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A comprehensive review of uncertainties in power systems, covering modeling, impact, and mitigation, is essential to understand and manage the challenges faced by the electric grid. Uncertainties in power systems can arise from various sources and can have significant implications for grid reliability, stability, and economic efficiency. Australia, susceptible to extreme weather such as wildfires and heavy rainfall, faces vulnerabilities in its power network assets. The decentralized distribution of population centers poses economic challenges in supplying power to remote areas, which is a crucial consideration for the emerging technologies emphasized in this paper. In addition, the evolution of modern power grids, facilitated by deploying the advanced metering infrastructure (AMI), has also brought new challenges to the system due to the risk of cyber-attacks via communication links. However, the existing literature lacks a comprehensive review and analysis of uncertainties in modern power systems, encompassing uncertainties related to weather events, cyber-attacks, and asset management, as well as the advantages and limitations of various mitigation approaches. To fill this void, this review covers a broad spectrum of uncertainties considering their impacts on the power system and explores conventional robust control as well as modern probabilistic and data-driven approaches for modeling and correlating the uncertainty events to the state of the grid for optimal decision making. This article also investigates the development of robust and scenario-based operations, control technologies for microgrids (MGs) and energy storage systems (ESSs), and demand-side frequency control ancillary service (D-FCAS) and reserve provision for frequency regulation to ensure a design of uncertainty-tolerance power system. This review delves into the trade-offs linked with the implementation of mitigation strategies, such as reliability, computational speed, and economic efficiency. It also explores how these strategies may influence the planning and operation of future power grids. [ABSTRACT FROM AUTHOR]

Recent events within the Australian National Electricity Market have demonstrated that the system of an energy-only market (a market that only compensates power that has been produced) is no longer fit for purpose. The rate of change in installed capacity and generation requires better planning to ensure reliability is maintained at the lowest total system cost during the transition to net zero. Australian National Electricity Market participants will need sufficient incentives and confidence to invest in new capacity. This paper assesses a "no constraints" scenario and recommends a range of policy and market mechanisms that could be utilized to achieve a net zero National Electricity Market in Australia by 2050. This paper adopts the perspective of total system cost, which allows multiple factors relating to decision-making to be incorporated. In the absence of a carbon price, this paper seeks to put forward technology-based policy and market mechanisms to incentivise the changes required. The "Modelling Energy and Grid Services" model used in this study has shown that this "no constraints" future grid will need to contain approximately 100 GW of variable renewable energy, almost 20 GW of firm, low-emissions generation, such as carbon capture, utilisation and storage, bioenergy with carbon capture and storage, hydroelectric power, or nuclear power. It will also require more than 10 GW of storage, including pumped hydro energy storage and other energy storage technologies, and over 30 GW of firm, dispatchable peaking plants, including thermal power generation. [ABSTRACT FROM AUTHOR]

The shift from large-scale centralised energy systems to smaller scale decentralised systems based on Distributed Energy Resources (DER) is likely to cause a sector-wide replacement of current electricity management practices and business models—creating a new energy paradigm. If handled well, such a transition will not be inherently disruptive; however, it can cause major disruption if long-held views and assumptions are not rapidly reconsidered and renewed, and new supporting structures are not swiftly put in place—hence, if disruption is experienced it will be due to a lack of strategic responses rather than the nature of the technology. This paper clarifies the nature of DERs and outlines key issues and opportunities associated with a range of associated service configurations and business models. The paper outlines key factors affecting the viability of such approaches and identifies leverage points for accelerating uptake. The paper concludes by considering how shifting landscape factors and related opportunities in the coming decades will shape the transition to a decentralised energy system. This paper contains findings from research performed at the Renewable, Affordable, Clean Energy Cooperative Research Centre (RACE CRC) in Australia. [ABSTRACT FROM AUTHOR]

A significant contribution to the reduction of carbon emissions will be enabled through the transition from a centralised fossil fuel system to a decentralised, renewable electricity system. However, due to the intermittent nature of renewable energy, storage is required to provide a suitable response to dynamic loads and manage the excess generated electricity with utilisation during periods of low generation. This paper investigates the use of stationary hydrogen-based energy storage systems for microgrids and distributed energy resource systems. An exploratory study was conducted in Australia based on a mixed methodology. Ten Australian industry experts were interviewed to determine use cases for hydrogen-based energy storage systems' requirements, barriers, methods, and recommendations. This study suggests that the current cost of the electrolyser, fuel cell, and storage medium, and the current low round-trip efficiency, are the main elements inhibiting hydrogen-based energy storage systems. Limited industry and practical experience are barriers to the implementation of hydrogen storage systems. Government support could help scale hydrogen-based energy storage systems among early adopters and enablers. Furthermore, collaboration and knowledge sharing could reduce risks, allowing the involvement of more stakeholders. Competition and innovation could ultimately reduce the costs, increasing the uptake of hydrogen storage systems. [ABSTRACT FROM AUTHOR]

