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In this paper, an Advanced Dynamic Model Predictive Control (AMPC) based on a Nonlinear Model Predictive Control (NMPC) framework with a multi-objective cost function driven by dynamic weights is proposed to improve the energy performance of fuel cell hybrid electric vehicles whilst prolonging their component lifetime. By the use of dynamic weights, the cost function is effectively formulated as the combination of fuel consumption, rate of change of fuel cell power, battery power, the fuel cell efficiency, state of charge of the battery, and their temperatures. In order to enhance the adaptability of the AMPC, a Fuzzy Cognitive Map (FCM) is then newly designed to regulate online the dynamic weights to adjust the importance of each cost component according to the conditions prevailing during driving. A comparative study between the proposed AMPC, a constant weight based NMPC and a conventional NMPC having cost function with fewer objectives has been carried out by means of simulation using a FCHEV model from the simulation tool ADVISOR to illustrate the efficacy of the proposed AMPC.

Abstract In this analysis the simple reaction water turbine known as Barker’s Mill is revisited. The major geometrical and operational parameters have been identified and, using principles of conservation of mass, momentum and energy, the governing equations have been developed for the ideal case of there being no frictional losses. The solutions of the resulting equations are offered in a non-dimensional form. It is shown that the maximum torque produced by the machine is developed when the turbine is stationary. At this point the net output power is zero. As the load torque is decreased the turbine rotates and power is produced. Furthermore, because of a centrifugal pumping effect, the mass flow rate of water through the turbine increases during acceleration. Further decrease in the load torque is accompanied by increases of speed, output power, water mass flow rate and efficiency. It is shown that when the load torque is reduced towards half the value of the torque at the stationary condition, water mass flow rate, rotational speed and output power tend towards infinity. Under this condition the efficiency of the machine approaches unity. The non-dimensional characteristics of the idealized turbine are used to investigate the general characteristics of the machine and to explore its application for production of power from water reservoirs with low heads. Theoretical analysis of a simple reaction turbine is presented including consideration of the fluid frictional losses for a practical situation. A practical turbine will never run away towards infinite speed and the maximum power and efficiency of such a turbine will depend on the fluid frictional losses. Here a new factor is defined, representing the overall fluid frictional losses within the turbine. Finally this paper presents briefly the experimental performance results for two simple reaction water turbine prototypes. The two turbine prototypes under investigation have rotor diameters O0.24 m and O0.12 m respectively. The two turbine models were tested under supply heads ranging from 1 m to 4 m. The simple reaction water turbine can operate under very low hydro-static head with high energy conversion efficiency. This type of turbine exhibits prominent self-pumping ability at high rotational speeds. Under low head to achieve high rotational speeds the turbine diameter should be very small and this limits the volumetric capacity and hence the power generation capacity of such a turbine. Consequently the practical applications of this turbine would be limited to micro-hydro power generation. The split pipe design of the reaction turbine tested is easy to manufacture and it has been shown to have overall energy conversion efficiency of approximately 50% even under low heads.

Abstract The study investigates biodiesel synthesis from waste seeds derived Mesua ferrea oil (MFO) using indigenously developed biocatalyst via lipase immobilisation on coconut shells derived microporous activated carbon (AC). The carbonaceous support was developed through steam activation of carbonised char at optimised activation conditions to attain maximum porous properties. The hydrolytic enzyme i.e. lipase was immobilised on prepared AC through adsorption process at different functional variables. The enzyme loading or uptake of carbonaceous support and enzymatic activity of respective sample at each set of parametric conditions were estimated. The adsorption assisted immobilisation was optimised employing Taguchi method and significant factors affecting highly both the responses were identified through estimation of statistical constraints. The optimised conditions derived using 3FI model were: Initial protein concentration 500 mg/L, time 270 min, temperature 15 °C, and solution pH 6 for achieving maximum adsorption capacity of 10.04 mg/g and biodiesel yield 67.5%. Moreover, statistical parameters revealed, immobilisation temperature and initial protein concentration influence the catalytic activity considerably and optimised immobilisation helps in attaining highly active and stable biocatalyst. Furthermore, the chosen model was effective in predicting the optimised conditions with high precision for maximising the responses. Thus, the developed biocatalyst through lipase immobilisation on indigenously prepared microporous carbon support is effective in transesterification of MFO at 3FI model derived optimised conditions.

Abstract Electrothermal instabilities occurring in the boundary layers of MHD generator channels can cause the breakdown of the electrostatic sheath and lead to the transition from the diffuse to an arc mode current transport. This instability may occur at the electrostatic sheath edge and the arc can punch through the sheath from the plasma side. A stability analysis, carried out for the occurrence of the instability, however, shows that the values of the critical parameter for the onset of instability at the sheath edge were much less than the critical values for breakdown from the electrode plasma interface. Since the perturbations occurring at the sheath edge were found to get damped at higher applied potentials, it is predicted that the instability occurring at the sheath edge at low potential differences cannot lead to the arc transition, but may lead to fluctuations in the values of observable parameters.

