Downdraft Fixed-bed Gasifier Research Articles

Numerical investigation to predict the impact of pre-heated air on the tar formation of cocoa pod husk gasification in a fixed bed downdraft gasifier

Tar production is a critical aspect of gasification thermochemistry, and it hinders the widening of biofuel utilisation in several applications. Both the gasifier configuration and the operating conditions influence the quantity of tar in PG. Since temperature plays a major role, this study examines the performance parameters of a gasifier across a spectrum of input air temperatures, from 27 to 627 °C, utilising computational fluid dynamics with species transport and porous media models. Since the deviation of numerical predictions from experimental results is within 10 %, the model's validity is confirmed. CO and H2 gas production increased from 19.23 % to 27.12 % and 9.23 %–16.2 %, respectively, over the tested air temperature range; however, the variation in methane content was not significant. Furthermore, the higher heating values of PG and cold gas efficiency were found to be 5–6.8 MJ/Nm3 and 65–69 %, respectively. The study also investigates reaction rates for gasification, combustion, and volatiles' breakdown under various operating conditions. Among the tar species studied, benzene is the most concentrated at 1.6 g/Nm3, followed by toluene at 0.9 g/Nm3, with naphthalene and phenol present in comparatively smaller amounts. Furthermore, the research indicates that an appropriate temperature of gasifying medium can control tar in PG.

Enhancement of H2 production via catalytic steam gasification of food waste as feedstock and its ash as a support and promoter for Ni catalyst

A novel Ni-based catalyst was prepared with 5% and 10% loading of Ni on food waste ash, and then it was characterized using various physico-chemical methods. Thereafter, the steam gasification experiments were conducted at 850 °C and a steam flow rate (SFR) of 0.75 mL/min in a downdraft fixed bed gasifier. The gasification results showed that a 5% Ni-loaded catalyst was more effective than 10% in enhancing the syngas production with a high hydrogen fraction. It was found that the use of this catalyst increased the syngas yield significantly to 1.8 m3/kg on increasing the catalyst content in feedstock to 50%. Additionally, the hydrogen fraction in syngas increased to 71% which, together with higher syngas yield, increased the hydrogen yield by almost 100%. Furthermore, the performance parameters for gasification, such as carbon conversion efficiency (CCE) and cold gas efficiency (CGE), were also found to be highest at 50% catalyst content of 5% Ni-loaded catalyst in the feedstock.

Syngas-Enriched hydrogen production via catalytic gasification of water hyacinth using renewable palm kernel shell hydrochar

Syngas produced from biomass gasification has emerged as a highly promising substitute for conventional fossil fuel, catering to various industrial applications while ensuring minimal greenhouse gas emissions. Water hyacinth (WH) has been a major concern due to its invasive nature and uncontrollable growth which impedes aquatic growth and urban management. Fortunately, WH is a potential biomass feedstock due to the comparable cellulose and hemicellulose contents alongside high carbon content and high calorific value which reflects good biofuel properties. Therefore, this study aims to investigate the conversion of WH biomass via catalytic air gasification for syngas-enriched hydrogen production using palm kernel shell hydrochar (PKSH). A parametric study was conducted in a lab-scale fixed-bed downdraft gasifier based on the response surface methodology coupled with Box-Behnken design (RSM-BBD). The combined interaction effects of the influencing parameters investigated are temperature (600–800 °C), biomass particle size (2–6 mm), catalyst loading (0–10 wt%), and air flow rate (1–3 L/min). Temperature was revealed to be the primary factor with significant influence on the H2 and CO output. Maximum syngas (30.09 vol%) compositions of 11.14 vol% H2 and 18.95 vol% CO were obtained at 800 °C with a particle size of 6 mm and air flow rate of 2 L/min alongside 5 wt% PKSH catalyst loading.

