hydrogen efficiency parameter to assess its impact on renewable penetration and losses. We will also include comparisons to results from established tools like HOMER for the base case to provide benchmarking. revision: partial

standing simulated objections not resolved
  • Empirical validation of the time-series simulation and dispatch models against real measured data from an operational microgrid, as no such dataset is available for the Rockhampton case study community.

Circularity Check

0 steps flagged

No circularity: framework applies standard simulation and optimization to external inputs

full rationale

The paper describes an integrated techno-economic framework that links time-series simulation, dispatch-based operation, and lifecycle costing to evaluate microgrid configurations. Sensitivity analysis varies external parameters (discount rate, capital costs, fuel price, load uncertainty, renewable variability, carbon pricing, grid outage duration) across scenarios, with no indication that any output is fitted to data and then relabeled as a prediction. No self-citations are invoked as load-bearing premises, no uniqueness theorems are imported, and no ansatz or renaming of known results occurs. The derivation chain consists of applying established modeling steps to given inputs and reporting the resulting indicators, rendering it self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

3 free parameters · 1 axioms · 0 invented entities

The framework rests on standard techno-economic modeling assumptions and input parameters that are varied rather than fitted; no new entities are introduced.

free parameters (3)
  • discount rate
    Treated as a variable input in sensitivity analysis rather than fitted to produce the central claim.
  • technology capital costs
    Varied across scenarios as an external driver; not derived from the model itself.
  • fuel price
    Input parameter swept in sensitivity; not an output of the derivation.
axioms (1)
  • domain assumption Standard assumptions in lifecycle costing, time-series simulation, and dispatch optimization hold for the listed microgrid components.
    Invoked when linking simulation, dispatch, and costing in the framework description.

pith-pipeline@v0.9.1-grok · 5798 in / 1469 out tokens · 28482 ms · 2026-06-28T09:02:14.106840+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

70 extracted references

  1. [1]

    Y. Guo, C. Zhao, Islanding-aware robust energy management for micro- grids, IEEE Transactions on Smart Grid 9 (2018) 1301–1309

    2018

  2. [2]

    X. Li, J. Zhu, Y. Wang, Z. Li, C. Wang, L. Guo, Enhanced dynamic stability control for low-inertia hybrid ac/dc microgrid with distributed energy storage systems, IEEE Access 7 (2019) 91234–91242

    2019

  3. [3]

    Y. Liu, Y. Li, H. B. Gooi, H. Xin, J. Pan, Distributed optimal tie-line power flow control for multiple interconnected ac microgrids, IEEE Transactions on Power Systems 34 (2019) 1869–1880

    2019

  4. [4]

    X. Gong, F. Dong, M. A. Mohamed, O. M. Abdalla, Z. M. Ali, A secured energy management architecture for smart hybrid microgrids considering pem-fuel cell and electric vehicles, Ieee Access 8 (2020) 47807–47823

    2020

  5. [5]

    M. Atef, T. Khatib, M. F. Abdullah, M. F. Romlie, Optimization of a hybrid solar pv and gas turbine generator system using the loss of load probability index, Clean Technologies 2 (2020) 16

    2020

  6. [6]

    Q. Li, Z. Cheng, M. Yan, Y. Wang, X. Dong, Research on the hybrid wind–solar–energy storage ac/dc microgrid system and its stability during smooth state transitions, Energies 16 (2023) 7930

    2023

  7. [7]

    Hatziargyriou, H

    N. Hatziargyriou, H. Asano, R. Iravani, C. Marnay, Microgrids, IEEE Power and Energy Magazine 5 (2007) 78–94

    2007

  8. [8]

    Y. Gui, B. Wei, M. Li, J. M. Guerrero, J. C. Vasquez, Passivity-based coordinated control for islanded ac microgrid, Applied Energy 229 (2018) 551–561. 26

    2018

  9. [9]

    Ejuh Che, K

    E. Ejuh Che, K. Roland Abeng, C. D. Iweh, G. J. Tsekouras, A. Fopah- Lele, The impact of integrating variable renewable energy sources into grid-connected power systems: challenges, mitigation strategies, and prospects, Energies 18 (2025) 689

