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Microalgae are fast becoming promising renewable green fuel that can be grown on diverse landforms. One of the energy-generating pathways is to directly combust the species while the interior water content is a major obstruction of its utilization. In this work, a mathematical model of the steam power plant and microalgae drying process were develo...
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... microalgae combustion has been reported as one of the efficient processes [1]. In order to have an insight on how direct combustion of microalgae can be used for power generation, an integrated 12.5 MW power plant model with microalgae drying is used in this case study. Pinch analysis is used to show the effectiveness of the heat integration of different design options and to identify further improvements. To illustrate how the concept of pinch analysis can give insight on improvements of heat integration process, microalgae-based power plant for an output power, P , of 12.5MW is shown in Fig 1. The process flow diagram given in Fig 1 describes the Base Case along with three possible integration cases. In the base case, fresh microalgae with a moisture content of 60wt% is fed directly to the boiler and the units in the dashed line were not considered in simulation study. The steam level and the BFW water preheating temperatures are selected arbitrarily. Next in case an attempt was made on possible overall efficiency increment by optimizing the steam pressure and boiler feed water-preheating levels. The next two cases comprised different drying schemes, with only HAD, and both HAD and SSD in multi-stage manner. When considering the last two cases, only the dryers in question are integrated in the simulation study. When using HAD-only drying, LP steam is extracted from the power plant to reduce the moisture content of microalgae from 60% to some value in the inlet of the boiler. While simultaneous usage of HAD and SSD for drying LP steam from the power plant is used in SSD and LP steam generated at SSD along with LP from the power plant is used to preheat the air for later usage in the HAD. Mathematical modeling of the steam cycle is based on conservation of mass and energy as in Eq. (1), for mass balance and Eq. (2), for energy balance. (1) (2) Where and respectively are mass in and mass out of a unit (kg/h), and respectively are energy flows in and out of a unit (kJ/h), and is the change (e.g. power output of a turbine) (kJ/h). The pumps and turbines are separately assumed to operate at 100% and 80% isentropic efficiency respectively. The isentropic efficiencies of the pump and turbine, η pump and η turbine , are defined by Eq. (3) and Eq. (4) ...
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... microalgae combustion has been reported as one of the efficient processes [1]. In order to have an insight on how direct combustion of microalgae can be used for power generation, an integrated 12.5 MW power plant model with microalgae drying is used in this case study. Pinch analysis is used to show the effectiveness of the heat integration of different design options and to identify further improvements. To illustrate how the concept of pinch analysis can give insight on improvements of heat integration process, microalgae-based power plant for an output power, P , of 12.5MW is shown in Fig 1. The process flow diagram given in Fig 1 describes the Base Case along with three possible integration cases. In the base case, fresh microalgae with a moisture content of 60wt% is fed directly to the boiler and the units in the dashed line were not considered in simulation study. The steam level and the BFW water preheating temperatures are selected arbitrarily. Next in case an attempt was made on possible overall efficiency increment by optimizing the steam pressure and boiler feed water-preheating levels. The next two cases comprised different drying schemes, with only HAD, and both HAD and SSD in multi-stage manner. When considering the last two cases, only the dryers in question are integrated in the simulation study. When using HAD-only drying, LP steam is extracted from the power plant to reduce the moisture content of microalgae from 60% to some value in the inlet of the boiler. While simultaneous usage of HAD and SSD for drying LP steam from the power plant is used in SSD and LP steam generated at SSD along with LP from the power plant is used to preheat the air for later usage in the HAD. Mathematical modeling of the steam cycle is based on conservation of mass and energy as in Eq. (1), for mass balance and Eq. (2), for energy balance. (1) (2) Where and respectively are mass in and mass out of a unit (kg/h), and respectively are energy flows in and out of a unit (kJ/h), and is the change (e.g. power output of a turbine) (kJ/h). The pumps and turbines are separately assumed to operate at 100% and 80% isentropic efficiency respectively. The isentropic efficiencies of the pump and turbine, η pump and η turbine , are defined by Eq. (3) and Eq. (4) ...
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... total power output, P out (MW), for the closed cycle of the power plant in Fig 1 for a given amount of microalgae feed can be calculated by Eq. (8) using the W i (the power output of the three turbines) and P i (the pumping represents pumping power of the ...
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... illustrate how the concept of pinch analysis can give insight on improvements of heat integration process, microalgae-based power plant for an output power, P out , of 12.5MW is shown in The process flow diagram given in Fig 1 describes the Base Case along with three possible integration cases. In the base case, fresh microalgae with a moisture content of 60wt% is fed directly to the boiler and the units in the dashed line were not considered in simulation study. ...
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... enthalpy and specific entropy were calculated via Water97, an Add-In for MS Excel which automatically calculates thermodynamic properties of water and steam under the industrial standard IAPWS-IF97 [2]. The efficiency of the boiler, η boiler , is assumed to be 90% and the boiler duty, (kJ/h), is calculated as in Eq. (5 The total power output, P out (MW), for the closed cycle of the power plant in Fig 1 for a given amount of microalgae feed can be calculated by Eq. (8) using the W i (the power output of the three turbines) and P i (the pumping represents pumping power of the pumps. ...