CFD Simulation of Air-Piloted Downdraft Gasification Process: A Comparative Study Between Coal and Palm Kernel Shell as Feedstock

A fixed bed downdraft gasifier model based on computational fluid dynamic (CFD) framework was developed to investigate the influence of feedstock (palm kernel shell [PKS] and coal) on the quality of syngas produced via the gasification process. Euler–Euler approach was utilized in this study to describe the gas and solid phases. Realizable k-ε turbulence model was used to evaluate the constitutive properties of the dispersed phase and the gas phase behavior. This simulation model was validated by comparing the syngas composition of gasification simulation of coal with previous research, which yielded the overall accuracy result of 83.2%. This study also highlighted that PKS gasification produced 53.74% and 90.51% higher composition of H2and CO respectively as compared to coal gasification. Whereas coal gasification produced 81.35%, 71.31% and 52.29% higher composition of CH4, H2O and CO2respectively as compared to PKS gasification. Hence, PKS produced 66.2% higher combustible gas of H2and CO than coal. PKS is thus considered as a potential renewable feedstock for gasification process as an alternative to the non-renewable coal. In addition, PKS gasification produced 52.29% lesser composition of CO2as compared to coal gasification.

UTILIZATION OF SYNTHESIS GAS GENERATED FROM AGRICULTURAL WASTE AS CLEAN SUSTAINABLE FUEL

Increased energy source demand has been the current driver of Malaysia’s economic growth. Renewable energy is therefore included in Malaysia’s energy policy to diversify its energy resources. With 77% of Malaysia’s land directed for agriculture – particularly for palm oil plantation, biomass from agriculture industries is thus considered as a viable energy resource. In addition to palm oil plantation, 18.56 million hectares of Malaysia’s tropical forest contributed substantial wood waste from logging activity. Through gasification, these resources can produce syngas. This paper aims to demonstrate the potential of palm kernel shells (PKS) and wood waste (WW) to generate syngas using a downdraft fixed bed gasifier, which has a suitable oxidation zone temperature to support syngas production. Results showed that PKS and WW syngas consisted of 94.93% and 97.92% carbon monoxide (CO) respectively with low hydrogen (H2) gas contents. The lower heating values (LHV) from PKS and WW are 10.68 MJ/kg and 10.26 MJ/kg, respectively. It can be concluded that agricultural wastes such as PKS and WW had shown high potential to become an alternative source of energy in the form of syngas.

Experimental assessment of a pilot-scale gasification plant fueled with olive pomace pellets for combined power, heat and biochar production

This research work examines the performance of an experimental gasification plant fueled with exhausted olive pomace pellets for the concurrent production of electricity, heat and biochar in the olive oil industry. The gasification plant consists of an air-blown downdraft fixed-bed gasifier that generates a lean fuel gas, termed producer gas, in a self-sustaining autothermal process. After conditioning of the producer gas in a cooling and cleaning unit, a four-stroke spark-ignition engine coupled to an electric generator is eventually used as power generation unit. An extensive experimental assessment of this facility was performed under partial and nominal load operation and was supplemented by a physicochemical analysis of the carbonaceous solid material discharged from the gasifier. The mass and energy balances of the gasification plant were calculated, including the carbon conversion efficiency and diverse energy conversion efficiencies. The results revealed an overall stable operation of the gasification plant in terms of composition and heating value of the producer gas and cogenerative production of electricity and heat in the engine–generator set. Under nominal operating conditions, the net electrical efficiency of the gasification plant was 12%–13%, with an average carbon conversion efficiency of the biomass feedstock into producer gas just above 80% and an average cold gas efficiency close to 70%.

A novel reutilization of ash from biomass gasification process: Feasibility and products improvement analysis

Due to the significant growth of the biomass gasification industry, management and disposal of ash has become one of the major environmental issues. This work proposed an innovative strategy that reutilizes ash into gasification process based on its potential catalysis to improve gas products. Reutilization of ash from corn straw (CS) air gasification in a downdraft fixed-bed gasifier was conducted for a feasibility analysis. The effect of ash loading rates (2 wt%, 5 wt%, 10 wt%, 15 wt%, and 20 wt%) on gasification performance were evaluated for an optimal condition analysis. Ash reutilization was proved to be feasible and able to achieve dual objective of improving gas product quality and reducing SO2 release. Results revealed that loading ash exhibited catalysis promoting CO formation, which correlated with the metal active sites provided by the ash and led to an improvement in dry or/and steam reforming. H2 production was also improved. These positive effects increased as ash loading rates increased, and maximum CO and H2 content (19.97 vol% and 15.72 vol%) were achieved at the ash loading rate of 10 wt%. Accordingly, the maximum LHV of gas products (6.47 MJ/Nm3) and the minimum tar content (3.62 g/Nm3) were obtained. While excess ash (loading rate > 10 wt%) showed unsatisfactory performance, even being far behind CS gasification without ash addition. Due to containing CaO, gasification ash showed SO2 capture capacity by forming CaSO4. This reaction competed with the concurrent CaO carbonation, whereas the latter was the priority. The properties of by-products (regenerated ash) were evaluated for overall economic benefits, and the results indicated that it had a high fertilizer potential. These results seemed to be interesting and valuable for ash utilization and effective gasification.

