Abstract

Many existing financial models for power plants chose a design based on the maximum thermal efficiency excluding the operational (OPEX) and capital (CAPEX) cost variations of technical factors. These factors are often fixed because including them in financial assessments can be burdensome and it is assumed that maximum efficiency equals maximum profit. However, this assumption may not always be right. Through 19,440 power plant steam-cycle design solutions and their associated OPEX and CAPEX, this study found the eighth most thermally-efficient solution to be $1.284 M more profitable than the traditional thermally-optimized design solution. As such, this paper presents a model incorporating technical factors through parametric estimation by minimizing the burden on decision makers. While this may reduce precision, it allows for quick cost assessments across differing design solutions. The data for model development was collected from a Korean-constructed, operational 600 MW coal-fired power plant in the Philippines. Using the Thermoflex software, nearly all design configurations’ heat rate outputs are simulated. Profitability is then optimized based on the resultant design configuration’s impact on revenue and CAPEX and OPEX costs. The simulation inputs included variables found to be most impactful on the steam generated power efficiency per existing literature. Lastly, the model includes an assessment of cost impacts among recent environmental regulations by incorporating carbon tax costs and a sensitivity analysis. The economic analysis model discussed in this paper is non-existent in current literature and will aid the power-plant project investment industry through their project feasibility analyses.

Highlights

  • IntroductionElectricity demand is steadily increasing globally as the world develops and technology advances

  • Electricity demand is steadily increasing globally as the world develops and technology advances.This increase in demand is not unique to any one country

  • The economic analysis model discussed in this paper is non-existent in current literature and will aid the power-plant project investment industry through their project feasibility analyses

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Summary

Introduction

Electricity demand is steadily increasing globally as the world develops and technology advances. This increase in demand is not unique to any one country. World power demand will increase 1.4 times from 19,562 TWh in 2012 to. Worldwide capacity is expected to increase by a factor of 1.4 from 6117 GW in 2014 to 8370 GW in 2025 to meet these demands. Added capacity in developing countries is expected to account for 70% of this increase [1]. While smart grid technologies and various renewable energy sources have been developed, they are insufficient for meeting the increasing demand and cannot replace traditional power-intensive generation [1]. The development of traditional power generation methods’ demand is expected to grow

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