Produção Nacional
Revisado por pares
Biomass based Rankine cycle, ORC and gasification system for electricity generation for isolated communities in Bonfim city, Brazil
2019; Institution of Engineering and Technology; Volume: 13; Issue: 5 Linguagem: Inglês
10.1049/iet-rpg.2018.5535
ISSN1752-1424
AutoresPedro Jessid Pacheco Torres, Osvaldo José Venturini, José Carlos Escobar Palácio, Rafael Augusto Costa Silva, Maria Luiza Grillo Renó,
Tópico(s)Energy and Environment Impacts
ResumoIET Renewable Power GenerationVolume 13, Issue 5 p. 737-743 Research ArticleFree Access Biomass based Rankine cycle, ORC and gasification system for electricity generation for isolated communities in Bonfim city, Brazil Pedro J. Pacheco Torres, Pedro J. Pacheco Torres Reformed Community of Research and Development in Engineering, CRIDI, Faculty of Engineering, Corporación Universitaria Reformada, Barranquilla, AT, ColombiaSearch for more papers by this authorOsvaldo José Venturini, Osvaldo José Venturini Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorJosé C. Escobar Palacio, José C. Escobar Palacio Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorRafael A. Costa Silva, Rafael A. Costa Silva Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorMaria Luiza Grillo Renó, Corresponding Author Maria Luiza Grillo Renó malureno@unifei.edu.br orcid.org/0000-0002-3903-2777 Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this author Pedro J. Pacheco Torres, Pedro J. Pacheco Torres Reformed Community of Research and Development in Engineering, CRIDI, Faculty of Engineering, Corporación Universitaria Reformada, Barranquilla, AT, ColombiaSearch for more papers by this authorOsvaldo José Venturini, Osvaldo José Venturini Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorJosé C. Escobar Palacio, José C. Escobar Palacio Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorRafael A. Costa Silva, Rafael A. Costa Silva Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this authorMaria Luiza Grillo Renó, Corresponding Author Maria Luiza Grillo Renó malureno@unifei.edu.br orcid.org/0000-0002-3903-2777 Mechanical Engineering Institute, Universidade Federal de Itajubá, Rua Doutor Pereira Cabral, 1303, Pinheirinho, Itajubá, BrazilSearch for more papers by this author First published: 08 February 2019 https://doi.org/10.1049/iet-rpg.2018.5535Citations: 3AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract In Brazil, specify in isolated areas, the connection to the conventional electric energy distribution grid becomes restrictied due to financial and geographical factors. Then the main option for supplying the energy demand is fossil fuel driven thermal systems. With the purpose of providing an alternative option for power generation, this study presents an analysis of biomass-based energy systems for isolated communities, in special Bonfim city, in Roraima state. The technologies applied were conventional Rankine cycle, organic Rankine cycle (ORC) and gasification system with an internal combustion engine. All systems are operated with agricultural wastes (rice straw and rice husk). The modelled systems produced electricity with a conversion efficiency of 10.78, 17.78 and 14% for ORC, conventional Rankine cycle and gasification systems, respectively. With these results and with a production of 35,667 tons of waste per year, the systems can supply the energetic demand of Bonfim city (536.40 kW). With relation to costs, currently the generation costs in isolated communities of Bonfim city are in a range of 390.31–475.85 US$/MWh. The proposed cases have a generation costs of 197.11 US$/MWh (conventional Rankine cycle), 324.77 US$/MWh (ORC) and 336.49 US$/MWh (gasification system). 1 Introduction Small-scale, distributed and low cost biomass power generation technologies are highly required in the modern society. There are needs for these technologies in the disaster areas of developed countries and un-electrified rural areas of developing countries [1]. The advantage of power generation from biomass is the available of the same in almost all places, especially in rural areas where there are remote villages with no access to grid but aced to significant amounts of biomass. Biomass power generation contributes to the prosperity of rural areas, providing employment and socio-economic benefits [2]. Brazil has a great potential for generating energy from biomass, but currently only a small fraction of the biomass is used for energy production [3]. For this reason, the electricity generation on a small scale from biomass has been the object of various studies and projects in later periods. These projects were primarily focused on the generation in isolated