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Citations
... If direct combustion is selected as a technique for thermochemical conversion, then it is only feasible with biomass material that has a moisture content of less than 50% [11]. Many researchers have tried to address this inherent drawback [12,13,14,15,16,17]. Although water removal from algae biomass is yet to achieve an economically reasonable cost, studying the high-quality and valuable fuels generated from microalgae species is still beneficial. ...
The thermal decomposition of the microalgae Spirulina platensis, synthetic wastes, and their blends under an oxidative atmosphere and their kinetic parameters were investigated using a thermogravimetric analyzer. Three stages were observed during the combustion of the blended fuels, and two distinct peaks occurred in the second stage. A kinetic analysis during combustion was studied according to the fitting method proposed by Coats-Redfern and Horowitz-Metzger. The addition of the microalgae to the synthetic waste led to an increase in the apparent activation energies in Zone I in the second stage, whereas an increasing proportion of the microalgae in the blends resulted in decreasing apparent activation energies in Zone II in the second stage.
... In this study, the algal biomasses obtained have calorific values (Table 2) quite similar to that observed for sugarcane bagasse, which is the usual source of biomass for energy cogeneration in ethanol plants (Dias et al., 2011). However, it is important to highlight that the high water content of algal biomasses can represent a major obstruction for its utilization (Jin et al., 2014). Considering that an algal biomass contains up to 60% of water, the specific heat capacity and latent heat of vaporization of water must be considered. ...
... Furthermore, others factors such as boiler efficiency and steam cycle efficiency, influence the overall efficiency of converting biomass energy in electricity (Luk et al., 2013). Accordingly, the overall energy efficiency obtained from Jin et al. (2014) when using algal biomasses for power generation was around 30%. Therefore, future studies focusing on techno-economic analyzes of the whole process, including the kinetic modelling of microalgae growth, are required to provide critical data on economic and environmental sustainability of this alternative. ...
Sugarcane ethanol is produced at large scale generating wastes that could be used for microalgae biomass production in a biorefinery strategy. In this study, forty microalgae strains were screened for growth in sugarcane vinasse at different concentrations. Two microalgae strains, Micractinium sp. Embrapa|LBA32 and C. biconvexa Embrapa|LBA40, presented vigorous growth in a light-dependent manner even in undiluted vinasse under non-axenic conditions. Microalgae strains presented higher biomass productivity in vinasse-based media compared to standard Bold's Basal Medium in cultures performed using 15L airlift flat plate photobioreactors. Chemical composition analyses showed that proteins and carbohydrates comprise the major fractions of algal biomass. Glucose was the main monosaccharide detected, ranging from 46% to 76% of the total carbohydrates content according to the strain and culture media used. This research highlights the potential of using residues derived from ethanol plants to cultivate microalgae for the production of energy and bioproducts.
The aim of the present work was to develop a transient mathematical model focused on microalgae biomass drying, considering two phases: solid (wet biomass) and gas (drying air). Mass and thermal energy balances were written for each phase producing a system of ordinary differential equations (ODE). The solution of the ODE set delivers the temperature and air humidity ratio and biomass profiles with respect to time. The numerical results were directly compared with temperature experimental measurements—for both phases—and with the biomass humidity content. Data from experiment 1 were used to carry out the mathematical model adjustment, whereas data from experiment 2 were used for the experimental validation of the model. The model was adjusted by proposing a new correlation for the mass transfer coefficient and by calibrating the heat transfer coefficient. The transient numerical results were in good quantitative and qualitative agreement with the experimental results, ie, within the experimental error bars. Then the experimentally validated mathematical model was utilized to optimize the following parameters: (i) the electric heater power ( equation/er4481-math-0001.png) and the dry air mass flow rate ( equation/er4481-math-0002.png) and (ii) the convection oven length to width ratio (L/W). The goal was to minimize system energy consumption (objective function). The optimization procedure was subject to the following physical constraints: (i) fixed convection oven total volume and (ii) fixed biomass and drying air contact surface area. For the oven original geometry, equation/er4481-math-0003.png = 3.0 kW and equation/er4481-math-0004.png = 9 g s⁻¹ were numerically found for minimum energy consumption, so that 36.9% and 43.5% energy consumption decreases were obtained, respectively, in comparison with the measurements of experiment 1. Next, the numerical geometric optimization found (L/W)opt = 9, with equation/er4481-math-0005.png and equation/er4481-math-0006.png, which was capable to reach a 51.6% energy consumption reduction in comparison with the original system tested in experiment 1. The novelty of this work consists of the development and experimental validation of a physically based microalgae biomass drying mathematical model, ie, instead of using empirical correlations to predict the drying time and temperature profiles and then minimize system energy consumption. Therefore, the results show that it is reasonable to state that the model could be used to design, control, and optimize drying systems with configurations similar to the one analyzed in this study.
