Ahmad Faizan Sherwani

Grey relational analysis coupled with principal component analysis for optimization of the cyclic parameters of a solar-driven organic Rankine cycle

Purpose The purpose of this paper is to investigate the effect of four controllable parameters (fuel mixture, evaporation bubble point temperature, expander inlet temperature and condensation dew point temperature) of a solar-driven organic Rankine cycle (ORC) on the first-law efficiency, the exergetic efficiency, the exergy destruction and the volume flow ratio (expander outlet/expander inlet). Design/methodology/approach Nine experiments as per Taguchi’s standard L9 orthogonal array were performed on the solar-driven ORC. Subsequently, multi-response optimization was performed using grey relational and principal component analyses. Findings The results revealed that the grey relational analysis along with the principal component analysis is a simple as well as effective method for solving the multi-response optimization problem and it provides the optimal combination of the solar-driven ORC parameters. Further, the analysis of variance was also employed to identify the most significant parameter based on the percentage of contribution of each cyclic parameter. Confirmation tests were performed to check the validity of the results which revealed good agreement between predicted and experimental values of the response variables at optimum combination of the input parameters. The optimal combination of process parameters is the set with A3 (the best fuel mixture in the context of optimal performance is 0.9 percent butane and 0.1 percent pentane by weight), B2 (evaporation bubble point temperature=358 K), C1 (condensation dew point temperature=300 K) and D3 (expander inlet temperature=370 K). Research limitations/implications In this research, the Taguchi-based grey relational analysis coupled with the principal components analysis has been successfully carried out, whereas for any optimized solution, it is required to have a real-time scenario that may be taken into consideration by the application of different soft computing techniques like genetic algorithm, simulated annealing, etc. The results generated are purely based on theoretical modeling, and, for further research, experimental analyses are required to consolidate the generated results. Originality/value This piece of research work will be helpful to users of solar energy, academicians, researchers and other concerned persons, in understanding the importance, severity and benefits obtained by the application, implementation and optimization of the cyclic parameters of the solar-driven ORC.

Taguchi-based combined grey relational and principal component analyses for multi-response optimization of diesel engines

Purpose Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions. Design/methodology/approach To achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis. Findings Results of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings. Practical implications In view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals. Originality/value From the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.

Optimization of diesel engine input parameters for reducing hydrocarbon emission and smoke opacity using Taguchi method and analysis of variance

The aim of this paper is to optimize the input parameters of diesel engine with respect to hydrocarbon emission and smoke opacity through experimentation and Taguchi approach. Four parameters, namely, compression ratio, fuel injection timing, air temperature, and air pressure were varied at five different levels and their effect on hydrocarbon emission and smoke opacity under no load, half load, and full load conditions were recorded. The optimum combination of control/input parameters leading to the optimum values of performance parameters/response variables, were determined using signal-to-noise ratio, analysis of means, and analysis of variance. Confirmation tests were performed to check the validity of the results, which revealed good agreement between the predicted and the experimental values of the response variables at optimum combination of the input parameters.

Thermodynamic analysis of low-grade solar heat source-powered modified organic Rankine cycle using zeotropic mixture (Butane/R1234yf)

ABSTRACT This paper communicates detailed energy and exergy analysis of low-grade energy resource of solar-powered organic Rankine cycle (ORC) integrated with both the internal heat exchanger and open feed water heater, ORC incorporated with the internal heat exchanger, with open feed water heater and basic ORC, respectively. Results indicate that highest first law efficiency (11.9%), exergetic efficiency (51.88%) and lowest exergy destruction (1749 kW) are obtained for ORC integrated with both internal heat exchanger and open feed water heater among other considered ORCs. Moreover, zeotropic mixture (butane/R1234yf) shows better first law and exergetic efficiency and lower exergy destruction than pure fluid.

Thermodynamic analysis of solar power organic Rankine cycle based on experimental data

ABSTRACT In the current work, analytical expressions have been coded in MATLAB 9.0 linked with REFPROP 9.0, for solar-powered ORC system integrated with conventional compound parabolic concentrator using environment-friendly hexane/R1234yf zeotropic mixture to calculate hourly (8 AM to 4 PM) combined performance of solar power ORC based on experimental data. It has been observed that maximum heat gain in the collector is 5.132 × 105 W at 1 PM for the mass fraction (0.7/0.3). Moreover, maximum overall thermal efficiency 17.65% is attained at 1 PM for the mass fraction 0.3/0.7 whereas overall exergetic efficiency 49.23% is achieved at the same time for the mass fraction 0.3/0.7.