areas and in low-income communities. As an example, Veláquez et al. [4] presented the development stages of a micro-scale system for electricity generation from biomass with 500 W of power in isolated communities in the Amazon region. The proposed system was based on an open steam power cycle, the results achieved demonstrated that the steam turbine is the critical component to the commercial-scale feasibility of the propose technology and significant improvements should be applied on the system, especially regarding the efficiency of the micro-turbine. Aghamohammadi et al. [5] proposed a sustainable management model for electrification of remote communities in the Amazon region. This paper presented a case study of the electrification in a river-dwelling community in the State of Pará, Brazil. The system consisted of a small biomass-based power plant that burns residues produced by the local economic activity. Besides Brazil, other countries have investigated this theme, for example in Malaysia. Aghamohammadi et al [5] investigated the sustainability of power generation from palm biomass in Sarawak (Malaysia). The results of study demonstrated that Sarawak has biomass in abundance; however, the key challenge to achieving the renewable energy target is the inadequate grid infrastructure that inhibits palm oil developers from benefiting from the feed-in-tariff payment scheme. In Indian there is also research in this area, as in [6] that highlights the technical and economic issues related to decentralised power generation in India using biomass gasification. The reviews of various technical options for biomass gasification based on low–medium–large-scale power generation. It was discussed the merits and demerits (operational and other problems) of different systems, as well as the viability of biomass-based power generation. In relation to the cost of electricity from biomass, power generation depends on the supply economics of biomass feedstock, power generation technology and scale of operation. Abdelhady et al. [7] analysed the techno-economic feasibility of electric power generation from rice straw in Egypt. It was estimated the energy production and the levelized cost of electricity (LCOE). The model proposed was biomass Rankine cycle power plant fed with rice straw. The simulation shows that the average nominal and the average real of LCOE for the proposed power plants are 10.55 and 6.33 ¢/kWh respectively, which is very competitive, compared with LCOE of other renewable energy technologies in Egypt. Pighinelli et al. [8] modelled an electricity generation plant of 2000 metric ton per day eucalyptus Tail Gas Reactive Pyrolysis (TGRP). The purpose was evaluated techno-economic viability in Brazil. Two scenarios were compared based on operational conditions in the country: a single biomass to bio-oil TGRP production facility and a distributed/satellite processing that consists of several small TGRP production facilities with aggregate capacity similar to the single one, both feeding into one centralised electricity generation plant. The selling price at the breakeven point of the electricity generated via TGRP was estimated to be US$ 0.34 and US$ 0.62 per kWh for the single and distributed scenarios, respectively. In relation to environmental aspects, Jongprasithporn et al. [9] presented the assessment and management of environmental risk of 7.5 and 9.9 MW biomass power plants in Thailand. The results of the research showed that the impact on air quality, sound levels, and water quality of biomass power plants are within the standard values. Abdul Malek et al. [10] analysed the environmental impact of a 10 MW biomass power plant in Malaysia. The results showed that the plant releases 50,130 t less CO2, 750 t less SO2, 218.65 t less NOx and 22.83 t less CO emissions in the environment compared with the existing energy mix. In this context, this work presents a technical and economic study of different types of generator systems, applying rice straw and rice husk to generate electricity in the city of Bonfim, Brazil. This research can expand to other cities in the North of Brazil involving similar agricultural and waste production. 