DOI: 10.3303/CET2292048 Paper Received: 31 January 2022; Revised: 16 March 2022; Accepted: 22 April 2022 Please cite this article as: Carotenuto A., Di Fraia S., Massarotti N., Rakib Uddin M., Vanoli L., 2022, Combined Heat and Power Generation from Mechanically Dewatered Sewage Sludge: Numerical Modelling , Chemical Engineering Transactions, 92, 283-288 DOI:10.3303/CET2292048 CHEMICAL ENGINEERING TRANSACTIONS VOL. 92, 2022 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Rubens Maciel Filho, Eliseo Ranzi, Leonardo Tognotti Copyright © 2022, AIDIC Servizi S.r.l. ISBN 978-88-95608-90-7; ISSN 2283-9216 Combined Heat and Power Generation from Mechanically Dewatered Sewage Sludge: Numerical Modelling Alberto Carotenuto, Simona Di Fraia, Nicola Massarotti, Mohammad Rakib Uddin*, Laura Vanoli Dipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope”, Napoli–80143, Italy mohammadrakib.uddin001@studenti.uniparthenope.it In the present study, a system for Combined Heat and Power (CHP) generation from mechanically dewatered Sewage Sludge (SS) is numerically analyzed through Aspen Plus software. The proposed system is composed of three consecutive processes: drying, gasification, and energy generation through an internal combustion engine. The gasification model is calibrated by applying a restricted chemical equilibrium approach and validated for four experimental outcomes available in the literature. Optimum gasification temperature (900 °C) is identified at an ideal equivalence ratio which is the ratio between actual air fed to the reactor to the stoichiometric air required for complete combustion of 0.2 predicted in a previous study through a sensitivity analysis. The CHP generation potentiality is assessed, finding 0.89 kWh/kg SS as Dry Solid (DS) of electrical and 1.67 kWh/kg of SS as DS of thermal energy. This allows supplying around 50 % of electrical energy required to run the wastewater treatment plant and is sufficient to complete the thermal drying of mechanically dewatered SS. 1. Introduction Energy recovery from mechanically dewatered Sewage Sludge (SS) as Combined Heat and Power (CHP) through gasification integrated with an Internal Combustion Engine (ICE) offers a high recovery efficiency, reduces the greenhouse gas emission, and increases renewable energy production (Zhang et al., 2019). Generated electrical energy can be used to run WasteWater Treatment Plants (WWTPs) and thermal energy to reduce the moisture content of mechanically dewatered SS from around 70 to less than 10 % as required for the gasification treatment (Di Fraia et al., 2016; Abdelrahim et al., 2020). The thermal drying process of mechanically dewatered SS is energy-intensive, with a demand of around 0.85 kWh/kg of evaporated water (Bennamoun et al., 2013). Huang et al. (2016) evaluated the average surface heat and mass transfer coefficients by varying the operating condition of air temperature (100–160 °C) and speed (0.6–2.0 m/s) for SS drying in a convective dryer. Bennamoun et al. (2016) identified optimum operating conditions (air temperature = 140 °C, velocity = 2 m/s, and air humidity = 0.05 kgwater/kgDry air) for drying of mechanically dewatered SS in a convective dryer, estimating an exergy efficiency of 90 %. The product generated through the gasification is syngas, a mixture of CO, H₂, CO₂, CH₄, moisture, tar, and other lighter hydrocarbons that may be used for CHP production, district heating, and chemical synthesis (Abdelrahim et al., 2020). The composition of syngas generated through air-gasification of SS depends on the characteristics of SS and the operating conditions of temperature and Equivalence Ratio (ER) (Di Fraia et al., 2021). de Andres et al. (2011) performed 19 tests to recognize optimum temperature (850 °C) and ER (0.2) during syngas generation from SS in a bubbling Fluidized Bed Reactor (FBR). Jeong et al. (2019) completed 7 experiments during syngas generation from SS through co-gasification with coal by using air in a two-stage FBR to detect optimum temperature (811 °C) and ER (0.3). Identification of optimum operating parameters for gasification through an experimental campaign is time- consuming and costly. Numerical modelling based on experimental data, i.e. through the simulation software Aspen Plus, to identify the optimum operating parameters for SS gasification can save time and cost significantly (Abdelrahim et al., 2020; Di Fraia et al., 2021). 