High-Ash Low-Rank Coal Gasification: Process Modeling and Multiobjective Optimization

The diversification of coal for its sustainable utilization in producing liquid transportation fuel is inevitable in countries with huge coal reserves. Gasification has been contemplated as one of the most promising thermochemical routes to convert coal into high-quality syngas, which can be utilized to produce liquid hydrocarbons through catalytic Fischer–Tropsch (F-T) synthesis. Liquid transportation fuel production through coal gasification could help deal with environmental challenges and renewable energy development. The present study aims to develop an equilibrium model of a downdraft fixed-bed gasifier using Aspen Plus simulator to predict the syngas compositions obtained from the gasification of high-ash low-rank coal at different operating conditions. Air is used as a gasifying agent in the present study. The model validation is done using published experimental and simulation results from previous investigations. The sensitivity analysis is done to observe the influence of the major operating parameters, such as equivalence ratio (ER), gasification temperature, and moisture content (MC), on the performance of the CL-RMC concerning syngas generation. The gasification performance of CL-RMC is analyzed by defining various performance parameters such as syngas composition, hydrogen-to-carbon monoxide (H2/CO), molar ratio, syngas yield (YSyngas), the lower heating value of syngas (LHVSyngas), cold gas efficiency (CGE), and carbon conversion efficiency (CCE). The combined effects of the major operating parameters are studied through the response surface methodology (RSM) using the design of experiments. The optimized condition of the major operational parameters is determined for a target value of a H2/CO molar ratio of 1 and the maximum CGE and CCE using the multiobjective optimization approach. The high-degree accurate regression model equations were generated for the H2/CO molar ratio, CGE, and CCE using the variance analysis (ANOVA) tool. The optimal conditions of the major operating parameters, i.e., ER, gasification temperature, MC for the H2/CO molar ratio of 1, and the maximum CGE and CCE, are found to be 0.5, 655 °C, and 16.36 wt %, respectively. The corresponding optimal values of CGE and CCE are obtained as 22 and 16.36%, respectively, with a cumulative composite desirability value of 0.7348. The findings of the present investigation can be decisive for future developmental projects in countries concerning the utilization of high-ash low-rank coal in liquid fuel production through the gasification route.

Experimental assessment of producer gas generation using agricultural and forestry residues in a fixed bed downdraft gasifier

The gasification of biomass waste integrated with thermal usage and power generation is a sustainable approach to generate energy. Present work focuses on operational assessment of an open-top downdraft gasifier at different flow rates of 10.5 and 12.5 g/s using corn cob and eucalyptus wood waste as feedstocks. Gasification characteristics (performance and syngas parameters), morphological characteristics (X-ray Diffraction, Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy), and thermogravimetric analysis are performed and analysed. The results indicate that values of the lowest hydrogen and carbon monoxide mole fractions, for corncob are 10.81 and 10.11 at the equivalence ratio (ER) of 0.278 and moisture content of 10%. Whereas the highest mole fraction of hydrogen and carbon monoxide for eucalyptus in the producer gas are 14.1 and 12.58 at ER of 0.125 and moisture of 15%. The syngas obtained from eucalyptus wood waste was better in terms of hydrogen content as compared to that from corn cob feedstock as the future vies greater role for hydrogen based fuels.

Investigation of factors affecting performance of a downdraft fixed bed gasifier using optimized MLP neural networks approach

Biomass gasification will be a competitive renewable technology to meet the world's energy demand in the near future. However, extremely time-consuming and costly experimental investigations are still required to achieve the best gasification performance. Machine learning through artificial neural networks can be considered as a convenient and low-cost tool for predicting and optimizing gasification conditions. In this paper, MLP neural network was used to develop a predictive model for the fixed bed gasification properties. Several MLP models were developed to predict the composition of the produced gas and the lower heating value based on the physicochemical composition of the biomass and the reactor operating conditions. The results showed that the MLP architecture with the Levenberg-Marquardt algorithm by considering the range of 47 to 57 neurons in the hidden layer and the tansig activation function had reasonable accuracy in predicting the outputs. Performance of the MLP proposed model showed good agreement between the output and target values with a coefficient of determination of R2 > 0.952, root mean squared error, RMSE < 0.83, and relative root mean squared error, rRMSE < 6.5 %. In addition, according to the results obtained, the MLP indicated the highest precision to model the fixed bed gasification over the other methods. Finally, after the implementation of the model, the sensitivity analysis of input data on output data was performed. The modeling results of this study showed that the MLP model can effectively replace the costly experimental tests to study the gasification process.