2 Methodology 2.1 Raw materials The city of Bonfim is one of the cities in the state of Roraima with an area of 8095.4 km2. This selected city presents the large availability of agricultural residues including seven different types of crops: cassava, rice, banana, corn, soybean, sugarcane, and beams [11]. Actually, the electricity generation is from fossil sources with a capacity 90% of the total crop production per year in Bomfin. This crop has two recoverable types of wastes: rice straw and rice husks. According to the Phyllis classification, waste rice has a calorific value of 14.54 MJ/kg and a moisture content of 4.04% [12, 13]. For determining the amount of available waste it is applied the waste conversion factor (WCF) that represents the amount of waste produced from amount of biomass produced, considering technical and environmental aspects. This factor depends of the ratio factor (RF), which corresponds the amount of waste generated from the quantity of produced product, and the availability factor (AFR), which is the allowed percentage of residue extraction. Equation (1) demonstrates this calculus as follows: (1) According to the literature, during rice cropping separate grains and straw. The rice straw has an RF of 1.25 tons of biomass per ton of rice [14], but it is recommended that not >40% of crop residues be removed (AFR = 40%). As a result, the WCF has a value of 0.50 for energy generation [15]. For rice husk, the quantity available is ∼0.20 per ton of rice with AFR equal to 100%, obtaining a WCF of 0.20 for the power generation. The sum of the two factors is equal to 0.70 tons of biomass per ton of rice [15]. 2.2 Biomass conversion technology applied There are four main categories of conversion technologies for exploitation of biomass energy: direct combustion, thermochemical processes (gasification or pyrolysis), biochemical processes, and agrochemical processes. Currently, the most commonly used technologies to convert biomass energy into electricity are direct combustion and gasification [16]. For this reason, this work selected these technologies through three case studies. As direct combustion, one case study is the organic Rankine cycle (ORC) with a capacity of 630 kW, other is a conventional Rankine cycle (625 kW). The last case study is the gasification process (870 kW). The capacity was based on the market availability of these technologies and electric power demand in Bonfim city (536.4 kW) [17]. For the different simulations, the following environmental conditions have been defined: atmospheric air temperature (25°C), atmospheric air pressure (101.3 kPa), and relative humidity in the atmosphere (0.6). 2.2.1 Conventional Rankine cycle The conventional Rankine cycle has been used for many years in several industries, such as: sugar, rice, palm oil, paper, and wood industries. The focus is to produce electricity with relatively low efficiency. However, the low price of fuel (biomass wastes from the process), the maturity and reliability of the technology, and its relatively low investment cost make this conversion technology an attractive option. The Rankine power system of this work consists mainly of a fire-tube boiler, one condensing/extraction steam turbine, an electric generator, two auxiliary pumps, a deaerator and a close water-cooling system (Fig. 1). Simulations were performed using GateCycleTM software that is a PC-based software application used for the design and performance evaluation of thermal power plant systems. The software combines an intuitive, graphical user interface with detailed analytical models for the thermodynamic, heat-transfer and fluid-mechanical process [18]. The general parameters adopted are from references data (Table 1). Table 1. Parameters for modelling the conventional Rankine cycle Parameter Value, unit Reference volatile matter 80% [19] biomass moisture 20% [19] steam pressure 2 MPa [20] steam temperature 300°C [20] extraction pressure 110 kPa GateCycle condensing pressure 10 kPa [20] installed capacity 625 kW [17] steam turbine isentropic efficiency 80% [21] pumps isentropic efficiency 70% [21] boiler thermal efficiency 70% [21] electrical efficiency of the generator 98% [20] biomass – LHV 14.54 MJ/kg [12] feed water temperature 102.65°C GateCycle time of service: 95% of the year 8322 h [22] Fig. 1Open in figure viewerPowerPoint Rankine cycle scheme in GateCycle 2.2.2 Organic Rankine cycle The ORCs' principle is similar to conventional Rankine cycle. The turbo generator works as a conventional steam turbine to transform thermal energy into mechanical energy and finally into electric energy. Instead of generating steam from water, the ORC system vaporises an organic fluid, characterised by a molecular mass higher than water. This characteristic leads to a slower rotation of the turbine, lower pressures and no erosion of the metal parts and blades. These systems are available on the market on small scales with turbine operating at temperatures and pressures around 300°C and 20 bar, respectively. Besides turbine, the cycle operates with a pump, a condenser, a boiler and a regenerator that ensures that the working fluid operates under critical pressure (20 