283 Model development on Aspen Plus for operating parameters optimization during air-gasification of SS is limited (Abdelrahim et al., 2020; Migliaccio et al., 2021). Abdelrahim et al. (2020) predicted as optimum operating parameters a temperature of 780 °C and an ER of 0.3 whereas Migliaccio et al. (2021) estimated identical ideal temperatures (850 °C) and ER (0.25) for syngas generation from two different SS. There are limited research articles available in the literature on Aspen Plus model development related to CHP generation from biomass (François et al., 2012; Villarini et al., 2019) and only two from SS through gasification integrated with an ICE system (Di Fraia et al., 2021; Brachi et al., 2022). Francois et al. (2012) assessed electrical (23 %), thermal (40 %) and cogeneration (67 %) efficiencies for CHP generation from wood. di Fraia et al. (2021) estimated electrical (29.20 %), thermal (45.92 %), and cogeneration (53.10 %) efficiencies during CHP generation from SS whereas Brachi et al. (2022) predicted electrical (19.3 %) and thermal (48.7 %) efficiencies. In the present study, a simulation model is developed to analyse the conversion of mechanically dewatered SS to CHP through three consecutive processes of thermal drying, gasification, and energy generation through an ICE. A convective belt dryer is considered due to its flexibility to manipulate and control (Di Fraia et al., 2016; Huang et al., 2016). The gasification model, based on a restricted chemical equilibrium approach (Abdelrahim et al., 2020; Di Fraia et al., 2021; Migliaccio et al., 2021), is calibrated and validated through the experimental data on syngas generation from SS in a fixed bed gasifier (Werle, 2014). Optimum operating temperature is identified through a sensitivity analysis. Finally, the CHP generation potentiality of SS is evaluated to identify the possible use for wastewater and sludge treatment. 2. Numerical Simulation: CHP from mechanically dewatered SS 2.1 Process flowsheet development The scheme for the proposed plant by connecting the processing unit of the dryer, gasifier, and ICE to generate CHP from mechanically dewatered SS is presented in Figure 1. Figure 1: Flow diagram of the proposed plant for CHP generation from mechanically dewatered SS. A detailed description of simulation related to CHP generation from mechanically dewatered SS through thermal drying, gasification integrated with an ICE is available in the literature (Di Fraia et al., 2016, 2021). ICE system is simulated considering the thermodynamic steps of compression, combustion, and expansion (Villarini, et al., 2019; Di Fraia et al., 2021). The description of the functional activities of each block used from the Aspen Plus library in the proposed plant is depicted in Table 1. 2.2 Model development Thermal Drying: The drying process is simulated to reduce the moisture content of mechanically dewatered SS from 48.72 to 5.53 % based on the following parameters of dryer length 20 m, drying time 3.45 h, heat transfer coefficient of 20.89 Wm-2K-1, critical, and equilibrium moisture content of 0.14 and 0.000984, respectively. Normalized drying rates against normalized moisture content for thermal drying of mechanically dewatered SS at 110 °C are collected from the literature (Huang et al., 2016). Gasification: The gasification process is simulated based on the following simplifying assumptions (Di Fraia et al., 2021): the developed model is kinetic free and zero-dimensional; gasification is completed in steady-state and isothermal condition; volatile products (H₂, CO, CO₂, CH₄, and H₂O) are formed through instantaneous pyrolysis of SS; all gases behave ideally; char is full of carbon and