The provision of energy services is a vital component of the energy system. This is
often considered emission-intensive and at same time, highly vulnerable to climate
change conditions. This forms the fundamental objective of this thesis, poised to examine technoeconomic and environmental implications of policy intervention, targeted at cushioning impacts of climate change on the energy system.
Four research queries are central to this work: (1) Review literature on impacts
of CV&C on the energy system; (2) Estimate influence of seasonal climatic and
socioeconomic factors on energy demand in Australia; (3) Model dynamic interactions
between energy policies and climate variability and change (CV&C) impacts on the energy
system in Australia and exploring the technoeconomic and environmental implications;
and (4) Identify least-cost combination of electricity generation technologies and
effective emissions reduction policies under climate change conditions in Australia.
A systematic scoping review method was first applied to identify consistent
pattern of CV&C impacts on the energy system, while spotting research gaps in studies
that met the inclusion criteria. Databases consisting of Scopus and Web of Science were
searched, and snowballing references in published studies was adopted. Data was
collated and summarised to identify the characteristic features of the studies, consistent
pattern of CV&C impacts, and locate research gaps to be filled by this study.
The second study applied an autoregressive distributed lag (ARDL) model to estimate temperature sensitive electricity demand in Australia. Estimates were used with
projected temperatures from global climate models (GCMs) to simulate future electricity
demand under climate change scenarios. The study further accounted for uncertainties
in electricity demand forecasting under climate change conditions, in relation to energy
efficiency improvement, renewable energy adoption and electricity price volatility. The
estimates from the ARDL model and projections from GCMs were used for energy system
simulation using the Long-range Energy Alternative and Planning (LEAP) system. It considered climate induced energy demand in the residential and commercial sector,
alongside linking the non-climate sensitive sector with energy supply sector. This model
was vital to justifying policy options under investigation. Further, LEAP modelling analysis was extended by identifying effective emission reduction policies considering CV&C impacts. Here, the Open Source Energy Modelling System (OSeMOSYS) was used for optimisation analysis to identify least-cost combination of electricity generation technologies and GHG emission reduction policies. Whereas, in the third and final study, cost-benefit analysis and estimation of long run marginal cost of electricity were conducted, while decomposition analysis of GHGs were analysed in the third study alone. Data used in the ARDL model included socioeconomic data which includes gross state product, as well as population and electricity prices from 1990-2016. The LEAP and OSeMOSYS model as used, was dated to 2014 as the base year, while several technological (power plant characteristics, household technologies), economic (energy prices, economic growth, carbon price) and environmental (emission factors, emission reduction target) variables were used to develop Australia’s energy model.
The literature search generated 5,062 articles in which 176 studies met the
inclusion criteria for the final literature review. Australian studies were scarce compared
to other developed countries. Also, just few articles made attempt to examine
decarbonisation under climate change. The ARDL model estimates and GCMs simulation
of future electricity demand under CV&C show that Australia had an upward sloping
climate-response functions, resulting to an increase in electricity demand. However, the
researcher identified an annual increase in projected electricity demand for states and
territory in Australia, which calls for the need to scale up RET.
The LEAP model results showed substantial impacts on energy demand, as well as
impacts on power sector efficiency. Under the BAU scenario, CV&C will result in an
increase in energy demand by 72 PJ and 150 PJ in the residential and commercial sectors,
respectively. Induced temperature enlarges the non-climate BAU demand, which will
increase threefold before 2050. Under the non-climate BAU, there is an expansion of
installed capacity to 81.8 GW generating 524.6 TWh. Due to CV&C impacts, power output declines by 59 TWh and 157 TWh in Representative Concentration Pathways (RCP) 4.5
and 8.5 climate scenarios. This leads to an increase in generation costs by 10% from the
base year, but a decrease in sales revenue by 8% and 21% in RCP 4.5 and RCP 8.5,
respectively. The LEAP-OSeMOSYS model suggests renewables and battery storage
systems as least-cost option. However, the configuration varied across Australia. Carbon
tax policy was observed to be effective in reducing Australia’s emission and foster huge
economic benefits when compared to the current emission reduction target policy in the
country. Also, renewable energy technologies increase electricity sales and decrease fuel
cost better than fossil fuel dominated scenarios.
Data from this study reveals that seasonal electricity demand in Australia will be
influenced by warmer temperatures. Also, the study identified the possibility of winter
peaking which is somewhat higher than summer peak demand in some states located in
the southern regions of Australia. However, winter peaking is projected to decline by midcentury across the RCPs, while summer peak load is projected to increase, thereby,
causing power companies to expand their generation capacity which may become
underutilised. Owing to increase in cooling requirements up to 2050, policy uncertainties
analysis recommend renewables to match an increasing future electricity demand.
The energy model indicates that ignoring the influence of CV&C may result in
severe economic implications which range from increased demand, higher fuel cost, loss
in revenue from decreased power output, as well as increased environmental
externalities. The study concludes that policy options to reduce energy demand and GHG
emissions under climate change may be expensive on the short-run, though, may likely
secure long-run benefits in cost savings and emission reductions. It is envisaged that this
could provide power sector management with initiatives that could be used to overcome
cost ineffectiveness of short-term cost. The modelling results makes a case for renewable energy in Australia as lower demand for energy and increased electricity generation from renewable energy source presents a win-win case for Australia.