Around the world, government policies to support new renewable energy technologies rely on accurate estimates of Levelised Cost of Energy (LCOE). This paper reveals that such estimates are based on "public domain" data which may be unreliable. A new approach and methodology has been developed which uses United Kingdom (UK) "audited" data, published in company accounts that has been obtained from Companies House, to determine more accurate LCOE estimates. The methodology is applicable to projects configured within Special Purpose Vehicle (SPV) companies. The methodology is then applied to a number of UK offshore wind farms and one Combined Cycle Gas Turbine (CCGT) project, with cost data then compared to that presently in the public domain. The analysis reveals that recent offshore wind projects show a slightly declining LCOE and that public domain cost estimates are unreliable. But of most concern is that offshore wind farm costs are still much higher than those implied by recent bids for UK government financial support via Contracts for Difference (CfDs). The paper concludes by addressing further the question of how offshore wind projects can achieve the degree of LCOE reductions required by recent CfD bids.
Policymakers increasingly need to balance the requirements of energy demand, security and costs: they need accurate estimates of performance. This paper uses public data to assess UK offshore wind farm performance to improve policy decisions. It finds that average capacity factors have improved from 34.9% in Round 1 to 41.0% in Round 2 projects. Drivers for performance are examined and the correlations in performance between UK offshore wind farms analysed. The paper also addresses problems with existing capacity factor estimates and generates new estimates of inter-year variability of capacity factor, providing a more accurate evidence base for policy decisions.
Technological Innovation Systems theory, and its “functions” framework, have demonstrated their value as tools for exploring socio-technological transitions. Although the “seven functions” model has demonstrated its academic value across a vast literature, there have been few attempts to explore the model through the lens of industry stakeholder opinion. We believe that involving a relevant stakeholder group offers the potential for validating this approach, and even potentially enriching it. This research aims to address that shortfall. In 32 interviews with senior participants in the UK offshore wind, tidal stream and wave sectors and associated supply chain, policy makers, support organisations and other stakeholders, the validity of the seven well-established “Hekkert” functions was tested. The research found that the interviewees confirmed that all seven functions were necessary in characterising the emergence of the focal technologies, and analysis of the interviews allowed the definition and scope of each function to be enriched. The research also found that an additional function—defined as “Demonstrating Value”—was helpful in providing a more complete description of technology emergence. This function is defined and appropriate metrics for it are discussed. The authors suggest that this proposed enrichment of the “functions” model may provide a greater understanding of socio-technological transitions in the face of volatile external contextual factors, whose importance the current COVID pandemic has made all too obvious.
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