This paper provides models for managing and investigating the power flow of a grid-connected solar photovoltaic (PV) system with an energy storage system (ESS) supplying the residential load. This paper presents a combination of models in forecasting solar PV power, forecasting load power, and determining battery capacity of the ESS, to improve the overall quality of the power flow management of a grid-connected solar PV system. Big data tools were used to formulate the solar PV power forecasting model and load power forecasting model, in which real historical solar electricity data of actual solar homes in Australia were used to improve the quality of the forecasting models. In addition, the time-of-use electricity pricing was also considered in managing the power flow, to provide the minimum cost of electricity from the grid to the residential load. The output of this model presents the power flow profiles, including the solar PV power, battery power, grid power, and load power of weekend and weekday in a summer season. The battery state-of-charge of the ESS was also presented. Therefore, this model may help power system engineers to investigate the power flow of each system of a grid-connected solar PV system and help in the management decision for the improvement of the overall quality of the power management of the system. [ABSTRACT FROM AUTHOR]

Synchronous generators are operating for less time than before or being decommissioned in the National Electricity Market (NEM) of Australia, due to the proliferation of asynchronous wind and solar generation. Sub-networks of the NEM will face inertia shortages in the near future. This paper develops a formulation of zonal inertia constrained generator dispatch for power systems with a diversified generator portfolio including synchronous generators, synchronous condensers, inverter-interfaced generators and energy storages. Zonal inertia constraints are formulated in unit commitment and optimal power flow to limit the rate of change of frequency (RoCoF) in the event of network separation. Load frequency relief is also considered to reduce the ramp rate requirement of primary reserve. The proposed formulation can reduce the average cost of primary reserve and maintain zonal inertia adequacy to constrain RoCoF in case of the trip of the interconnector(s). [ABSTRACT FROM AUTHOR]

Market and network integration of distributed energy resources can be facilitated by their coordination within a virtual power plant (VPP). However, VPP operation subject to network limits and different market and physical uncertainties is a challenging task. This paper introduces a framework that co-optimizes the VPP provision of multiple market (e.g., energy, reserve), system (e.g., fast frequency response, inertia, upstream reactive power), and local network (e.g., voltage support) services with the aim of maximizing its revenue. To ensure problem tractability, while accommodating the uncertain nature of market prices, local demand, and renewable output and while operating within local network constraints, the framework is broken down into three sequentially coordinated optimization problems. Specifically, a scenario-based robust optimization for day-ahead resource scheduling, with linearized power flows, and two receding horizon optimizations for close-to-real-time dispatch, with a more accurate second-order cone relaxation of the power flows. The results from a real Australian case study demonstrate how the framework enables effective deployment of VPP flexibility to maximize its multi-service value stack, within an uncertain operating environment, and within technical limits. [ABSTRACT FROM AUTHOR]

Deploying the cloud energy storage system (CESS) is an economic and efficient way to store excess photovoltaic generation and participate in demand response without personal investment on pricy energy storage equipment. It is a shared battery energy storage system (BESS) for local residential and small commercial consumers, which is designed and controlled by the CESS operator. Based on the profit purpose, the CESS operator not only pursues the most economic operating strategy, but also tries to minimize the total investment on the design stage. This paper considers the investment on the batteries, power conversion system, reactive power compensation equipment and the cost including battery degradation cost and operation cost. The electricity price uncertainty and the voltage deviation of the CESS node caused by power exchange are also considered. Moreover, the cases of a largely centralized energy storage system and multiple distributed energy storage systems are all modelled. Finally, an original robust cooptimization model is transferred to a mixed integer linear programming model (MILP) and solved in GAMS. Numerical results based on historical data from 300 residential consumers in Australia present that the battery degradation cost and price uncertainty can't be neglected. [ABSTRACT FROM AUTHOR]