Gasification of Biowaste Based on Validated Computational Simulations: A Circular Economy Model to Handle Poultry Litter Waste

Converting waste biomass resources through downdraft gasification can generate a producer gas for a combined heat and power unit. The study includes feedstock analysis, process modelling using ECLIPSE simulation software, and experimental analysis of materials in a pilot-scale fixed-bed downdraft gasifier. Anaerobic digestate and miscanthus were investigated for comparing the gasification potential of poultry litter as an energy source. Models validated through experimental analysis were applied to a case study based on a typical poultry farm in Northern Ireland.; Results found producer gas with a lower heating value up to 4.15 MJ/Nm3 can be generated. Sufficient poultry waste is generated on-site to produce the required heat and electricity for each shed, allowing the farm to switch from fossil fuels to a local renewable resource and addressing the waste disposal issue.; Downdraft gasification coupled with cogeneration could have a payback period of 4–5 years given the correct conditions. The net present value is positive for all technologies considered (i.e. internal combustion engine and the Organic Rankine cycle combined heat and power unit) under different subsidies, showing the economic viability of the solution. The break-even selling price could be lower than the current grid electricity selling price (£120/MWh) when incentives such as: (i) avoiding disposal cost of £30/tonne, (ii) selling the biochar by-product at £200/tonne and (iii) fuel displacement costs of 1.5p/kWh are considered.Graphical abstract

An Investigation on Gasification Conversion of Municipal Solid Waste Using Fixed Bed Downdraft: Study Case of Final Processing Site TPA Putri Cempo Surakarta

The municipal solid waste (MSW) gasifier is one of the promising technologies to fulfill the energy demand of TPA Putri Cempo Surakarta. Municipal solid waste gasification is a chemical process that converts solid Municipal solid waste into useful, convenient gaseous fuel. According to the government program in presidential regulation number 35 of 2018, the acceleration of waste processing development into electric energy based on environmentally friendly technology needs to be developed. One of the technologies to convert waste into renewable energy is to use thermochemical processes of gasification. The aim of this paper is to investigate the conversion of municipal solid waste gasification (MSW) using a fixed bed downdraft gasifier by circulating the mass balance of municipal solid waste (MSW) to be converted into syngas with a variation of air-fuel ratio (AFR) of 0.1 to 1.0 and gasifier temperature at 500 – 1000°C. The result showed that the fixed bed downdraft gasifier produced syngas with the composition of CO (24.78%), CO2 (18.65%), H2 (15.6%), and CH4 (4.06%), with an AFR of 0.3 at a gasification temperature of 600°C.both.

A hybrid intelligent model to predict the hydrogen concentration in the producer gas from a downdraft gasifier

This research work presents an artificial intelligence approach to predicting the hydrogen concentration in the producer gas from biomass gasification. An experimental gasification plant consisting of an air-blown downdraft fixed-bed gasifier fueled with exhausted olive pomace pellets and a producer gas conditioning unit was used to collect the whole dataset. During an extensive experimental campaign, the producer gas volumetric composition was measured and recorded with a portable syngas analyzer at a constant time step of 10 seconds. The resulting dataset comprises nearly 75 hours of plant operation in total. A hybrid intelligent model was developed with the aim of performing fault detection in measuring the hydrogen concentration in the producer gas and still provide reliable values in the event of malfunction. The best performing hybrid model comprises six local internal submodels that combine artificial neural networks and support vector machines for regression. The results are remarkably satisfactory, with a mean absolute prediction error of only 0.134% by volume. Accordingly, the developed model could be used as a virtual sensor to support or even avoid the need for a real sensor that is specific for measuring the hydrogen concentration in the producer gas.