tar formation is neglected as it is ignored on available literature for SS gasification process (Abdelrahim et al., 2020; Di Fraia et al., 2021; Migliaccio et al., 2021). Indeed, tar formation ignorance does not have any impact on the evaluation of the energy recovery potentiality of SS. Gasification model is calibrated to reduce the deviation which is created due to the difference between the syngas composition and LHV (Lower Heating Value) predicted through the developed model and experimental data. It is suggested that the deviation of syngas composition from experimental outcomes should be lower than 284 ±20% to claim the developed model has good agreement with the experimental campaign. This can be achieved by restricting individual gasification reactions to a specific temperature according to equation (1) (Abdelrahim et al., 2020; Di Fraia et al., 2021): 𝑇𝐸𝑞𝑙𝑚 = 𝑇𝐺𝑎𝑠𝑓 + ∆𝑇𝐴𝑝𝑝𝑟 (1) where, 𝑇𝐸𝑞𝑙𝑚 is the equilibrium temperature, 𝑇𝐺𝑎𝑠𝑓 is the gasification temperature and ∆𝑇𝐴𝑝𝑝𝑟 is the limit of gasifier temperature where the reaction is restricted. Characteristics of SS are presented in Table 2. The reactions considered to complete the gasification process simulation are presented in Table 3. The composition of generated syngas at five distinct operating conditions is presented in Table 4 (Werle, 2014). Operating parameters and syngas properties at condition III is used for model calibration by applying a restricted chemical equilibrium approach whereas the remaining four conditions are for validation. During model calibration, ∆𝑇𝐴𝑝𝑝𝑟 is predicted through regression tools available in Aspen Plus by setting a 5% standard deviation (95 % confidence level) from the experimental outcomes and the results are illustrated in Table 5 with a fraction of carbon participating in the gasification process. Table 1. Functional description of unit operation block used in Aspen Plus flowsheet. Process Block Name Function Drying Heater It increases the temperature (110 °C) of incoming air to dry WETSS stream. Convective Dryer It reduces the moisture content of mechanically dewatered SS from 48.72 to 5.53 wt% at 110 °C (Huang et al., 2016). Gasification RYield It completes the decomposition of SS (at 400 °C specifics for pyrolysis) to conventional (C, H₂, N₂, S, Cl₂, F₂) and non-conventional (ash) components based on ultimate analysis (Di Fraia et al., 2021). Separator It separates the decomposed product into three streams: GASFEED (fraction of C, H₂, N₂, S, Cl₂, and F₂), CHAR (fraction of carbon), and C-ASH (ash). RGibbs It completes the combustion of char to supply heat to the gasifier. Heater It increases incoming air temperature to complete the gasification process. RGibbs It completes the gasification reaction by minimizing Gibb's free energy. Heater It increases the ash temperature to equalize with gasification products. Mixer It mixes the gasification products and ash. Cleaning & Cooling SSplit It completes the separation of solid particles from syngas. Heater It reduces the syngas temperature to ambient value (30 °C) through cooling. ICE system Compressor It increases the potential energy of incoming air through pressure raising. RGibbs It completes the combustion of the syngas to generate thermal energy. Turbine It generates mechanical energy from the thermal energy of CMBST stream to produce electricity. Heater It generates thermal energy from the exhaust stream of block TURB. 2.3 Process performance evaluation: Gasification and cogeneration system Gasification process performances are evaluated through the prediction of syngas LHV, Cold Gas Efficiency (CGE), Carbon Conversion Efficiency (CCE), and net power (𝑃𝑛𝑒𝑡 ) available from the gasification products. Syngas LHV depends on composition and corresponds to equation (2) (Zheng et al., 2019). CGE is the ratio of energy content between the gasification products and input and CCE is the ratio of carbon present in the syngas to the reactant, (Jeong et al., 2019). 𝑃𝑛𝑒𝑡 is the difference between the power gain from products and the investment to complete the gasification process. 