Abstract Photovoltaic (PV) solar power, which is considered as the most competitive clean energy source, contributes to a significant percentage of electricity production in many developed countries. However, accurate PV power forecasting is necessary due to its high variation that can be caused by several factors. Hence, the intermittent nature of PV production represents a major challenge to integrate PV systems into the electric grid. The scope of this paper deals with this issue through developing a new integrated PV power forecasting model. The proposed model is based on the use of a new decomposition methodology, named Iterative Filtering for decomposing PV power into different intrinsic functions (IMFs), then Extreme Learning Machine (ELM) is used as essence predictor. To this end, the proposed IF-ELM model is evaluated on three solar PV power plants installed at three different sites, with different climatic conditions. Direct and recursive IF-ELM methodologies are examined for multi-step ahead forecasting in a very short time-scale (up to 60 min). Overall, the forecasting results show high precision performance for the studied forecasting horizons- in terms of different statistical metrics compared to stand-alone models. Also, the proposed IF method shows its high performance when compared to the recently developed decomposition method. complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) in improving the forecasting accuracy of a single model. Forecasting results with the IF-ELM model led to an error in nRMSE that is less than 10% and a Correlation Coefficient greater than 98% over all forecasting horizons.

Abstract Worldwide efforts are being made for evolving viable electricity generation alternative to the traditional fossil fuel based power generation systems and also to enhance the efficiency of existing power generation systems. Studies have been made for integrating fuel cell with gas turbine cycle and Organic Rankine cycle, but there exist possibility of further investigation by incorporating the measures to increase effective energy utilization in the cycle along with consideration of different working fluids in Organic Rankine cycle. In the present paper, a combined cycle system consisting of technologies namely solid oxide fuel cell, gas turbine and Organic Rankine cycle is studied. The considered combined cycle system employs Heat Recovery Steam Generator followed by Organic Rankine cycle as bottoming cycle for recovering the waste heat coming out from hybrid SOFC-GT system through a Heat Recovery Vapour Generator. The considered SOFC-GT system has methane gas being used as fuel which is reformed by both external and internal reformers with anode gas recycling. Here three different working fluids namely R141b, R245fa and R236fa are used in bottoming Organic Rankine cycle for comparing their effects on the cycle performance of proposed SOFC-GT-ORC combined cycle system based on first law of the thermodynamics. Results have been obtained from the computer simulation based on thermodynamic modeling of SOFC-GT-ORC combined cycle and the effects of gas turbine inlet temperature, cycle pressure ratio, fuel utilization factor and ORC turbine inlet temperature are investigated on the cycle performance. The study indicates that the efficiency is increased about 8%-12% by recovering SOFC-GT waste heat through ORC and R236fa is found to be the best in terms of power generation capacity and efficiency of SOFC-GT-ORC system. Outcome from this paper gives insight to the power sector professionals and research community working for evolving efficient and robust power generation alternatives based on the combination of direct energy conversion system and indirect energy conversion system.

Abstract Renewable energy systems are proving to be promising and environment friendly sources of electricity generation, particularly, in countries with inadequate fossil fuel resources. In recent years, wind, solar photovoltaic (PV) and biomass based systems have been drawing more attention to provide electricity to isolated or energy deficient regions. This paper presents a hybrid PV-wind generation system along with biomass and storage to fulfill the electrical load demand of a small area. For optimal sizing of components, a recently introduced swarm based artificial bee colony (ABC) algorithm is applied. To verify the strength of the proposed technique, the results are compared with the results obtained from the standard software tool, hybrid optimization model for electric renewable (HOMER) and particle swarm optimization (PSO) algorithm. It has been verified from the results that the ABC algorithm has good convergence property and ability to provide good quality results. Further, for critical case such as the failure of any source, the behavior of the proposed system has been observed. It is evident from the results that the proposed scheme is able to manage a smooth power flow with the same optimal configuration.

Abstract The significant temperature effect on solar cells results in loss of photovoltaic (PV) efficiency by up to 20–25%, which may over-negate the efforts in technology development for promoting PV efficiency. This motivates studies in thermal management for solar cells. This study concerns the thermal assessment of an advanced system composed by a solar cell and a nano-coated heat pipe plate for thermal management. Solar cell temperature and the corresponding evaporative heat flux are evaluated based on a conjugated heat transfer model. It indicates that the solar cell can be cooled down to be below 40 °C and suffers no temperature effect due to the use of the heat pipe plate. The heat pipe plate can provide sufficient cooling to the solar cell under different solar irradiance. The analytical and experimental results show that the maximum evaporative heat flux of the current heat pipe plate is around 450 W/m2. However, the practical heat removal flux at the condenser is 390 W/m2. The loss of cooling energy is due to the gathered vapour at the condenser section, which prevents the liquid-vapour circulation inside the vacuum chamber of the device. By using additional cooling strategies (i.e. heat sink, PCMs, water jacket) at the condenser section, the heat removal ability can be further improved.

A novel thermal-energy storage concept involving the use of salt-hydrates such as sodium thiosulphate pentahydrate, Na2S2O3·5H2O is under investigation. With fusion temperatures of many salts lying between 0 and 100°C, such substances may be considered as likely materials to be used in conjunction with solar energy flat-plate collector systems for domestic use. Phase change storage or latent heat storage is concluded to be a promising technique for storing solar energy. The solid-liquid transformation of salt-hydrates is actually a dehydration or hydration of salt, although this process resembles melting or freezing thermodynamically. Three types of behaviour can be identified: congruent, incrongruent, and semicongruent melting. None of the congruent melting salt-hydrates have been judged for use in thermal storage because of cost and safety considerations.