This paper proposes a rule-based power management algorithm to enable the dispatch of a utility-scale PV power plant consisting of a hybrid energy storage system, in accordance with the Australian national electricity rules. This algorithm is purposely designed to regulate the instantaneous power of a PV plant with the same level of dispatchability as conventional power plants. Additionally, the proposed algorithm is robust under large forecasting errors (up to 60%) of solar irradiance and it can be easily implemented in practice. Specifically, this algorithm can be executed within seconds even when considering detailed market operation and model nonlinearities. A 30 MW PV plant, including a 7.5 MW/1.25 MWh vanadium redox battery and a 1.5 MW/0.25 MWh suppercapacitors bank, has been modeled using MATLAB/Simulink and PLECS software environment. The simulation results were based on various scenarios and confirmed the effectiveness of the proposed power management algorithm. It has been shown that even in the worst-case scenario of solar forecasting error of 60%, the proposed algorithm still managed to deliver over 94% of the available energy for a given solar irradiance profile of one month. [ABSTRACT FROM AUTHOR]

A high penetration of rooftop solar photovoltaic (PV) resources into low-voltage (LV) distribution networks creates reverse power-flow and voltage-rise problems. This generally occurs when the generation from PV resources substantially exceeds the load demand during high insolation period. This paper has investigated the solar PV impacts and developed a mitigation strategy by an effective use of distributed energy storage systems integrated with solar PV units in LV networks. The storage is used to consume surplus solar PV power locally during PV peak, and the stored energy is utilized in the evening for the peak-load support. A charging/discharging control strategy is developed taking into account the current state of charge (SoC) of the storage and the intended length of charging/discharging period to effectively utilize the available capacity of the storage. The proposed strategy can also mitigate the impact of sudden changes in PV output, due to unstable weather conditions, by putting the storage into a short-term discharge mode. The charging rate is adjusted dynamically to recover the charge drained during the short-term discharge to ensure that the level of SoC is as close to the desired SoC as possible. A comprehensive battery model is used to capture the realistic behavior of the distributed energy storage units in a distribution feeder. The proposed PV impact mitigation strategy is tested on a practical distribution network in Australia and validated through simulations. [ABSTRACT FROM PUBLISHER]

This paper investigates a comparative study for practical optimal sizing of rooftop solar photovoltaic (PV) and battery energy storage systems (BESSs) for grid-connected houses (GCHs) by considering flat and time-of-use (TOU) electricity rate options. Two system configurations, PV only and PV-BESS, were optimally sized by minimizing the net present cost of electricity for four options of electricity rates. A practical model was developed by considering grid constraints, daily supply of charge of electricity, salvation value and degradation of PV and BESS, actual annual data of load and solar, and current market price of components. A rule-based energy management system was examined for GCHs to control the power flow among PV, BESS, load, and grid. Various sensitivity analyses are presented to examine the impacts of grid constraint and electricity rates on the cost of electricity and the sizes of the components. Although the capacity optimization model is generally developed for any case study, a grid-connected house in Australia is considered as the case system in this paper. It is found that the TOU-Flat option for the PV-BESS configuration achieved the lowest NPC compared to other configuration and options. The optimal capacities of rooftop PV and BESS were obtained as 9 kW and 6 kWh, respectively, for the PV-BESS configuration with TOU-Flat according to two performance metrices: net present cost and cost of electricity. [ABSTRACT FROM AUTHOR]

Considering power quality problems such as overvoltage and three-phase unbalance caused by high permeability distributed photovoltaic access in low-voltage distribution networks, this paper proposes a comprehensive control scheme using a static var. generator (SVG), electric energy storage (EES), a phase switching device (PSD) and an intelligent terminal controller. The control strategies of transformer overload, bus over/under voltage, anti-countercurrent, storage battery state of charge (SOC) maintenance, and three-phase unbalance are studied. The engineering application in the Greenvale low-voltage distribution networks in Australia with high permeability distributed photovoltaics is discussed. The results show that the intelligent terminal controller is able to improve the power quality of low-voltage distribution networks through coordination with EES, SVG and PSD. [ABSTRACT FROM AUTHOR]