    2025

  10. [10]

    L. Che, M. Shahidehpour, A. Abusorrah, A. Alabdulwahab, X. Zhang, Optimal interconnection planning of community microgrids with re- newable energy sources, IEEE Transactions on Smart Grid 8 (2017) 1054–1063

    2017

  11. [11]

    G. R. Goyal, S. Vadhera, Solution to uncertainty of renewable energy sources and peak hour demand in smart grid system, Measurement: Sensors 33 (2024) 101129

    2024

  12. [12]

    M. Atef, M. Abdullah, T. Khatib, M. Romlie, Utilization of artificial neural networks to improve the accuracy of a hybrid power system model, in: 2019 IEEE Student Conference on Research and Development (SCOReD), IEEE, 2019, pp. 284–288

    2019

  13. [13]

    J. He, X. Wu, X. Wu, Y. Xu, J. M. Guerrero, Small-signal stability analysis and optimal parameters design of microgrid clusters, IEEE Access 7 (2019) 36896–36909

    2019

  14. [14]

    R. Hao, Q. Ai, T. Guan, Y. Cheng, D. Wei, Decentralized price incentive energy interaction management for interconnected microgrids, Electric Power Systems Research 172 (2019) 114–128

    2019

  15. [15]

    M. Atef, M. Uddin, M. M. Rana, M. R. Sarkar, G. Shafiullah, Data- driven optimization framework for microgrid energy management, in: Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications, CRC Press, 2024, pp. 169–188

    2024

  16. [16]

    Elkhatib, T

    R. Elkhatib, T. Kaoutari, H. Louahlia, Green hydrogen energy source for a residential fuel cell micro-combined heat and power, Applied Thermal Engineering 248 (2024) 123194

    2024

  17. [17]

    D. Das, I. Chakraborty, A. K. Bohre, P. Kumar, R. Agarwala, Sustainable integration of green hydrogen in renewable energy systems for residential and ev applications, International Journal of Energy Research (2024). 27

    2024

  18. [20]

    S. J. Navas, G. C. González, F. Pino, Hybrid power-heat microgrid solution using hydrogen as an energy vector for residential houses in spain. a case study, Energy Conversion and Management 263 (2022) 115724

    2022

  19. [21]

    Uddin, H

    M. Uddin, H. Mo, D. Dong, S. Elsawah, Techno-economic potential of multi-energy community microgrid: The perspective of australia, Renewable Energy 219 (2023) 119544

    2023

  20. [22]

    G. Ali, N. Javaid, S. Rehman, M. Butt, I. Khan, A comprehensive review on energy management strategy of microgrids, Energies 16 (2023) 1207

    2023

  21. [23]

    Singh, V

    H. Singh, V. Sharma, M. Niazi, A comprehensive review on sustain- able energy management systems for optimal operation of microgrids, Renewable and Sustainable Energy Reviews 173 (2023) 113152

    2023

  22. [24]

    Mohammadi, A

    A. Mohammadi, A. Kumar, R. Singh, Enhancing microgrid stability and energy management: Techniques, challenges, and future directions, Energies 16 (2023) 4672

    2023

  23. [25]

    S. T. Meraj, S. S. Yu, M. S. Rahman, K. Hasan, M. H. Lipu, H. Trinh, Energy management schemes, challenges and impacts of emerging inverter technology for renewable energy integration towards grid decarbonization, Journal of Cleaner Production 405 (2023) 137002

    2023

  24. [26]

    Ahmad, M

    F. Ahmad, M. T. Iqbal, S. Rehman, Applications of energy storage systems in enhancing energy management and access in microgrids: A review, Journal of Energy Storage 69 (2023) 107807

    2023

  25. [27]

    X. Liu, T. Zhao, H. Deng, P. Wang, J. Liu, F. Blaabjerg, Microgrid energy management with energy storage systems: A review, CSEE Journal of Power and Energy Systems (2022). 28

    2022

  26. [28]