Exergy sustainability analysis of biomass gasification: a critical review

Biomass gasification technology is a promising process to produce a stable gas with a wide range of applications, from direct use to the synthesis of value-added biochemicals and biofuels. Due to the high capital/operating costs of the technology and the necessity for prudent management of thermal energy exchanges in the biomass gasification process, it is important to use advanced sustainability metrics to ensure that environmental and other sustainability factors are addressed beneficially. Consequently, various engineering techniques are being used to make decisions on endogenous and exogenous parameters of biomass gasification processes to find the most efficient, viable, and sustainable operations and conditions. Among available approaches, exergy methods have attracted much attention due to their scientific rigor in accounting for the performance, cost, and environmental impact of biomass gasification systems. Therefore, this review is devoted to critically reviewing and numerically scrutinizing the use of exergy methods in analyzing biomass gasification systems. First, a bibliometric analysis is conducted to systematically identify research themes and trends in exergy-based sustainability assessments of biomass gasification systems. Then, the effects of biomass composition, reactor type, gasifying agent, and operating parameters on the exergy efficiency of the process are thoroughly investigated and mechanistically discussed. Unlike oxygen, nitrogen, and ash contents of biomass, the exergy efficiency of the gasification process is positively correlated with the carbon and hydrogen contents of biomass. A mixed gasifying medium (CO2 and steam) provides higher exergy efficiency values. The downdraft fixed-bed gasifier exhibits the highest exergy efficiency among biomass gasification systems. Finally, opportunities and limitations of exergy methods for analyzing sustainability aspects of biomass gasification systems are outlined to guide future research in this domain.

Study on physicochemical characteristics, solidification and utilisation of tannery sludge gasification ash

Gasification is an attractive method for tannery sludge (TS) disposal because of its advantages: volume reduction, stabilisation, harmlessness, and energy recovery. TS reduction ash (AR) and TS oxidation ash (AO), simulated from a downdraft fixed bed gasifier (DFBG) and an updraft fixed bed gasifier (UFBG), were investigated on their physicochemical characteristics, solidification behaviour, and value-added utilisation. Results showed that the main mineral matters in AR and AO consisted of Fe-oxids and Fe–Cr compounds, and the DFBG was more suitable for TS gasification than the UFBG because of the lower content of Cr(Ⅵ) in AR. With the addition of waste glass bottles (WGB), the ash fusion temperatures (AFTs) and leaching concentrations of heavy metals in AR and AO decreased significantly, and the heavy metals in AR and AO were successfully immobilised by the wrapping effect of the molten WGB. Moreover, gasification ash, as an auxiliary material for rock wool, reduced the AFTs and viscosity coefficient of the main chemical compositions in rock wool. With the addition of AR, the occurrence of Fe-containing compounds and the extremely low risk of leaching toxicity of heavy metals were observed. The maximum addition proportion of gasification ash was dependent on the maximum content of Fe2O3 allowed in the raw materials of rock wool, and its addition ratio must be below 15%.

Investigation of relative influence of process variables in a 10-kW downdraft fixed-bed gasifier with ANN models

Biomass gasification is considered among promising solutions for renewable energy generation. The process converts the biomass, such as rice husk, to synthetic gas (syngas). It produces CO, CO2, CH4, and H2 gas that are useful for internal combustion engines. The process is complicated to control. Hence, a thorough knowledge of this process is needed. One of the approaches to reveal the control parameters of the gasifier is using an artificial neural network (ANN). In this research, an ANN model is deployed from experiments that measure combustion temperature, intake, and discharge airflow rate as input variables. The output of this model is to predict the increase of combustion temperature in the reactor as this parameter is crucial for the design of an automated control system. From the two experiments, the models produce satisfying accuracy (R2 = 0.832 and 0.911) and relatively low errors (RMSE values of 0.250 and 0.098). The neural network itself is used to analyze the significant control parameters by the permutation importance method.

Simulation on co-gasification of bituminous coal and industrial sludge in a downdraft fixed bed gasifier coupling with sensible heat recovery, and potential application in sludge-to-energy

The co-gasification of bituminous coal (BC) and industrial sludge (IS) in the downdraft fixed bed gasifier (DFBG) was simulated by a validated steady-state model structured using the Aspen Plus software. The gasification process was decoupled into the drying, pyrolysis, partial oxidation, and reforming and reduction, and then modeled. Furthermore, the sensible heat recovery of syngas was also considered to realize the energy optimization of DFBG gasification system. The sensitivity analysis was performed to investigate the influences of the gasification temperature, air equivalent ratio, and steam to BC-IS blends ratio (S/BC-IS) on the co-gasification characteristics. The energy distributions of the whole process were completed by calculating energy input and output. Results showed that, boosting gasification temperature could improve the syngas content and gasification performance. However, as air equivalent ratio increased, the H2 and CO contents, and gasification performance constantly reduced. A higher S/BC-IS was beneficial for H2 production, but impaired CO content and cold gas efficiency. In addition, the calculations of energy balance indicated that the best cold gas efficiency of the blends could be obtained when the BC blending ratio was 0.7.

