Search

This paper evaluates the economic feasibility of SPCC (solar-assisted post-combustion carbon capture) at a coal power plant near Sydney, Townsville and Melbourne for implementation in 2020. A review of Australia's carbon and renewable energy policy is performed first, after which the merits of application of each incentive for SPCC are compared. Incentives such as subsidies, preferential discount rate, carbon tax and RECs (renewable energy certificates) are evaluated. No single incentive on its own, and within reasonable limits, is able to provide a favourable economic performance for power plant based renewable powered CCS (carbon capture and storage). However, once the compounded effect of carbon tax and electricity price increase is taken into account, a carbon price as low as A$ 25/tonne-CO 2 and a REC price as low as A$ 35/MWh e is able to produce a positive net benefit in Townsville, while a slightly higher carbon price and REC price is required for Sydney. Melbourne performs poorest amongst the three locations, where substantially higher incentives would be needed for economic feasibility. The level of incentives required for SPCC to become feasible are found to fall in the range of current Australian policy incentives accessible to renewable energy technologies for stand-alone power generation. [ABSTRACT FROM AUTHOR]

The Asia-Pacific has experienced prodigious growth in energy use and is by far the world's largest greenhouse-gas emitting region. Australia has played a leading role in meeting the region's energy and resource needs, becoming the world's largest exporter of coal, liquefied natural gas, iron ore, and alumina. Our analysis shows that these exports are tied to sizeable consequential emissions at the point of use or processing, accounting for about 8.6% of the total greenhouse gas emissions of the Asia-Pacific. The paper investigates three pathways by which Australia could instead export zero-carbon energy and products: direct exports of renewable electricity via sub-sea cables, exports of zero-carbon fuels such as green hydrogen, and the export of "green" metals processed from Australian ores using renewable energy. Carrying out robust, high-level calculations we find that Australia has the land and renewable energy resources to become a key exporter of these commodities. Realization of this potential relies on ongoing cost reductions, growing demand-side interest linked to meeting ambitious emission reduction targets in the region, and the development of cross-border frameworks for clean energy trade. If it were to achieve this goal, Australia could make a sizeable contribution to regional decarbonization via renewable-energy based exports. • Consequential emissions from existing key Australian exports are estimated. • The potential for replacement zero-carbon exports from Australia is analyzed. • Land, water, and energy requirements for new zero-carbon exports are calculated. • There is the potential to reduce Asia-Pacific greenhouse gas emissions by about 8.6%. • Around 2% of Australia's land mass would be required for solar and wind farms. [ABSTRACT FROM AUTHOR]

Abstract Coal plays a key role in China's economy as a dominant primary energy resource. In this paper, we provide probability density forecasts for weekly steam coal prices in China based on daily factors such as renewable energy source, Daqing oil, Japanese natural gas, Australia steam coal prices, coal mining industry index, A-share power sector index, A-share index, coal industry index, and temperature. The empirical results show that the influence of temperature lasts longer than other factors, while the Australia steam coal prices, renewable energy source and A-share index are the three best predictors for steam coal prices. It is also shown that the high-frequency factors are useful to forecast steam coal prices and that considering the nonlinearity of coal prices can improve the forecast accuracy by about 22%. We further provide the probability density forecasts for steam coal prices based on the influence of all the selected factors, the results suggest that our proposed method can provide accurate and satisfying probability density forecasts. Given these results, the policy-makers can make effective strategies which can not only adjust the energy structure but also ensure economic growth. • High-frequency factors are useful to forecast coal prices. • C-MIDAS-X model considers the high-frequency factors and the nonlinearity of coal prices. • The probability density forecasts are satisfying. [ABSTRACT FROM AUTHOR]

This study aims to analyse whether the Australian commitment to the Paris Agreement in 2016 and national energy policies will have a visible effect in decreasing the historical dependence of the NEM (National Electricity Market) on fossil fuels by 2030 and consequently decreasing the carbon emissions generated. In this paper, we model the 2030 electricity mix in the NEM in Australia. EnergyPlan , which is the modelling tool adopted for this study, is described and a reference model is conceived and calibrated based on the 2018 electricity situation on the NEM. The simulations are implemented considering three different supply scenarios and three potential electricity demands, to evaluate how different variables can influence the NEM electricity mix by 2030. This study concludes that by 2030 wind and solar power (including rooftop-PV systems) will be the major renewable energy contributors in the NEM, as opposed to 2018 where hydropower represented the main renewable energy source. Nonetheless, the electricity system in 2030 will continue to rely on fossil fuels, which will account for more than 50% of the final energy mix in every scenario, depicting that new efforts will still be needed beyond 2030. • We foresee the electricity mix in Australia by 2030. • We study three generation and three demand scenarios. • Fossil fuels will still account for more than 50% of the final electricity mix. • We expect a visible CO2 emissions reduction, due to the bet in RES in recent years. [ABSTRACT FROM AUTHOR]

Challenging frequency control issues, such as the reliability and security of the power system, arise when increasing penetration levels of inverter-interfaced generation are imposed. As a result of the displacement of convention generation in favour of renewable energy sources, the reduction of frequency response capabilities can be seen. A promising method of overcoming the aforementioned challenges is to utilise Battery Energy Storage Systems (BESS), which provides frequency support by injecting instantaneous power to the grid and back up the conventional generation systems. However, large battery systems increase the cost while inadequate battery capacities result in poor performance. This paper, therefore, proposes an approach for finding the optimum BESS size for an islanded microgrid power system. The determination of the optimum BESS size is based on an existing case study, under which the most severe contingencies of generation loss and load loss have been accounted for, as well as different levels of penetration of renewable energy sources. As a result of using meta-heuristic optimization (Grey Wolf Optimization), the constraint optimization problem has been identified as BESS sizing. Through the use of real-time simulation DIgSILENT PowerFactory software, estimated BESS size can be applied to a standalone microgrid to test the frequency of support capabilities. The simulation has made it apparent that through the selection of the optimum BESS size, the system frequency response is not only mitigated, but improved. • Proposing a novel optimization model for determining the optimal size of the battery devices of standalone microgrids. • Propose an intelligent approach to mitigate the frequency response of standalone microgrids based on hybridization sources. • Combining the advantages of the BESS controller and the meta-heuristic Grey Wolf Optimizer (GWO) algorithm. • Validate the system performance based on a real case study under different scenarios. [ABSTRACT FROM AUTHOR]