Avaliação energética e econômica do aproveitamento de energia térmica residual utilizando ciclo Rankine Orgânico.

Abstract

This paper aimed to make a thermal analysis of the electricity generation from the reuse of waste heat discharged on the atmosphere, specifically in industries that use thermal energy in their processes, such as steel, cement and lime industries, among others. For this, it was created a computational tool for technical and financial analysis, developed in Microsoft Excel, along with the CoolProp module, allowing wide use in the private setor and academia. To reuse this energy, the Organic Rankine Cycle (ORC) was considered.. The methodology was based on the study of consolidated theories of power cycles, energy balance of the 1st Law of Thermodynamics, organic working fluids, acquisition cost estimates (MCT – Module Costing Technique) and methods for financial evaluation of investments. After determining and adopting assumptions and boundary conditions, the technical and financial model was developed for implementation in the spreadsheet, along with the user interface. In this interface, data such as work regime, waste heat gas flow and temperature, exchange rate, taxes and kWh price, among others, are filled in. From the calculations performed by the tool, results are displayed to the user, such as the amount of energy generated, price of electricity produced, investment value, operating costs and payback, in order to obtain preliminary results regarding viability of implementation of an ORC system into the industrial process, aiming at self-sufficiency in relation to the electricity by the concessionaire. Additionally, two operating scenarios were simulated, one with low and one with high waste heat available. It was possible to verify specific conditions of economic and financial feasibility in work regimes exceeding 6,000 hours/year, with temperatures above 150 °C and flow rates above 17 m3/s, according to the values established for the currency exchange rate, financial leverage and minimum attractiveness rate. Finally, the correlations between the input data and the results obtained were analyzed in order to map the greatest influences in relation to the project's viability, especially exchange rate, price of kWh from the concessionaire and cost of capital, which can make the investment not recommended, even in operating scenarios with high temperatures, flow rates and working regimes.