Although noteworthy efforts towards energy storage participation in electricity markets have been witnessed worldwide during the last decades, market mechanisms for optimal storage integration are yet to be comprehensively studied. This paper presents a novel approach wherein a multi-period look-ahead market is proposed to progressively solve the optimisation problem over a receding horizon, incorporating intertemporal constraints to enable forward planning. The focus is specifically on modelling the bidding behaviour of energy storage, and to address this, we develop two distinct models for the participation of energy storage in the market. The integrated model aims to schedule the future dispatch of the storage to minimise total operational cost, taking into account the fixed costs of the storage, while the strategic model pursues the dual ambition to maximise storage profit by formulating a bilevel optimisation problem. We validate the viability of our proposed market mechanisms through case studies on the Australian National Electricity Market. We conduct case studies which provide evidence that both the strategic and integrated bidding models effectively address the requirement for forward planning, resulting in reduced market costs and volatility. Notably, the strategic model outperforms in terms of generating higher storage revenue, while the integrated model exhibits a slight advantage in terms of lower market costs compared to the strategic model. • Development of a multi-period look-ahead market for storage integration in electricity markets. • Model of strategic bidding using a bilevel optimisation model, vs an integrated bidding model. • Both bidding models can fulfil need for forward planning, reducing market costs and volatility. • The strategic model increases storage revenue, while the integrated model reduces market costs. • Testing is carried out using a high-fidelity model of Australia's NEM and historical data. [ABSTRACT FROM AUTHOR]

• A PV variability tolerant multifunctional control strategy for BESS is proposed. • Four control functions of BESS with possible user-defined extensions were formulated. • A use-case to control PV plant's power ramp rate is demonstrated using real data. • Validation is performed in real-time software-in-loop platform using real-field data. • Evaluation of proposed strategy shows the potential for real-world deployment. This paper proposes a multifunctional control strategy for battery energy storage systems (BESSs) in solar photovoltaic (PV) plants to avoid the unacceptable PV-power ramp-rate caused by PV variability. In addition to the PV variability tolerant ramp-rate control, the proposed multifunctional BESS control strategy is capable of maintaining a user-specified charging profile to store excess PV power while providing backup power support and charge maintenance, by accommodating diverse control functions time to time. Four control functions, namely, Rest (RST), Surplus Energy Storage (STR), Back-up Power Support (SPT) and Charge Maintenance (CMT) functions, are proposed in this article. Besides, extendibility of the proposed multifunctional strategy is presented by adding two action strategies – one with the STR function and another with the SPT function. Validation of the proposed control strategy is conducted by using real historical data from a utility-scale solar PV plant located in Queensland, Australia. Numerical analyses show that the strategy can successfully keep the PV ramp-rate within specified limit along with the user specified charge profile. Further, exploiting the real-field data, the proposed strategy is demonstrated through a real-time co-simulation study conducted in a MATLAB interfaced RSCAD-RTDS platform that can be used as Digital Twin (DT) for the PV plant. [ABSTRACT FROM AUTHOR]

Australia has committed to reducing its greenhouse gas emissions in a manner consistent with limiting anthropogenic climate change to no more than 2 degrees Celsius. One of the ways in which this commitment is being realised is through a shift towards variable renewable energy (VRE) within Australia's National Electricity Market (NEM). Substituting existing dispatchable thermal plant with VRE requires consideration of long-term energy resource adequacy given the unpredictability of solar and wind resources. While pumped hydro and battery storage are key technologies for addressing short-term mismatches between resource availability and demand, they may be unable to cost effectively address 'energy droughts'. In this article, we present a time sequential solver model of the NEM and an optimal firming technology plant mix to allow the system to be supplied by 100% VRE. Our conclusion is that some form of fuel-based technology (most likely hydrogen) will probably be required. This has important implications for Australian energy policy. [ABSTRACT FROM AUTHOR]

Conventional fossil-fuel-based power systems are undergoing rapid transformation via the replacement of coal-fired generation with wind and solar farms. The stochastic and intermittent nature of such renewable sources demands alternative dispatchable technology capable of meeting system stability and reliability needs. Battery energy storage can play a crucial role in enabling the high uptake of wind and solar generation. However, battery life is very sensitive to the way battery energy storage systems (BESS) are operated. In this paper, we propose a framework to analyse battery operation in the Australian National Electricity Market (NEM) electricity spot and contingency reserve markets. We investigate battery operation in different states of Australia under various operating strategies. By considering battery degradation costs within the operating strategy, BESS can generate revenue from the energy market without significantly compromising battery life. Participating in contingency markets, batteries can substantially increase their revenue with almost no impact on battery health. Finally, when battery systems are introduced into highly volatile markets (such as South Australia) more aggressive cycling of batteries leads to accelerated battery aging, which may be justified by increased revenue. The findings also suggest that with falling replacement costs, the operation of battery energy systems can be adjusted, increasing immediate revenues and moving the battery end-of-life conditions closer. [ABSTRACT FROM AUTHOR]