Performance evaluation of solar photovoltaic electricity-generating systems: an Indian perspective

ABSTRACT The present work seeks to assess the sustainability of different solar photovoltaic (SPV) electricity-generating systems based upon energy, environment and economics. The sustainability indicators evaluated for energy, environment and economics are electrical output, life-cycle greenhouse gas (GHG) emissions and life-cycle cost of electricity generated per kilowatt hour. The selected SPV-based electricity generation technologies for sustainability evaluation are amorphous, monocrystalline and polycrystalline at different locations and tilt angles across India. For SPV systems, most of the emissions are the result of electricity use during manufacturing. In these cases, an average grid mix for the region of manufacture is typically used to calculate energy use and emissions. Based upon these three indicators, a figure of merit (FM) has been proposed. The results proposed that polycrystalline gives the maximum electrical output, minimum GHG emission, minimum cost and maximum FM at a radiation level of 6 kWh/m2/day with latitude and tilt angle of 34° and 35°, respectively. This work will be helpful to users of solar energy, academicians, researchers and other concerned persons, in understanding the importance, severity and benefits obtained by the application and implementation of the SPV electricity-generating systems.

Optimization of diesel engine input parameters running on Polanga biodiesel to improve performance and exhaust emission using MOORA technique with standard deviation

ABSTRACT Fast exhausting fossil fuel reserves and high rise in the air pollution levels due to combustion of these fuels bound us to discover some cleaner and environment-friendly fuels for the engines. Biodiesel from edible and non-edible seed oils has been identified as a better alternate of the diesel fuel in engines with a little sacrifice in terms of power output but with an improvement in exhaust emissions. The aim of the present research work is to optimize the input parameters of diesel engine running on Polanga biodiesel to improve performance and exhaust emissions. The input parameters selected for optimization are fuel injection timing, fuel injection pressure, Polanga biodiesel blend, and engine load with respect to brake thermal efficiency, brake specific fuel consumption, hydrocarbon emission, smoke opacity, and emission of nitrogen oxides. Relative weights of the response variables were calculated by standard deviation. The optimum combination of input parameters was obtained by Taguchi-based Multi-Objective Optimization by Ratio Analysis. Experiments were performed according to Taguchi’s L16 orthogonal array in a random manner in which three replicates of each experiment were noted. The optimum combination of input parameters for maximum performance and minimum exhaust emissions found to be as fuel injection timing 27° bTDC, fuel injection pressure – 220 bar, biodiesel blend – B40, and engine load – 60%. The optimum values of the response variables, at the obtained optimum combination of input parameters, were predicted by Taguchi method and then verified experimentally and a good relation was found between them. These optimum values found to be as brake thermal efficiency – 36.351%, brake specific fuel consumption – 0.322 kg/kW-h, hydrocarbon emission – 2.193 ppm, smoke opacity – 80.925 HSU, and NOx emission – 690.987 ppmv.

Thermo-economic and multiobjective optimization of saturated and superheated organic Rankine cycle using a low-grade solar heat source

This paper presents detailed energy and exergy analysis and comparison of low-grade solar heat source powered superheated and saturated organic Rankine cycle (ORC) using zeotropic mixture butane/R1234ze. The required expression to evaluate the power output, first law efficiency exergetic efficiency, exergy destruction, and required heat exchangers area are coded in Matlab 2015a interfaced with REFPROP 9.0. Moreover, saturated and superheated ORCs are further optimized by genetic algorithm by selecting exergetic efficiency and product of overall heat transfer coefficient and heat exchanger area. It is observed that superheated ORC exhibits better net power output, first law, and exergetic efficiency, lower exergy destruction, and poorer economy than saturated ORC. Further, the performance of saturated ORC is increased by 34.02% and that of superheated ORC by 17.06% by the multiobjective genetic algorithm.

Thermodynamic and multi-objective optimisation of solar-driven Organic Rankine Cycle using zeotropic mixtures

ABSTRACT This paper communicates the performance of low-grade solar heat source powered Organic Rankine Cycle (ORC). To investigate the system performance, first law and exergetic efficiencies, power output are evaluated and compared for zeotropic mixtures of (iso)butane/(iso)pentane and cyclohexane/R123. The results indicate that there exists an optimal mass fraction for which energy and exergetic efficiencies, and power output are maximum corresponding to a given value of expander inlet temperature compared with pure fluids. However, the specific volume flow ratio of the expander is higher for zeotropic mixtures; which results in a lower economy of mixtures than pure fluids. The use of an internal heat exchanger in the system improves cycle performance. Moreover, the multi-objective genetic algorithm further improves the performance of ORC and exhibits better exergetic efficiency 51–57% and 0–14.09% reduction in lower expander-specific volume flow ratio (v 6/v 5) than thermodynamically optimised ORC.