    Alvarez, M

    J. Alvarez, M. Sanchez, P. Torres, S. Rehman, State-of-the-art review on energy management and control of networked microgrids, Energies 16 (2023) 5378

    2023

  27. [29]

    L. P. Van, K. Do Chi, T. N. Duc, Review of hydrogen technologies based microgrid: Energy management systems, challenges and future recommendations, International Journal of Hydrogen Energy 48 (2023) 14127–14148

    2023

  28. [30]

    Naseri, S

    N. Naseri, S. El Hani, M. Machmoum, E. Elbouchikhi, A. Daghouri, Energy management strategy for a net zero emission islanded photovoltaic microgrid-based green hydrogen system, Energies 17 (2024) 2111

    2024

  29. [31]

    Enaloui, S

    R. Enaloui, S. Sharifi, B. Faridpak, A. Hammad, M. Al-Hussein, P. Musilek, Techno-economic assessment of a solar-powered green hydro- gen storage concept based on reversible solid oxide cells for residential micro-grid: A case study in calgary, Energy 319 (2025) 134981

    2025

  30. [32]

    H. Raj, S. Jaiswal, A. Maheshwari, A review of energy management strategy and forecasting techniques in multi microgrids, International Journal of Ambient Energy 46 (2025) 2507808

    2025

  31. [33]

    Agha Kassab, F

    F. Agha Kassab, F. Locment, M. Sechilariu, B. Celik, R. Rodriguez, A comprehensive review of sizing and energy management strategies for optimal planning of microgrids with pv and other renewable integration, Applied Sciences 14 (2024) 10479

    2024

  32. [34]

    J. A. Rodriguez-Gil, E. Mojica-Nava, D. Vargas-Medina, M. F. Arevalo- Castiblanco, C. A. Cortes, S. Rivera, J. Cortes-Romero, Energy man- agement system in networked microgrids: An overview, Energy Systems (2024) 1–32

    2024

  33. [35]

    Uddin, H

    M. Uddin, H. Mo, D. Dong, S. Elsawah, J. Zhu, J. M. Guerrero, Micro- grids: A review, outstanding issues and future trends, Energy Strategy Reviews 49 (2023) 101127

    2023

  34. [36]

    M. Atef, S. Alahakoon, P. Wolfs, T. Khatib, U. Mumtahina, M. Uddin, Techno-economic energy planning of residential microgrids: An australian case study, in: 2025 IEEE PES 35th Australasian Universities Power Engineering Conference (AUPEC), IEEE, 2025, pp. 1–5. 29

    2025

  35. [37]

    M. Atef, S. Alahakoon, P. Wolfs, T. Khatib, U. Mumtahina, M. Uddin, Real-time energy management of residential microgrids: An australian case study, in: 2025 IEEE PES 35th Australasian Universities Power Engineering Conference (AUPEC), IEEE, 2025, pp. 1–5

    2025

  36. [38]

    M. E. González-Niño, O. H. Sierra-Herrera, W. A. Pineda-Muñoz, N. Muñoz-Galeano, J. M. López-Lezama, Exploring technology trends and future directions for optimized energy management in microgrids, Information 16 (2025) 183

    2025

  37. [39]

    A. R. Abbasi, D. Baleanu, Recent developments of energy management strategies in microgrids: An updated and comprehensive review and classification, Energy Conversion and Management 297 (2023) 117723

    2023

  38. [40]

    B. Modu, M. P. Abdullah, A. L. Bukar, M. F. Hamza, A systematic review of hybrid renewable energy systems with hydrogen storage: Sizing, optimization, and energy management strategy, International Journal of Hydrogen Energy (2023)

    2023

  39. [41]

    D. M. Sackey, M. Amoah, A. B. Jehuri, D.-G. Owusu-Manu, A. Acapkovi, Techno-economic analysis of a microgrid design for a commercial health facility in ghana-case study of zipline sefwi-wiawso, Scientific African 19 (2023) e01552

    2023

  40. [42]