bar). A limiting factor in ORC is the working fluid; this limits the efficiency of the cycle. So, various studies have been carried out to identify adequate working fluids, for example toluene and octamethyltrisiloxane (OMTS). These fluids can be applied for biomass energy power systems, mainly the toluene, which has a critical pressure of 40.09 bar, offering more suitable conditions for ORC applications. On the other hand, the OMTS has low critical pressure (14.2 bar), its vaporisation enthalpy is significantly lower and it has efficiency lower than toluene. With this previous analysis, the toluene was selected for this work. The properties of the fluid were obtained from the CoolProp Tool (Excel®). This software is a thermophysical property database which is available under MIT License as free software. It has a databank of 122 components with thermodynamic and transport properties for pure components and their mixture. CoolPro Tool is developed as a C++ library. It has an interface available for several of the popular programming languages in the form of wrappers, such as Python, Modelica, octave, MathCAD, and MATLAB [23]. The main operating parameters of ORC system are summarised in Table 2 and the thermal system scheme in Fig. 2. Table 2. Parameters for modelling the ORC operating with toluene Parameter Value, unit Reference volatile matter 80% [19] biomass moisture 20% [19] turbine inlet pressure 1.8 MPa [24] turbine inlet temperature 300°C [24] condensing pressure 74 kPa [25] installed capacity 630 kW [17] turbine isentropic efficiency 75% [21] pumps isentropic efficiency 70% [21] evaporator inlet temperature 205°C [26] boiler thermal efficiency 70% [21] electrical efficiency of the generator 98% [20] biomass – LHV 14.54 MJ/kg [12] time of service: 95% of the year 8322 h [22] Fig. 2Open in figure viewerPowerPoint ORC scheme 2.2.3 Biomass gasification Fig. 3 shows a schematic representation of a gasifier coupled with an internal combustion engine for electricity generation. The selected gasifier was a fixed bed co-current that has the advantage of producing a tar-free gas (or syngas), suitable for engine applications. Fig. 3Open in figure viewerPowerPoint Schematic representation of electricity generation from biomass gasification The syngas is composed mainly of hydrogen (17%), carbon monoxide (18.4%) and carbon dioxide (9.9%) with a lower heating value 4 MJ/Nm3. Although the syngas is tar-free, it needs cleaning treatment due to the presence of other contaminants (particulates, flash, ash etc.) [27]. Currently, there a variety of technologies for gas cleaning systems (e.g. sand filters, washing towers, venture washer, electrostatic precipitator and bag filters) [28, 29]. Once the gas is cleaned and cooled, it is sent to the combustion engine. The cold efficiency of the gasification process and the performance of the internal combustion engine were calculated using the model developed by González [30]. The geometry used corresponds to Yanmar BTD 22 engine. This was originally built to work with diesel but was modified to work with natural gas and syngas. The cylinder diameter is 0.09 m, the piston stroke is 0.09, the compression rate is 12 and number of cylinders is 2. The main parameters for plant simulation are in Table 3. Table 3. Parameters for modelling the gasification process (fixed bed co-current) Parameter Value, unit Reference volatile matter 80% [19] biomass moisture 20% [19] gasifier cold efficiency 70% [24] gas engine efficiency 28% [24] installed capacity 870 kW [17] turbine isentropic efficiency 75% [21] pumps isentropic efficiency 70% [21] evaporator inlet temperature 205°C [26] boiler thermal efficiency 70% [21] electrical efficiency of the generator 98% [20] biomass – LHV 14.54 MJ/kg [12] derating 23% [31] time of service: 95% of the year 8322 h [22] The energy available in the gasifier is calculated as shown in the following equation: (2) where Ea is the available energy in the gasifier (MJ/year); mTb is the mass flow of treated biomass (kg/year); LHV is the low heating value of the biomass (MJ/kg); and ƞg is the gasifier cold efficiency (%). The capacity installed is approached as follows: (3) where P (kW) is the power generator to be installed; Δt (s) is the service time (95% of the year); ƞe (%) is the gas engine efficiency; and dr (%) is the derating. In a system with Gasifier–Gas cleaning–Internal Combustion Engine, the power consumption is 10% of electric energy generated [30]. 