𝐿𝐻𝑉𝑠𝑦𝑛𝑔𝑎𝑠 (𝑀𝐽 𝑁𝑚 3)⁄ = 0.108𝑦𝐻2 + 0.126𝑦𝐶𝑂 + 0.358𝑦𝐶𝐻4 (2) where, 𝑦𝐻2 , 𝑦𝐶𝑂 , and 𝑦𝐶𝐻4 denote the volume fraction of H₂, CO, and CH₄ present in syngas, respectively. Cogeneration process performances are characterized by evaluating electrical and thermal efficiencies of the engine as well as the efficiency of the system (𝜂𝑠𝑦𝑠 ). For the sake of completeness: 𝜂𝑠𝑦𝑠 (%) = 𝑁𝑇𝑈𝑅𝐵 +𝑄𝐸𝑋𝐶𝐻 +𝑄𝐸𝑋 𝐿𝐻𝑉𝑆𝑆 . �̇�𝑆𝑆+�̇�𝐼𝑁𝑃𝑈𝑇 ∙ 100 (3) where, 𝑁𝑇𝑈𝑅𝐵 denotes effective power obtained from the model of the ICE, 𝑄𝐸𝑋𝐶𝐻 is the heat available during the cooling of syngas before entering the ICE, 𝑄𝐸𝑋 denotes the available thermal power generated from the cooling of turbine exhausts to usable temperature (80 °C) (Di Fraia et al., 2021) and �̇�𝐼𝑁𝑃𝑈𝑇 is the rate of power supplied associated with the RGibbs reactor including air preheating. 285 2.4 Operating parameters for cogeneration process simulation The operating conditions required to complete the cogeneration process simulation are collected from literature and are presented in Table 6 (Di Fraia et al., 2021). Table 2. Characteristics of thermally dried SS (Werle, 2014). Proximate analysis (wt%) Ultimate analysis (wt%) Moisture 5.30 C 31.79 H₂ 4.36 Volatile matter 51.00 N₂ 4.88 S 1.67 Fixed carbon 7.20 F₂ 0.013 Cl₂ 0.22 Ash 36.50 O₂ 20.57 LHV (MJ/kg, d.b) 12.96 *d.b = Dry basis Table 3. List of reactions considered in the gasification model. Rxn Reaction Name of Rxn R1 C + H₂O → H₂ + CO Water-gas R2 C + O₂ → CO₂ Carbon combustion R3 C + 2H₂ → CH₄ Methanation R4 CO + H₂O → H₂ + CO₂ Water Gas Shift R5 C₂H₄ + 3O₂ → 2CO₂ + 2H₂O Ethene combustion R6 C₃H₈ + 5O₂ → 3CO₂ + 4H₂O Propane combustion R7 H₂ + 0.5O₂ → H₂O Hydrogen combustion *Rxn = Reaction Table 4. Overview of gasification conditions and corresponding syngas compositions (Werle, 2014). Test condition I II III IV V Operating Parameters Temperature (°C) 900 920 940 960 980 ER (-) 0.23 SS fed rate (kg/h) 1.0 Air fed rate (kg/h) 1.01 Syngas composition (vol%), (Dry & N₂ free basis) H₂ 12.63 12.95 13.00 13.05 13.00 CO 56.95 57.18 57.40 58.13 58.97 CO₂ 28.47 27.90 27.61 26.69 25.80 CH₄ 1.95 1.97 1.99 2.14 2.23 Table 5. Predicted ∆𝑇𝐴𝑝𝑝𝑟 for each reaction and fraction of carbon participate in the gasification process. Reaction No. ∆𝑇𝐴𝑝𝑝𝑟 (°C) R1 -313.2 R2 -500.0 R3 -485.1 R4 500.0 R5 -500.0 R6 -456.8 R7 -482.0 Fraction of C participating in gasification reaction 0.932 Table 6. Operating parameters for the simulation of the cogeneration system (Di Fraia et al., 2021). Operating conditions Value Operating conditions Value Temperature (incoming syngas to the ICE, °C) 30.0 Isentropic expansion and compression coefficient (%) 90.0 Temperature (incoming air to the compressor, °C) 20.0 Stoichiometric air ratio (-) 3.0 Pressure (fume exit from turbine, bar) 1.0 The pressure of air exit from compressor and combustion chamber (bar) 20.0 Utilization temperature of exhaust fume (°C) 80.0 3. Results and Discussion Thermal Drying: the thermal energy required to complete the drying process is estimated to be 0.83 kWh/kg. Gasification: comparison between the results predicted through the developed model and the experimental campaign available in the literature (Werle, 2014) during calibration and validation is presented in Figure 2. The developed model has a good agreement with the experimental campaign as the deviation of individual components <±15 % with an average value in the range of 6.0 - 11.32 % during model calibration and validation. 3.1 Sensitivity analysis Variation of syngas composition, CCE, CGE, LHV of syngas and 𝑃𝑛𝑒𝑡 with gasification temperature in the range of 700 to 1000 °C at a fixed ER of 0.2 estimated as an optimum value in a previous study carried out by the authors (Di Fraia et al., 2021) is presented in Figure 3. The concentration of H₂ and CO raises continuously with temperature whereas that of CO₂ and C₂H₆ decreases and a slower increase for CH₄ due to the forward movement of endothermic (water-gas and water gas shift) reactions. Combustion reactions present the opposite trend and the concentration of CO₂ and C₂H₆ decreases. H₂ and CO are the major contributor components to syngas LHV (Jeong et al., 2019; Zheng et al., 2019). Consequently, LHV, CGE and 𝑃𝑛𝑒𝑡 increase with 286 temperature. The decrease of carbon content through CO₂ concentration is lower than increment by CO. As a result, CCE increases continuously with temperature. 