کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7256092 1472396 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Grid parity in tidal stream energy projects: An assessment of financial, technological and economic LCOE input parameters
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
پیش نمایش صفحه اول مقاله
Grid parity in tidal stream energy projects: An assessment of financial, technological and economic LCOE input parameters
چکیده انگلیسی
Assessments in electricity production technologies are usually supported by a levelised cost of energy (LCOE) analysis. Such cost analyses are riddled with uncertainty, with LCOE values depending on a number of financial, technical and economic variables. When it comes to minimising LCOE, the question arises as to which parameters have a greater bearing - especially if the current grid parity gap between tidal stream energy and conventional sources is to be narrowed. The aim of this study is to investigate the independent effects of the input variables on LCOE values, in order to determine the main drivers in closing the grid parity gap between tidal stream energy costs and traditional grid-power costs. The assessment features six tidal stream farms, in which different numbers of turbines, rows and spacing are considered. Not only are the device interactions of each configuration considered (by means of numerical modelling) but also the impacts of the financial and economic variables. In addition to individual variable sensitivity, a multivariable scenario analysis estimates the combined effect on the projected LCOE of varying an entire set of inputs simultaneously. As a result, it is found that the power coefficient is one of the inputs with the greatest bearing on the LCOE, closely followed by the discount rate and the capital costs (CAPEX). On this basis, a LCOE best-case scenario is constructed, which characterises tidal stream energy projects in terms of economic viability over a variety of conditions in four countries.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Technological Forecasting and Social Change - Volume 104, March 2016, Pages 89-101
نویسندگان
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