The impacts of climate change on the energy system are diverse; this article focuses on the potential effects on UK energy demand and the ramifications for national infrastructure building on the findings of the UK's 2012 Climate Change Risk Assessment. It reviews the available literature, where it exists, on the relationships among current energy demand, weather and climate change, and the implications for these relationships due to mitigation plans and potential adaptation responses. The review highlights the mechanisms by which future climate change, in particular changes in mean and extreme temperature, could affect the annual amount of UK energy demand and the seasonal, daily and spatial variation of the impacts. Published literature quantifying the effects of climate change on UK energy demand is limited; thus, where evidence is not available, information on the current relationship between weather and demand is combined with expert judgement to highlight potential demand responses to a changing climate without quantification. The impacts identified could have significant implications for the long-term planning of energy infrastructure and system operation and building design, depending on their magnitude, highlighting the need for further research in this area. (National Grid, 2014a). Historical relationships between economic growth and energy demand will likely be significantly altered by efforts to mitigate climate change as well as its inevitable impacts and our adaptation responses; thus, demand forecasters and those involved in infrastructure planning require an understanding of these ramifications for energy demand (McColl et al., 2012; National Grid, 2014a). Conor WalshParameters of demand considered here that are likely to be affected by climate change include (but are not limited to) the following: the size of annual energy demand, the size and timing of peak demand, the spatial distribution of demand and the sector affected (Chandramowli and Felder, 2014; ENA, 2011; National Grid, 2014a, 2014b, 2014c. These parameters of demand are among those considered when planning and managing energy infrastructure. The sizes of annual energy demand and peak demand influence the amount of supply and /or storage required, for example, the available capacity of electricity supply or the amount of gas and oil stored in the UK at any given time. The timing of peak demand influences planned maintenance and construction schedules and supply planning (ENA, 2011; National Grid, 2014b, 2014c. The regional distribution of demand influences the logistics of supply, including the topology and capacity of the electricity transmission and gas distribution networks (National Grid, 2014b, 2014c. In the case of electricity, the change in demand in urban against rural areas influences the effects seen by distribution network operators due to other confounding factors such as the urban heat island effect and the differences in network configuration (networked or radial) that service these areas (ENA, 2011). Finally, the s...
Background Bioenergy is a significant contributor to renewable power generation, renewable transport fuel and renewable heat. However, the deployed capacity significantly lags identified potential and has not seen the same rapid response to policy stimuli observed in the solar and wind sectors. This work analyses the historical trajectory of UK bioenergy development to discern potential underpinning reasons for that.Results It is noted that the technology landscape is arguably more complex than in other renewables, with multiple feedstocks, pre-treatment and conversion technologies involved in potentially hundreds of different pathways/combinations; not all of these pathways/combinations deliver greenhouse gas reductions, and most have other impacts (positive and negative) that go beyond energy and greenhouse gas balances to interact with atmospheric, aquatic, land, economic and social systems. We apply a risk management approach to show how disaggregation of the system can support more appropriate decision-making and provide greater resilience to the inherent variability associated with natural, land-based systems.Conclusions It is concluded that disaggregation of bioenergy systems into 3 sub-systems allows management of the most significant risks to be placed with the parties most able to deal with them and that a simple, semi-quantitative assessment of the performance of each sub-system facilitates an effective ranking of the “best” use of biomass in line with policy objectives; supporting effective decision making about priority feedstocks, technologies and demand sectors.
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