    M. A. Ahmed, G. Abbas, T. A. Jumani, N. Rashid, A. A. Bhutto, S. M. Eldin, Techno-economic optimal planning of an industrial microgrid considering integrated energy resources, Frontiers in Energy Research 11 (2023) 1145888

    2023

  41. [43]

    M. Atef, S. Alahakoon, P. Wolfs, U. Mumtahina, T. Khatib, M. Ud- din, Energy management in microgrids: Commercial, industrial, and residential perspectives, Energies 19 (2026) 419

    2026

  42. [44]

    F. Wang, J. Zhao, L. Chen, Review of energy management systems in microgrids: Classification, strategies, and future challenges, Journal of Energy Storage 80 (2024) 108765

    2024

  43. [45]

    Fernandez, N

    L. Fernandez, N. Patel, D. Kumar, Energy management strategies for active distribution networks and microgrids: A comprehensive survey, Renewable and Sustainable Energy Reviews 181 (2025) 113701. 30

    2025

  44. [46]

    Zheng, M

    Z. Zheng, M. Shafique, X. Luo, S. Wang, A systematic review towards integrative energy management of smart grids and urban energy systems, Renewable and Sustainable Energy Reviews 189 (2024) 114023

    2024

  45. [47]

    Ferahtia, A

    S. Ferahtia, A. Houari, T. Cioara, M. Bouznit, H. Rezk, A. Djerioui, Recent advances on energy management and control of direct current microgrid for smart cities and industry: A survey, Applied Energy 368 (2024) 123501

    2024

  46. [48]

    Z. M. Ali, M. Calasan, S. H. A. Aleem, F. Jurado, F. H. Gandoman, Applications of energy storage systems in enhancing energy management and access in microgrids: A review, Energies 16 (2023) 5930

    2023

  47. [49]

    Sadeghian, A

    O. Sadeghian, A. M. Shotorbani, S. Ghassemzadeh, B. Mohammadi- Ivatloo, Energy management of hybrid fuel cell and renewable energy based systems-a review, International Journal of Hydrogen Energy 107 (2025) 135–163

    2025

  48. [50]

    M. Atef, S. Alahakoon, U. Mumtahina, P. Wolfs, T. Khatib, M. Uddin, A review of microgrid energy management systems: methods, challenges, and future directions, International Journal of Ambient Energy 47 (2026) 2595117

    2026

  49. [51]

    X. Chen, P. Wu, J. Yang, A comprehensive review on dc microgrid control and energy management strategies, International Journal of Electrical Power & Energy Systems 155 (2025) 109350

    2025

  50. [52]

    S. E. Eyimaya, N. Altin, Review of energy management systems in microgrids, Applied Sciences 14 (2024) 1249

    2024

  51. [53]

    Sadeghian, A

    O. Sadeghian, A. M. Shotorbani, S. Ghassemzadeh, B. Mohammadi- Ivatloo, Energy management of hybrid fuel cell and renewable energy based systems-a review, International Journal of Hydrogen Energy (2024)

    2024

  52. [54]

    M. U. Safder, M. J. Sanjari, A. Hamza, R. Garmabdari, M. A. Hos- sain, J. Lu, Enhancing microgrid stability and energy management: Techniques, challenges, and future directions, Energies 16 (2023) 6417. 31

    2023

  53. [55]

    L. Han, M. Chen, X. Zhang, A review of hierarchical energy management system in networked microgrids for sustainable operation, International Journal of Electrical Power & Energy Systems 153 (2024) 109218

    2024

  54. [56]

    L. Xu, W. Li, M. Khan, Energy management system in networked microgrids: An overview, Renewable Energy 222 (2024) 1489–1507

    2024

  55. [57]

    Agha Kassab, R

    F. Agha Kassab, R. Rodriguez, B. Celik, F. Locment, M. Sechilariu, A comprehensive review of sizing and energy management strategies for optimal planning of microgrids with pv and other renewable integration, Applied Sciences 14 (2024) 10479

    2024

  56. [58]

    Abbas, S

    N. Abbas, S. Shah, A. Malik, Review of hydrogen technologies-based microgrid energy management systems, challenges and future directions, International Journal of Hydrogen Energy 48 (2023) 25467–25487

