Different Geothermal Power Cycle Configurations Cost Estimation Models

Moein Shamoushaki,Pouriya H Niknam,Daniele Fiaschi,Lorenzo Talluri,Giampaolo Manfrida

doi:10.3390/su132011133

Abstract

An economic assessment of different geothermal power cycle configurations to generate cost models is conducted in this study. The thermodynamic and exergoeconomic modeling of the cycles is performed in MATLAB coupled to Refprop. The models were derived based on robust multivariable regression to minimize the residuals by using the genetic algorithm. The cross-validation approach is applied to determine a dataset to examine the model in the training phase for validation and reduce the overfitting problem. The generated cost models are the total cost rate, the plant’s total cost, and power generation cost. The cost models and the relevant coefficients are generated based on the most compatibilities and lower error. The results showed that one of the most influential factors on the ORC cycle is the working fluid type, which significantly affects the final economic results. Other parameters that considerably impact economic models results, of all configurations, are geothermal fluid pressure and temperature and inlet pressure of turbine. Rising the geothermal fluid mass flow rate has a remarkable impact on cost models as the capacity and size of equipment increases. The generated cost models in this study can estimate the mentioned cost parameters with an acceptable deviation and provide a fast way to predict the total cost of the power plants.

Highlights

In the cost estimation process, there may generally be some uncertainties that can affect the decision of industries
Has tried been tried ficientscients to reduce the errors, the most correlation is obtained. It hasItbeen to generate thereliable most reliable cost models according to the available cost results; to generate the most cost models according to the available cost results; the deviation in different models and parameters is different
Among considered cost parameters, power generation cost had the highest deviation, forcycles, ORC cycles, these deviation is higher than cycles

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. One of the most vital parts of designing a power plant is determining the execution of the project. The cost estimation of a project defines whether the stakeholders and industries progress with the project. Power plant cost estimating is one of the most critical steps in project management. A cost assessment builds the baseline of the project cost at diverse stages of the project’s development. A cost estimation at a particular step of project development expresses a prediction based on available data. In the cost estimation process, there may generally be some uncertainties that can affect the decision of industries

Methods

Results

Discussion

Conclusion