This paper develops new practical rule-based energy management systems (EMSs) for typical grid-connected houses with solar photovoltaic (PV) and battery by considering different rates for purchasing and selling electricity. The EMSs are developed to supply the household's loads and reduce operating costs of the system based on different options of flat and time-of-use (ToU) rates for buying and selling electricity prices. Four different options are evaluated and compared in this study: (1) Flat-Flat, (2) ToU-Flat, (3) Flat-ToU, and (4) ToU-ToU. The operation cost is calculated based on the electricity exchange with the main grid, the equivalent cost of PV generation, as well as the degradation cost of battery storage. The operation of the grid-connected house with rooftop solar PV and battery is evaluated for a sunny week in summer and a cloudy week in winter to investigate the proper performance for high and low generations of PV. While the developed rule-based EMS are generic and can be applied for any case studies, a grid-connected house in Australia is examined. For this purpose, real data of solar radiation, air temperature, electricity consumption, and electricity rates are used. It is found that the ToU-Flat option has the lowest operating cost for the customers. [ABSTRACT FROM AUTHOR]

This paper provides a critical study of current Australian and leading international policies aimed at supporting electrical energy storage for stationary power applications with a focus on battery and hydrogen storage technologies. It demonstrates that global leaders such as Germany and the U.S. are actively taking steps to support energy storage technologies through policy and regulatory change. This is principally to integrate increasing amounts of intermittent renewable energy (wind and solar) that will be required to meet high renewable energy targets. The relevance of this to the Australian energy market is that whilst it is unique, it does have aspects in common with the energy markets of these global leaders. This includes regions of high concentrations of intermittent renewable energy (Texas and California) and high penetration rates of residential solar photovoltaics (PV) (Germany). Therefore, Australian policy makers have a good opportunity to observe what is working in an international context to support energy storage. These learnings can then be used to help shape future policy directions and guide Australia along the path to a sustainable energy future. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the details of a theoretical study of the economic advantages of using large-scale energy storage to complement a wind farm in a base-load dominated electricity grid. A computer model is developed which simulates the operation of several energy storage systems when used with the 190-MW Portland Wind Farm (PWF) located in Portland, Victoria, Australia. A variety of operating strategies are compared with the results of a dynamic programming model which finds the maximum possible revenue which a given system can generate for a set of input conditions. Three energy storage systems are modelled and costed: Pumped Seawater Hydro Storage (PSHS), Compressed Air Energy Storage (CAES), and Thermal Energy Storage (TES). It is found that CAES is the most profitable storage medium, requiring a capital expenditure of A$140M and generating a rate of return (ROR) of 15.4%. The ROR for PSHS was 9.6%, and for TES was 8.0%. Therefore, a significant investment opportunity exists for the installation of an energy storage system in this wind farm. It is therefore highly recommended that CAES is investigated further with the aim of introducing large-scale energy storage to PWF and other similar wind turbine installations. [Copyright &y& Elsevier]

Virtual power plants (VPPs) have become a driving force for the decentralized energy industry, due to their efficient management and control of distributed energy resources. Most of the operation strategies for VPPs are designed based on the day-ahead forecasts. However, the prediction errors of the renewable energy sources (RES) and loads in the power dispatch schedule can lead to a suboptimal operation. In this article, an adaptive and predictive energy management strategy for a real-time optimal operation of VPPs is proposed based on the model predictive control technique with a feedback correction (FC) to compensate for the prediction error. This strategy has two parts: 1) receding-horizon optimization (RHO), and 2) FC. In the first part, a hybrid prediction algorithm based on the integration of the time-series model and the Kalman filter is used to forecast the output powers of RES and the loads. Based on the prediction, the RHO model schedules the operation following the latest forecast information. In the second part, the receding schedule is adjusted based on the fast-rolling gray model's ultrashort-term error prediction. The FC is applied to minimize the adjustments for compensating the prediction error. The proposed strategy is implemented on a VPP in a real electricity distribution system in New South Wales, Australia. The simulation results demonstrate the effectiveness of the proposed strategy with a better tracking of the actual available resources and a minimal mismatch between demand and supply. [ABSTRACT FROM AUTHOR]

