Sectoral disaggregation.

Sectoral disaggregation.

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Article
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Using a purpose-built, multi-sectoral energy-economy-environmental model we evaluate the economic and environmental impact of a reduction in the levelized costs of offshore wind energy generation in the UK. Our modelling approach suggests that in order to significantly increase the offshore wind capacity in the UK the required fall in the generatio...

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Context 1
... model is a flexible framework that allows for a range of model closures, functional forms and key parameter values. The model has 25 industry sectors, detailed in Table 1, of which thirteen are energy sectors. Among energy sectors, we identify nine electricity generation sectors. ...
Context 2
... initial database used to calibrate the model is a Social Accounting Matrix (SAM) for the UK in 2010. This is based upon the UK symmetric Input-Output (IO) Table derived from the UK Supply and Use Table (ONS, 2014) together with data from income account (ONS, 2014). The UK income account is used to create the income-expenditure accounts for households, government, corporations, capital and external sectors and therefore complete the SAM, which is central to the construction of the baseline database. ...
Context 3
... the vertical axis, we show the levelised cost in £ per MWh and on the Table 2 Projected levelised costs of offshore wind. 2014 2030 High 189 135 Central 163 115 Low 144 100 Source: DECC (2013c) Electricity Generation Costs (levelised costs with technology specific hurdle rates, p.25). ...