An investigation for improving dry anaerobic digestion of municipal solid wastes by adding biochar derived from gasification of wood pellets

In this study, the effect of biochar addition derived from a downdraft fixed-bed gasifier on the performances of dry anaerobic digestion of the Organic Fraction of Municipal Solid Waste (OFMSW) was investigated at a high organic load of (1) the source segregated OFMSW (16 and 26% TS) and (2) the source segregated OFMSW replaced with 15% garden waste (22.2% TS). Adding biochar effectively enhanced the rate and yield of biomethane (up to 36.6%), controlled acidification, and shortened lag phase in both feedstocks at high organic loads up to 136.9 gVS/L. Execution of dry anaerobic digestion for source-separated OFMSW without acidification can only be achieved by more than 30 g/L biochar dosage, which is better to run in a semi-solid state (16% TS). However, the synergistic effects at higher biochar doses were not palpable. OFMSW with a higher C/N ratio yielded more limited benefits, as inhibitory volatile fatty acids were further controlled in the early days. This study could promise the integration of gasification and dry anaerobic digestion to enhance the biogas production efficiency at high organic loads, although more researches should be done under continuous conditions.

Enhancement of syngas production via co-gasification and renewable densified fuels (RDF) in an open-top downdraft gasifier: Case study of Indonesian waste

The global increase in world population is followed with a rise in waste generation and energy needs in various sectors. Organic waste, also known as biomass, is the most substantial contribution of the waste generation and it also can be utilized in energy generation. Therefore, the purpose of this study is to analyze the syngas production from co-gasification using Renewable Densified Fuels (RDF) with gasification temperature, lower heating and gas emission values, on the performance of the biomass co-gasification process in an open-top downdraft fixed bed gasifier. In this study organic waste used woods, coconut fibers and rice husks in pellets to blend the compositions of raw materials during the co-gasification process. The method used is the co-gasification technique with feed pellets WCF (wood-coconut fiber) and RH (rice husk) in various compositions, for example: 100% WCF, with 0% of RH, 75 WCF: 25 RH, 50 WCF: 50RH, 25 WCF: 75RH and all 100% RH with 0WCF. Furthermore, the syngas testing was directly measured on the burner with TCD type Shimadzu 8A gas chromatography. The result showed that the highest reactor temperature in the pyrolysis zone is 700 °C–900 °C which was significantly stable at 800 °C with oxidation temperature of 1000 °C–1100 °C. Furthermore, the result of the synthetic gas showed that the highest lower heating value of 100% WCF pellet composition at 3.582 kJ/Nm3 and lower heating value of RDF blending composition (75:25) at 3.392 kJ/Nm3. The increase in pellet fuels also leads to a rise in the LHV syngas value. These results produced a visually low tar content and ash particles in all compositions by approximately 30–35% of the initial mass, with the lowest ash in 100% WCF pellets composition at 0.25 g.

A novel biomass gasification micro-cogeneration plant: Experimental and numerical analysis

This work presents a numerical model developed to predict the behaviour of a real micro-cogeneration biomass gasification system, based on a fixed-bed downdraft gasifier, coupled with a spark-ignition internal combustion engine. The model developed by the authors takes into account all the thermo-physical processes occurring in the whole system: gasification, cleaning, combustion and heat recovery. The numerical model is based on the Gibbs free energy minimization, applying the restricted equilibrium method. The model has been validated with the experimental data collected during an extensive experimental campaign, and a good agreement between measured data and predicted results is obtained. The present validated model has proved to be a useful tool for analyzing the performance of real micro-CHP plants. The global electrical and thermal efficiencies predicted by the model are 19.9% and 17.8%, while the measured values are 19.5% and 21.7%, respectively. Some parametric analyses have been carried out in order to assess the performance of the system as a function of the main gasifier and engine parameters, and to predict the behaviour of the system.