PROJECT TITLE :

Evaluation of the Levelized Cost of Energy Method for Analyzing Renewable Energy Systems: A Case Study of System Equivalency Crossover Points Under Varying Analysis Assumptions

ABSTRACT:

A modified levelized price of energy (LCOE) model was created to see the economic crossover point (measured in $hskip1ptssr C hskip-7pt raise2.4pt hbox$buildrelvrule depth0.5pt width5.5pt overvrule depth0.5pt width5pt$hskip2pt/hboxbarrel $ of oil) between a traditional diesel power-generating facility and a hybrid closed-loop wind–hydro energy system on the island of El Hierro. This island represents the first system-of-systems coupled wind and pumped-storage hydroelectric facility in the world aimed toward achieving energy independence for an island. LCOE models were developed using mounted baseline oil costs of thirty, forty, and fifty $hskip1ptssr C hskip-7pt raise2.4pt hbox$buildrelvrule depth0.5pt width5.5pt overvrule depth0.5pt width5pt$hskip2pt/hboxbarrel $, that is the price range when the construction project was undertaken. The proportion change of the Spanish shopper value index and industrial worth index were used to assess the result of fixing oil prices on the LCOE. This paper concerned on-website investigation of the technical and financial parts of the project and resulted in an LCOE model that features investment, operation and maintenance, emissions, and land prices. Sensitivity analyses were administrated at varying inflation and discount rates. Results indicate that the economic crossover point between the energy production systems to be below the current world oil value and inside the range of prices when the project was initiated. Increasing inflation rates reduces the crossover purpose by increasing future costs associated with the diesel system, and increasing discount rates raises the crossover point by discounting future prices related to diesel fuel expense. Under constant dollar analysis, the LCEO model robustly highlights system equivalency p- ints; however, the inclusion of discount rate challenges this robustness by introducing the potential for gaming the analysis in favor of one technology over another.


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