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... Although there are no subsidies for offshore wind-power plants at the time of this study, the Italian government is considering introducing subsidies. Three events were thus considered, namely feed-in tariff (F), with a fixed sold price for produced energy of 187 EUR/MWh, set according to the historical levelised cost of energy of offshore windpower systems [78]; feed-in premium tariff (P), with an increment in the hourly energy price of 31 EUR/MWh; and no subsidies (-). ...
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Wind-energy systems are strongly affected by uncertainty and variability. Therefore, uncertainty sources should be considered during the economic evaluation of this type of system. In the literature, a framework for the economic performance assessment of wind-power systems has been proposed. Furthermore, in another contribution, the random discontinuities of political and regulatory scenarios have been included by using scenario analysis. However, the implemented models neglected the uncertainty related to disruptive events and the effect of climate change on the wind resource. To fill this gap, in this paper, climate change and disruptive events are included in a new model for evaluating the economic performance of wind turbine systems using scenario analysis. Analysis of a numerical example has been carried out to show the framework’s capabilities and to evaluate the effects of the added issues. The main results confirm previous findings on the necessity of including regulatory and political risks to achieve a proper economic evaluation. Additionally, they show that disruptive events increase the variability of the expected value of the Net Present Value (NPV). Therefore, even though climate change is expected to increase wind producibility in the numerical example location, the inclusion of disruptive events constrains the NPV growth.
... Three scenarios are thus considered, namely feed in tariff (F), feed in premium tariff (P), and no subsidies (N). Due to the lack of data, feed in tariff was set at 187 €/MWh, according to the historical levelized cost of energy for offshore wind power systems (Lecca et al., 2017). In this scenario, the time series of electricity price has no influence on NPV, because the power produced is sold at a fixed price. ...
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The technical and economic performance of renewable energy systems is affected by the uncertainty and variability of many influencing factors, including the inherent uncertainty in the availability of energy sources and the economic context, as well as equipment availability. Traditional design and evaluation methods are based on the assumption of average nominal values of design parameters. This prevents technical and economic risk assessment, which is a central issue in the proper design of these systems. Software tools and some contributions on this topic are available in the literature, but only a few sources of uncertainty are considered. In a previous work, a framework for evaluating the economic performance of offshore wind power systems considering the main sources of uncertainty was proposed, but the implemented model neglected the uncertainty related to changes in the political and regulatory scenario during system life. To fill this gap, in this paper, the random discontinuities arising from this kind of risk are included in a new economic performance assessment model using scenario analysis. Widely accepted scenarios for energy price, learning rate and subsidies were taken from the literature and combined into consistent stories for the life of the plant. Simulations were carried out in a case study. The main results show the crucial role of this type of uncertainty in a correct economic risk assessment in wind power systems. From the best-case scenario to the worst-case scenario, there is a difference of about 290% in the expected value of NPV. In addition, several scenarios were combined to assess a single net present value distribution using their associated probability. Several scenarios for increasing or decreasing subsidies were defined, and an example was carried out. Considering a constant value of subsidies, instead of combining different plausible stories, led to an overestimation of NPV of about 160%.
... The North Sea is a highly suitable location for OWFs, accounting for 77% of the total OWF installed capacity in Europe (WindEurope, 2019). There is therefore a huge potential for large-scale OWFs to assist in achieving Scotland's energy goals and to benefit the economy by stimulating investment, employment and local content (Allan et al., 2008;Graziano et al., 2017;Lecca et al., 2017;McNeil et al., 2013). Whilst Scotland was slow to extend its installed capacity after the first operational commercial OWF in 2010, since 2017 this has rapidly expanded with the Scottish Government consenting to a further 4.1 GW of projects and construction expected in the early 2020s. ...
... As the basic model, one-factor learning curve model depicts the decline of unit investment cost of renewable energy power along with the growth of cumulative installed capacity or electricity generation (Zou et al., 2017;Tu et al., 2019b). In recent years, with the expansion of global offshore wind power, many scholars have begun to estimate the learning rate of offshore wind power by using learning curve model (Sarker & Faiz, 2017;Lecca et al., 2017). As shown the existing researches in Table 1, offshore wind power has presented different development trends in different periods. ...
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... Concerning the costs, in Section 2 an extensive assessment at 2030 was reported. In this section, the economic benefits beyond 2060, such as long-term progressive decrease of costs and weighted average cost of capital (WACC) due to the learning curve, and reaching large diffusion of floating wind technology, are considered [26]. ...
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... The CGE model has been applied to assess the wider macroeconomic impacts of marine renewables (e.g. Allan et al., 2014;Cohen and Caron, 2018;Dalton et al., 2016;Graziano et al., 2017;Lecca et al., 2017), but no particular attention has been paid to sectoral impacts on seafood productions. Meanwhile, the CGE model has also been applied to analyse the impacts of regional fishery policies on seafood production (e.g. ...
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The rapid development of offshore wind farms (OWFs) has stimulated debate about its overall socioeconomic impacts. Expanding the scale of OWFs increases the availability and affordability of electricity but could displace existing fishing activities and reduce food supply. To evaluate these impacts from a macroeconomic perspective, a computable general equilibrium (CGE) model is developed, using Scotland as a case study. A particular focus is placed on the disaggregated electricity and seafood sectors, their interconnectedness from an energy-food nexus perspective, and the distributional effects across household groups. This paper explores, from macroeconomic perspective, the trade-offs in the energy-food nexus between expanding OWFs and the seafood sectors, together with the impacts on food and energy security. The results suggest that, through economic linkages, increasing the number of OWFs would have a negative, but limited, effect on seafood production sectors. However, the falling cost of electricity from OWFs would have a positive impact on the economy overall and benefit lower income households, contributing to a reduction in fuel poverty. The model results raise the awareness of nexus linkages between OWFs and seafood production and are applicable to policies involving the development of other offshore renewables.
... Of course, in practice these will operate in combination with other policies, including those designed to encourage substitution of renewables in electricity production. We have explored the impact of the introduction of renewable technologies in, for example, Allan et al. (2008) and Lecca et al. (2017). ...
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... The literature on renewable energy economics has focused on the sub- stitution between fossil fuel input and renewable energy sources (e.g., Gerlagh and van der Zwaan, 2004;Lazkano et al., 2017;Lecca et al., 2017;Popp, 2006;Papageorgiou et al., 2017). ...
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... Mu et al. [12] have conducted a recent global review of employment effects of renewable energy deployment. The policy intentions that we examine can be constrained by the fractured roll-out of 'almost mature' technologies [13], the failure to achieve the expected rates of technological learning [14] and the socio-political realities that increasing scale in technology deployment must be lockstepped with the social and political agency that is willing to maintain the course [15]. Furthermore, most energy transition studies and policies do not accept the reality of "actors behaving badly" [16] nor the reality that highly effective and efficient deployments may stimulate inter-sectoral rebound either domestically or abroad where physical growth in downstream sectors uses more energy and possibly gives higher emissions from non-electric fuels [17]. ...
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The UK has an ambitious target of an 80% reduction in carbon dioxide emissions by 2050, to be reached using a series of 'carbon budgets' to aid policy development. Current energy systems modelling methods do not explore, or are unable to account for, physical (thermodynamic) limits to the rate of change of infrastructure. The power generation sector has a variety of technological options for this low-carbon transition. We compare physically constrained scenarios that accentuate either carbon capture and storage, fastest plausible nuclear new build, or fastest plausible build rate of offshore wind. We set these in the context of the UK's legislated fifth carbon budget, which has a comprehensive range of carbon reduction measures with respect to business-as-usual. The framework for our scenario comparison uses our novel system dynamics model to substantiate the policy's ability to meet 2035 emissions targets while maintaining financial productivity and socially expected employment levels. For an ambitious nuclear new build programme we find that even if it stays on track it is more expensive than offshore wind generation and delays emissions reductions. This affects the cumulative emissions and impacts on the UK's ability to contribute to international climate change targets. If delays or cancellation occur to the deployment programmes of carbon capture and storage technologies or nuclear new build, we suggest the electricity and decarbonisation targets can by met by a fast growth of offshore wind generation with no change to financial and employment levels.
... The CGE model has been applied to assess the wider macroeconomic impacts of marine renewables (e.g. Allan et al., 2014;Cohen and Caron, 2018;Dalton et al., 2016;Graziano et al., 2017;Lecca et al., 2017), but no particular attention has been paid to sectoral impacts on seafood productions. Meanwhile, the CGE model has also been applied to analyse the impacts of regional fishery policies on seafood production (e.g. ...
Conference Paper
Rapid development of offshore wind energy industry in recent years has raised increasing concerns about its socioeconomic impacts on the overall economy. On one side, the expanding scale of offshore wind farms would cause conflicts and tradeoffs with existing fishing industries in the marine environment, resulting in higher fishing effort and thus reduced fish supply. On the other side, the falling cost of offshore wind farms would result in opposite impacts on the economy. To evaluate these concerns in a macroeconomic way, a computable general equilibrium model for Scotland is developed to evaluate the macroeconomic impacts of the developing offshore wind farms. Particular focuses are put on the corresponding electricity and seafood sectors and their nexus approach between them, and the distributional effects across the different household groups. The modelling approach suggests that the increased number of offshore wind farms has limited negative effect on seafood production sectors. Meanwhile, the falling cost of offshore wind farms would have be positive to the economy in general and would be benefited to especially lower income households and mitigate the fuel poverty to them.