Many sharks and other marine taxa use natal areas to maximize survival of young, meaning such areas are often attributed conservation value. The use of natal areas is often linked to predator avoidance or food resources. However, energetic constraints that may influence dispersal of young and their use of natal areas are poorly understood. We combined swim-tunnel respirometry, calorimetry, lipid class analysis and a bioenergetics model to investigate how energy demands influence dispersal of young in a globally distributed shark. The school shark (a.k.a. soupfin, tope), Galeorhinus galeus , is Critically Endangered due to overfishing and is one of many sharks that use protected natal areas in Australia. Energy storage in neonate pups was limited by small livers, low overall lipid content and low levels of energy storage lipids (e.g. triacylglycerols) relative to adults, with energy stores sufficient to sustain routine demands for 1.3–4 days (mean ± SD: 2.4 ± 0.8 days). High levels of growth-associated structural lipids (e.g. phospholipids) and high energetic cost of growth suggested large investment in growth during residency in natal areas. Rapid growth (~40% in length) between birth in summer and dispersal in late autumn–winter likely increased survival by reducing predation and improving foraging ability. Delaying dispersal may allow prioritization of growth and may also provide energy savings through improved swimming efficiency and cooler ambient temperatures (daily ration was predicted to fall by around a third in winter). Neonate school sharks are therefore ill-equipped for large-scale dispersal and neonates recorded in the northwest of their Australian distribution are likely born locally, not at known south-eastern pupping areas. This suggests the existence of previously unrecorded school shark pupping areas. Integrated bioenergetic approaches as applied here may help to understand dispersal from natal areas in other taxa, such as teleost fishes, elasmobranchs and invertebrates. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a consideration of the role of battery energy storage in enhancing electricity grid stability at a time of increased use of non-hydro renewable generation sources, focusing on the Australian case. Besides the creation of a strategic reserve one measure that might reduce this instability that have being increasingly attracted much attention by both the operators of power systems and electricity distribution networks is the use of battery energy storage. Together, the multitude of regulatory and advisory bodies operating in and around the National Electricity Market of Australia (NEM), and the diverse and sometimes contrary opinions as to the best underlying foundational architecture for the NEM, overlaid by ongoing disagreement at the government policy level, point to continuing uncertainty and difficulties for an Australian electricity system in a state of transition. [ABSTRACT FROM AUTHOR]

This article determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) for grid-connected households to minimize the net present cost of electricity. The real-time rule-based home energy management systems using actual annual data of solar insolation, ambient temperature, household electricity consumption, and electricity rates are used in the optimization process. The above-mentioned technique is applied to two system configurations—household with a solar PV and a BES. The uncertainty analysis is implemented using ten years of real data to confirm the optimal results. An accurate cash flow analysis is also presented to illustrate the customer payment in each year during the project lifetime. The sensitivity analysis is conducted by varying the cost and capacity of system components, grid constraint, average daily electricity demand, and retail price of electricity. A typical grid-connected household in South Australia is considered as the case study. A practical guideline is presented for the residential consumers in South Australia to select the optimal PV/BES based on their daily average electricity demand and the available rooftop space for PV installation. Finally, the proposed optimization method is applied to households of other Australian States and a comparison of results is presented. [ABSTRACT FROM AUTHOR]

The energy transition for a net-zero future will require deep decarbonisation that hydrogen is uniquely positioned to facilitate. This technoeconomic study considers renewable hydrogen production, transmission and storage for energy networks using the National Electricity Market (NEM) region of Eastern Australia as a case study. Plausible growth projections are developed to meet domestic demands for gas out to 2040 based on industry commitments and scalable technology deployment. Analysis using the discounted cash flow technique is performed to determine possible levelised cost figures for key processes out to 2050. Variables include geographic limitations, growth rates and capacity factors to minimise abatement costs compared to business-as-usual natural gas forecasts. The study provides an optimistic outlook considering renewable power-to-X opportunities for blending, replacement and gas-to-power to show viable pathways for the gas transition to green hydrogen. Blending is achievable with modest (3%) green premiums this decade, and substitution for natural gas combustion in the long-term is likely to represent an abatement cost of AUD 18/tCO2-e including transmission and storage. [ABSTRACT FROM AUTHOR]