A comparative study of biomass integrated gasification combined cycle power systems: Performance analysis
Introduction
The growing need for sustainable renewable energy and increasing concern over greenhouse gas emissions has prompted the development of biomass-based power plants (Hahn et al., 2015, Patterson et al., 2017). Previous research has applied coal-based technologies to biomass-based power systems (Hu et al., 2017, Yan et al., 2016). In the coal-based electricity generation industry, Integrated Gasification Combined Cycle (IGCC) has been used as a clean coal technology (Franco and Diaz, 2009). The application of this technology has shown that IGCC has a Higher Heating Value (HHV) based efficiency of 42.1%, which reduces the cost of CO2 Capture and Storage (CCS) for controlling CO2 emissions (Fout et al., 2015). Therefore, Biomass Integrated Gasification Combined Cycle (BIGCC), which has a similar system design as IGCC, is expected to be highly efficient and economically feasible for biomass-based power plants (Klein et al., 2011).
BIGCC power systems have been developed for decades. Twenty years ago there was a significant interest in BIGCC power systems. By 2006, five BIGCC demonstration projects had been built (Pang and Li, 2006). However, only two of them proved the viability of this technology. Two reasons are responsible for the slow development of BIGCC projects. The first reason is the lack of a detailed feasibility study, which should include a full analysis of technology improvements, supply chain, energy market, and economic scale. The second reason is the unrealistic expectations of the economic benefits of these projects. Although some preliminary BIGCC power system attempts were not very successful, the system still is considered to have great potentials mainly for its possibility to increase the conversion efficiency of biomass into electricity (Williams, 2005). Moreover, recent work has shown that improved analysis tools such as exergy analysis, tech-economic analysis, life-cycle assessment, and energy market integration allow for more detailed feasibility studies to be implemented before a project is designed (Da Fonseca Filho et al., 2016, Mondal and Ghosh, 2017). In addition, biomass gasification technology has been developed and zero-cost wastes biomass resources can be applied to reduce the cost of BIGCC power systems. Therefore, after a decade of silence, some attention has been redirected to BIGCC power systems (Hagos et al., 2017, Mondal and Ghosh, 2017, Shabbir and Mirzaeian, 2016, Taylor et al., 2015).
BIGCC power systems have integrated biomass gasification with the combined cycle of gas and steam turbines. Biomass gasification is a promising technology that converts solid biomass fuel into a gaseous energy carrier (Simone et al., 2012). There are many types of gasifiers available for biomass gasification, such as fixed bed, fluidized bed, entrained flow, and plasma. In this study, the type of gasifier we selected is the fluidized bed because of its excellent mass and heat exchange rates, temperature uniformity, high fuel flexibility, and high capacity up to 100 MW (Ruiz et al., 2013).
Optimization of BIGCC power systems can be performed in three main steps in system design. The first step is related to biomass gasification. The proposed improvement is using a mixture of oxygen and steam as the gasification agent instead of air that is traditionally used. The major problem with air gasification is the low heating value of syngas which is around 6 MJ/Nm3. In contrast, oxygen/steam gasification can produce syngas with a higher heating value, which is could be greater than 11.11 MJ/Nm3. (Lv et al., 2007). Even though previous studies have shown that oxygen/steam gasification improves syngas quality, we need further evidence to see if oxygen/steam gasification can generate more power in a real BIGCC plant due to the additional energy consumption in the Air Separation Unit (ASU).
The modification can also be applied to the second step, which considers the process of burning the syngas to generate power in a combined cycle. One alternative is changing the traditional internally fired gas turbine into an externally fired gas turbine (Datta et al., 2010). The syngas, which burns in an internally fired gas turbine, needs to be cleaned carefully, which increase the cost of BIGCC plants. In contrast, Externally Fired Gas Turbine (EFGT) cycle integrated with biomass gasification has two advantages. One is that “dirty” fuel can burn in the externally fired gas turbine, which can reduce the cost of syngas cleaning. The other is that EFGT employs low-pressure combustion, which can reduce the energy consumption of compressors and improve the system efficiency. Even though previous studies have analyzed the performance characteristic of EFGT-BIGCC, it is hard to determine whether using the externally fired combustion method is a definite improvement of BIGCC as a result of the high capital cost and high technology risk of EFGT.
The last significant step in BIGCC power system design is pollution control. As a clean biomass conversion technology, BIGCC can obtain net negative CO2 emissions when it is integrated with CO2 Capture and Storage (CCS), which can use pre-combustion and post-combustion techniques to control CO2 emission by consuming energy. Even though the pre-combustion CCS decreases the CO2 emissions by 2.4–2.9 times for an oxygen/steam blown BIGCC power system, its efficiency decreases around 10% (Mínguez et al., 2013). For a coal-based IGCC power plant it has been shown that, compared with post-combustion CCS method, the pre-combustion capture design has superior performance (Cormos, 2014). However, it is still hard to demonstrate the benefit of employing pre-combustion CCS method in biomass-based BIGCC plants due to the limited availability of comparison data between pre-combustion and post-combustion.
Based on the previous description, the evaluation of BIGCC systems technological alternatives includes three critical design parameters, which are gasification agents, the gas turbine combustion methods, and CO2 emission control options. However, a BIGCC comparison study that considers all of these parameters cannot be found in the literature. Therefore, the purpose of this paper is to evaluate eight BIGCC plant scheme alternatives by using Aspen plus software with the same simulation assumptions and to carry out an exergy-based thermodynamic assessment. This study aims to provide more insights on the technological options for BIGCC system design.
Section snippets
System configuration
Eight BIGCC power system scheme alternatives are modeled using Aspen Plus software. Table 1 lists the configurations of these systems, each of which is named by three letters. “A” and “O” correspond respectively to using the air or the mixture of oxygen and steam as the gasification agent. “I” and “E” coincide respectively with using the internally fired or the externally fired gas turbine. “C” and “V” are corresponding to BIGCC plants with or without CCS, respectively. For example, an “AIV”
Mass and exergy balance
Table 3 shows the mass balance of water and carbon in the eight BIGCC power systems when the biomass input is 27 ton/hr. Both carbon and water reach balances in all systems. For the water balance, the total water input incorporates the water input to the cleaning system and the Rankine Cycle, whereas the water output includes all the water consumption. As shown in Table 3, AEV and AEC have the largest water consumption at 104.3 ton/hr, which means the externally fired gas turbine combined cycle
Conclusions
This paper simulates eight BIGCC power systems using Aspen Plus and uses exergy as the criterion to evaluate their performance. The exergy analysis shows that AEV and OEC have the highest exergy efficiency of 37.1% and 25.2%, respectively, which demonstrates that the external combustion and oxygen/steam gasification integrated with Selexol are less energy intensive methods. The performance analysis confirms that the effect of the gas turbine on the system performance is larger than that of the
Acknowledgement
The authors would like to thank the Committee on Coordination of Improvements in Higher Education (CAPES), Call Projects: MEC/MCTI/CAPES/CNPq/FAPs No 71/2013 – Special Guest Researcher, also the National Council for Scientific and Technological Development (CNPq) and the Research Support Foundation of the State of Minas Gerais (FAPEMIG) for a research productivity grant. The grant number Proposal: 152583. Process: 88881.030460 / 2013-01 for financial support, and the University of Iowa, US
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