3 Results After defining the appropriate parameters for each different technology, it was calculated the efficiencies and the biomass consumption by (4) and (5). These results are shown in Table 4. (4) (5) The η (%) (from (4)) is the electric efficiency, Wnet is the net power produced, Qin is the heat value of biomass fuel, SBC (kg/kWh) is the specific biomass consumption and Ab is the amount of biomass consumption. Table 4. Performance of the technologies proposed ORC Rankine cycle Gasification biomass consumption, kg/s 0.40 0.24 0.33 electric efficiency, % 10.78 17.78 14 SBC, kg/kWh 2.41 1.51 1.97 net power, kW 3143 2905 3358 The ORC has the potential to generate 4993 MWh/y with an efficiency of 10.78%. The conventional Rankine cycle has the potential to generate 4785 MWh/y with an efficiency of 17.78%. Finally, the gasification system with the internal combustion engine has the potential to generate 5011 MWh/y also with an efficiency of 14%. 3.1 Generation cost As a comparative measure of the current systems with the proposed ones, it was necessary to determine the annual generation costs of the diesel oil plants. Then, it was necessary determinate the cost of the inputs (fuel) and the fixed and operational costs of the plants. Bonfim city has seven diesel oil plants with the following capacities: 4.8 kW (Maloca Moscow), 10 kW (Jacamim), 18 kW (Pium), two of 32 kW (Maloca do Manoá and Nova Esperança), 120 kW (Vila Vilena), and 320 kW (São Francisco). As a result, the total installed capacity is 536.8 kW. The plant operation and the investment costs of each of these plants were obtained by considering Normative Resolution No. 427, 22 February 2011 year and the literature data [27, 28]. The quantity of energy produced by diesel oil plants is determined by the following equation: (6) where Wnet (kWh) is the amount of energy generated by the system, P (kW) is the power generation and Δt is the availability of the plant (95% = 8322 h). The power generation can be computed by the following equation: (7) where nf is the fuel conversion efficiency, ma is the mass of air introduced into the cylinder (s) per cycle, N is the crankshaft rotational speed, QHV is the heating value of the fuel, F/A is the fuel mass flow rate/air mass flow rate, nR is the number of crank revolutions per power stroke. With this information, it was possible to calculate the diesel consumption for this generation system as follows: (8) where Af is the amount of fuel consumed during power generation and DCI (l/kWh) is the diesel consumption index. These data were obtained from [32] and it is presented in Table 5. Table 5. Fuel specific consumption limits by power of the piston engine [32] Power, kW DCI/liquid fuel, l/kWh Heat-rate, kJ/kWh 1–100 0.404 14,404 101–250 0.349 12,443 251–500 0.329 11,730 501–750 0.296 10,533 751–1000 0.296 10,533 1001–2500 0.296 10,533 2501–5000 0.283 10,090 5001–7500 0.283 10,090 7501–10,000 0.283 10,090 10,001–12,500 0.283 10,090 12,501–15,000 0.283 10,090 15,001–20,000 0.283 10,090 20,001–above 0.283 10,090 Thus, for the first plant (Maloca Moscow plant), the amount of energy generated and the fuel consumption are, 39,945.60 kWh and 16,138.02 l, respectively. Considering a cost of R$ 2.86 per litre of diesel oil and using an exchange rate of 3.00 R$/US$, it was determined that the annual cost of diesel is USD 15,379.75 per year. Complementing the total generation costs, for computing the fixed investments and the operation and maintenance costs of the plant, it was based in generation capacity, reference of thermoelectric plants cost [29] as follows: (9) (10) where Cf (US$/year) is the fixed cost during power generation, CO&M (US$/year) is the operating and maintenance cost, Wnet (MWh) is the energy generated by the system, FCI (R$/MWh) is the fixed cost index and O&M.CI (R$/MWh) is the operating and maintenance cost index. Table 6 presents the values for FCI and O&M.CI of power plant operating with internal combustion engine (diesel fuel). Table 6. Cost of power generation of diesel oil plants [31] Installed power, kW O&M.CI, R$/MWh FCI, R$/MWh 0–24 106.60 165.59 25–49 106.60 165.59 50–74 106.60 165.59 75–99 106.60 165.59 100–249 107.99 147.80 250–499 107.99 135.21 500–749 107.99 122.05 750–999 90.88 102.71 1000–2499 90.88 104.27 2500–4999 85.74 103.99 5000–7499 76.27 92.50 7500–9999 71.12 86.26 10,000–14,999 66.73 80.95 15,000–19,999 58.37 70.80 20,000–above 53.39 64.76 In conclusion, considering an exchange rate of 3.00 R$/US$, for Maloca Moscow plant, the annual additional fixed and O&M costs of energy generation are US$2207.37 and US$ 1421.01, respectively. The generation costs with the current system (diesel oil thermoelectric plants) are 1.8 million USD per year. Table 7 shows these three costs (the costs of fuel, operation and maintenance, and fixed investment) for seven diesel oil plants in Bonfim city. Table 7. Generation costs of diesel oil