Clean energy futures: An Australian based foresight study

Gilmore, Nicholas; Koskinen, Ilpo; Gennip, Doménique van; Paget, Greta; Burr, Patrick A.; Obbard, E.G.; Daiyan, Rahman; Sproul, Alistair B.; Kay, Merlinde; Lennon, Alison; Konstantinou, Georgios; Hemer, Mark; Gui, Emi Minghui; Gurieff, Nicholas

doi:10.1016/j.energy.2022.125089

Cited by 16 publications

(11 citation statements)

References 80 publications

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“…The literature review led to a technology review that created a series of scenarios for the future (Gilmore et al ., forthcoming). In this review, the second author built four scenarios he used as a priming technique for eliciting and provoking insights from technological and scientific experts.…”

Section: Methodology: Participatory Co-writingmentioning

confidence: 99%

Designing energy futures: a participatory foresight study in Australia

Koskinen

Gilmore

Gui

2022

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Purpose This paper aims to: first, it studies expert opinions about the future of clean, decentralized energy technology in Australia; second, develop an interpretive and participatory foresighting methodology for a forthcoming study. Design/methodology/approach This paper reports a forecasting study about the future of clean energy. Driven mostly by economics and changing carbon policies, the energy sector is currently moving from fossil fuels to a variety of cleaner technologies. Energy experts have several incommensurate interpretations of how this change will happen. This paper describes the first phase of an ongoing study that foresight clean energy futures in Australia. By building on a participatory method in a scientific expert community, it describes the path from technological presumptions into four parallel yet interconnected scenarios. The paper also explores the social drivers behind these scenarios. Findings First, energy experts in Australia classify futures into four main scenarios: abundant, where energy will be mostly produced by solar cells; traded, where the future of energy lies in virtual power plants and microgrids; circular, which targets Australia’s NetZero goals through biomaterials, carbon capture and new powerful; secure, which secures the country’s energy supply through coal and nuclear energy. Second, they locate policy as the most important form of wildcards. The policy is multilayered from local to US politics and falls outside the scope of forecasting. Research limitations/implications The most important limitations of the study are: first, its reliance on scientific and technological experts, which guarantees its scientific validity but may underrepresent the social drivers of energy; second, this study is a methodological pilot of a larger study that will target industrial, commercial and local drivers; third, its focus on Australia, where politics, the size of the country and climate shape the uptake of clean energy in specific ways, most notably in the case of rapid uptake of solar energy. Practical implications The main practical implications of the paper are its broad focus on clean energy futures and its participatory foresighting approach, which can be repeated in other studies. Social implications The main social implication of the study is that it clearly shows that a technological perspective is necessary but not sufficient in understanding the future of clean energy. The paper also shows that local drivers importantly mold the future and should be taken into account in future studies and policy. Originality/value This paper makes two contributions. First, it organizes several technologies into four scenarios that clarify Australia’s clean energy futures better than a piecemeal study would do. Second, it developed and piloted an interpretive participatory methodology for studying futures by building on references from design research. This methodology will be used in subsequent studies.

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Section: Methodology: Participatory Co-writingmentioning

confidence: 99%

Designing energy futures: a participatory foresight study in Australia

Koskinen

Gilmore

Gui

2022

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“…Australia's National Hydrogen Strategy includes plans for the economic evaluation of large-scale hydrogen projects, including the production, storage, and export of green hydrogen. The strategy aims to leverage Australia's vast renewable energy resources for hydrogen production and explore international partnerships for export [112]. The DOE in the United States has launched various initiatives to evaluate the economics of hydrogen production, storage, and transportation.…”

Section: Current World-wide Developmentsmentioning

confidence: 99%

Large scale of green hydrogen storage: Opportunities and challenges

Ma,

Zhao,

Wang

et al. 2024

International Journal of Hydrogen Energy

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“…1) Case 1 -Line-to-Ground Fault on Bus 508 Fig. 6 shows the results of the three models for a single line to ground fault on Bus 508, which occurs at t = 0.1 s with 2 Angle differences are given in degrees.…”

Section: Transient Analysismentioning

confidence: 99%

“…Modern power systems are evolving to more complex model configurations due to the rising demand for global energy consumption and the increasing penetration of a wide variety of new power system components and devices [1], [2]. Flexible ac transmission systems (FACTS), renewable energy sources (RES), battery energy storage systems (BESS), microgrids, and dc interconnections will become more commonplace in future power systems [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Development of Power System Models for Distributed Real-Time Simulations

et al. 2022

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This paper proposes a general methodology for the development of power system models suitable for distributed real-time simulations (D-RTS) based on topology, simulator interfaces and data exchange. D-RTS have risen as functional alternatives that can combine remote and multi-vendor resources for large-scale power system simulations via a virtual connection. However, previous work focused on combination of separate models and not the performance of D-RTS when splitting a single monolithic model, failing to study the behaviors of D-RTS, including, synchronization and accuracy. The proposed methodology is used to develop distributed models of two widely used testbed large power systems, the IEEE Australian Benchmark model and the IEEE 300-Bus system. These testbeds are selected as they can be simulated as both monolithic and distributed models in available simulators in order to validate both the methodology and resulting model performance. The obtained results and comparison between monolithic and distributed models support the proposed approach and demonstrate the performance of D-RTS under both steady-state and transient operations in multiple scenarios.INDEX TERMS Co-simulation, distributed real-time simulation (D-RTS), geographically distributed realtime simulation (GD-RTS), real-time simulation (RTS)

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Clean energy futures: An Australian based foresight study

Cited by 16 publications

References 80 publications

Designing energy futures: a participatory foresight study in Australia

Designing energy futures: a participatory foresight study in Australia

Large scale of green hydrogen storage: Opportunities and challenges

Development of Power System Models for Distributed Real-Time Simulations

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