    2023

  57. [59]

    URL:https://www.dcceew.gov.au/sites/defa ult/files/documents/national-hydrogen-strategy-2024.pdf , accessed: 2026-03-29

    DepartmentofClimateChange, Energy, theEnvironmentandWater(DC- CEEW), National Hydrogen Strategy 2024, Technical Report, Australian Government, 2024. URL:https://www.dcceew.gov.au/sites/defa ult/files/documents/national-hydrogen-strategy-2024.pdf , accessed: 2026-03-29

    2024

  58. [60]

    URL:https://www.dcceew.gov.au/en ergy/publications/australias-national-hydrogen-strategy , accessed: 2026-03-29

    Department of Climate Change, Energy, the Environment and Water (DCCEEW), Australia’s National Hydrogen Strategy, DCCEEW (Energy publications webpage), 2024. URL:https://www.dcceew.gov.au/en ergy/publications/australias-national-hydrogen-strategy , accessed: 2026-03-29

    2024

  59. [61]

    URL:https: //www.dcceew.gov.au/energy/hydrogen, accessed: 2026-03-29

    Department of Climate Change, Energy, the Environment and Water (DCCEEW), Growing Australia’s hydrogen industry, DCCEEW (Hy- drogen webpage; last updated 30 January 2026), 2026. URL:https: //www.dcceew.gov.au/energy/hydrogen, accessed: 2026-03-29

    2026

  60. [62]

    37, assent 13 Sep 2022), 2022

    Parliament of Australia, Climate Change Bill 2022, Bills & Legislation (Bill details page; Act no. 37, assent 13 Sep 2022), 2022. URL:https: //www.aph.gov.au/Parliamentary_Business/Bills_Legislation/ Bills_Search_Results/Result?bId=r6885, accessed: 2026-03-29

    2022

  61. [63]

    URL:https: 32 //www.legislation.gov.au/C2022A00037/latest/text , accessed: 2026-03-29

    Australian Government, Climate Change Act 2022, Federal Register of Legislation (latest compilation shown on page), 2022. URL:https: 32 //www.legislation.gov.au/C2022A00037/latest/text , accessed: 2026-03-29

    2022

  62. [64]

    A. Ali, M. Khan, S. Rehman, Energy management of hybrid fuel cell and renewable energy based systems: A review, International Journal of Hydrogen Energy 49 (2024) 563–589

    2024

  63. [65]

    Australian Renewable Energy Agency (ARENA), Regional Microgrids Program, ARENA funding webpage (program announced 25 Aug 2023),

    2023

  64. [66]

    URL: https://arena.gov.au/funding/rmp/, accessed: 2026-03- 29

    2026

  65. [67]

    Australian Renewable Energy Agency (ARENA), Empowering First Nations communities with ARENA backed microgrids, ARENA news,

  66. [68]

    URL: https://arena.gov.au/news/empowering-first-nat ions-communities-with-arena-backed-microgrids/ , accessed: 2026-03-29

    2026

  67. [69]

    Arévalo, D

    P. Arévalo, D. Ochoa-Correa, E. Villa-Ávila, V. Iñiguez-Morán, P. Astudillo-Salinas, Systematic review of hierarchical and multi-agent optimization strategies for p2p energy management and electric machines in microgrids, Applied Sciences 15 (2025) 4817

    2025

  68. [70]

    The Hon Chris Bowen MP, New National Hydrogen Strategy sets up Australia as renewable superpower, Media release, Ministers for the Department of Climate Change, Energy, the Environment and Water,

  69. [71]

    URL: https://minister.dcceew.gov.au/bowen/media-relea ses/new-national-hydrogen-strategy-sets-australia-renewab le-superpower, accessed: 2026-03-29

    2026

  70. [72]

    URL:https://www.ce fc.com.au/, accessed: 2026-03-29

    Clean Energy Finance Corporation (CEFC), Clean Energy Finance Corporation (CEFC) — Home, Website, 2026. URL:https://www.ce fc.com.au/, accessed: 2026-03-29. 33

    2026