thermoelectric plants in Bonfim city Plant Fuel cost, US$ Cost operation and maintenance, US$ Fixed income, US$ Maloca Moscow 1.53 × 104 1.42 × 103 2.21 × 103 Jacamin 3.20 × 104 2.96 × 103 4.60 × 103 Pium 5.76 × 104 5.33 × 103 8.28 × 103 Maloca do Manoá 1.02 × 105 9.60 × 103 1.31 × 104 Nova Esperança 1.02 × 105 9.60 × 103 1.31 × 104 Vila Vilena 3.32 × 105 3.60 × 104 4.50 × 104 São Francisco 8.34 × 105 9.60 × 104 1.08 × 105 total 1.48 × 106 1.60 × 105 1.95 × 105 Table 8 presents the investment cost for the three technologies of this study. Table 8. Investment cost for three cases [26-29] Rankine cycle ORC Gasification capacity, kW 625 630 870 PCE (US$) 2.74 × 106 4.72 × 106 5.12 × 106 CWE (73% PCE), US$ 2.00 × 106 3.44 × 106 3.74 × 106 TDC (PCE + CWE), US$ 4.74 × 106 8.16 × 106 8.86 × 106 IC (12% TDC), US$ 5.69 × 105 9.79 × 105 1.06 × 106 FCI (TDC + IC), US$ 5.31 × 106 9.14 × 106 9.92 × 106 AM (3% TDC), US$ 1.42 × 105 2.44 × 105 6.25 × 105 total cost, US$ 5.45 × 106 9.39 × 106 1.02 × 107 In Table 8, the abbreviations are PCE (purchased-equipment cost), CWE (civil work and engineering), TDC (total direct cost), IC (indirect cost), AM (annual maintenance). It can be observed that the RC power plant of 625 kW capacity has a total cost of 5.4 million US$, the ORC plant of 630 kW capacity has a total cost of 9.3 million US$, and the Gasification plant of 870 kW capacity has a total cost of 10.1 million US$. Dividing the total cost (US$) by the capacity power plant (kW) it is obtained the specific cost: 8728 US$/kW (Rankine cycle), 14,901 US$/kW (ORC), 11,708 US$/kW (gasification). In Fig. 4, it is possible to compare the calculation of the generation cost for conventional diesel oil plants and for the cases proposed in this paper. Fig. 4Open in figure viewerPowerPoint Generation costs of thermoelectric plants and the proposed cases The generation costs in isolated communities of Bonfim city are in the range of 390.31–475.85 US$/MWh. The generation costs of the proposed cases are 197.11 US$/MWh for the Rankine cycle, 324.77 US$/MWh for the ORC, and 336.49 US$/MWh for the gasification system. 3.2 Economic analysis There are different types of economic indicators to determine the feasibility of a project. The indicators used in this work are the Net Present Value (NPV) and the Internal Rate of Return (IRR). The NPV is an indicator that shows the economic viability of the project during its useful life. This indicator is defined by the difference between the current value of the benefits and the value of the system costs (11) where PB ($/year) is the project benefit in one year; Cp ($/year) is the cost of the project in one year, Dir is the discount rate (interest); t is the time; and n is the useful life of the investment (years). The IRR indicator was calculated as follows: (12) The NPV and the IRR are based on ANEEL Technical Note No. 89 of 2014. For the economic analysis, a minimum rate of attractiveness of 7.16% was adopted. Table 9 shows the values considerate for the fixed and maintenance cost. Fig. 5 shows the IRR calculated for the different proposed cases. Table 9. Cost for economic analyses Rankine cycle (US$) ORC, (US$) Gasification, (US$) yearly maint. 1.42 × 105 2.44 × 105 2.65 × 105 variable fixed 2.09 × 104 2.09 × 104 2.09 × 104 biomass pre-treatment 3.73 × 104 6.20 × 104 5.07 × 104 total yearly cost 7.00 × 105 1.14 × 106 1.18 × 106 Fig. 5Open in figure viewerPowerPoint Internal rate of return for the three cases The IRR values of the different cases proposed for the isolated communities of Bonfim city are 27.17% for the Rankine cycle, 13.69% for the ORC, and 12.09% for the gasification system. The results appoint the potential to obtain internal taxes of return 69, 91 and 279% higher than the minimal tax of attractiveness, in function of the technology applied. Economic analysis of a project requires the formulation of a cash flow and the use of a data considered certain and constant, but this hardly happens in our case, because these data are from estimated values, that try to translate a picture of the real happening, and each one of the variables changes over time. Therefore, the calculated NPV values are also not accurate, and as a consequence, it is imperative to apply a method to determine the influence that the change in one of the variables has on the expected results of the project as a whole. Therefore a sensitive analysis was made for each scenario based on the information presented in Table 10. Table 10. Main economic parameters considered Variable Base value electricity price 410.32 US$/MWh project lifetime 20 years tax rate 7.16% operation 8322 h For each scenario, a set of initial values ('base
Referência(s)