𝑃𝑛𝑒𝑡 rises with temperature up to 900 °C and afterward decreases due to the increase of required thermal power to complete the gasification process. The increase of available power from 900 to 950 °C is lower compared to the demand and consequently, 𝑃𝑛𝑒𝑡 decreases. Figure 2: Comparison of syngas composition predicted through the developed model with the experimental campaign during (a) Model calibration and (b) Model validation. Based on the current simulation results, 900 °C is the optimum temperature for gasification of SS and afterward is not profitable in terms of net power obtained from the products. The effect of temperature on syngas composition, CCE, CGE, and LHV obtained in the present study is in accordance with the available literature on SS gasification (Abdelrahim et al., 2020; Di Fraia et al., 2021; Migliaccio et al., 2021). 3.2 Cogeneration process performances The potentiality of electrical and thermal power generation from SS is found to be 0.89 kWh/kg SS as DS and 1.67 kWh/kg SS as DS, respectively. The predicted value of CGE, 𝜂𝑠𝑦𝑠, electrical and thermal efficiencies result to be 72.3 %, 67.4 %, 24.8 %, and 46.3 % respectively which are in agreement with those found in the pertinent literature (Di Fraia et al., 2021). Based on the current simulation results it can be said that the generated electrical energy can support around 50 % of the demand specified to run a WWTP considering the energy demand evaluated by the German Ministry of Environment (Capodaglio and Olsson, 2020) and thermal power is sufficient to reduce the moisture content of mechanically dewatered SS from 48.72 to 5.53 % by thermal drying. -20 0 20 40 60 H₂ (vol.%) CO (vol.%) CO₂ (vol.%) CH₄ (vol.%) S y n g a s c o m p o s it io n ( v o l. % ), (D ry & N ₂ fr e e b a s is ) Syngas component Experimental Result Simulation Result Deviation (%) Average Deviation (%) 0 20 40 60 900 920 940 960 980 S y n g a s C o m p o s it io n (v o l. % ), ( D ry & N ₂ fr e e b a s is ) Gasification Temperature (⁰C) H₂: Sim. CO: Sim. CO₂: Sim. CH₄: Sim. H₂: Exp. CO: Exp. CO₂: Exp. CH₄: Exp. 0 20 40 60 700 800 900 1000 S y n g a s C o m p o s it io n (v o l% ), ( D ry & N ₂ fr e e b a s is ) Gasification Temperature (°C) H₂ CO CO₂ CH₄ C₂H₆ 2 2.2 2.4 0 4 8 700 800 900 1000 N e t P o w e r (k W ) S y n g a s L H V ( M J /N m 3 ) Gasification Temperature (°C) LHV Net Power (a) (b) 30 50 70 90 700 800 900 1000 C C E & C G E , (% ) Gasification Temperature (°C) CGE CCE Figure 3: Effect of temperature on (a) syngas composition, (b) CCE and CGE of the gasification process, and (c) Syngas LHV and net power available from the gasification products. (a) (c) (b) 287 4. Conclusion A simulation on Aspen Plus is carried out to analyze the combined heat and power generation potentiality of mechanically dewatered SS. The proposed layout is composed of three consecutive processes: drying followed by gasification and an internal combustion engine. Optimum operating temperature for the gasification of SS is predicted by considering its impact on syngas composition, LHV, CCE, CGE and 𝑃𝑛𝑒𝑡. Temperature rising improves the syngas LHV and gasification process performances. The evaluated combined heat and power generation potentiality from SS obtained in the present analysis highlights that • Around 50 % of electrical energy needed for wastewater treatment • The entire thermal energy required to complete the drying of mechanically dewatered SS as needed for gasification treatment can be produced through the proposed system. Simulation on co-gasification of SS with biomass or wood will be carried out as future research to improve the cogeneration efficiencies predicted in the current study. 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