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Abstract The present work attempts to devise an efficient method utilizing an on-grid photovoltaic-thermal heat pump water heater (PV-THPWH) integrated with a real-time variable frequency controller to achieve the goal of energy-efficient buildings. The prime focus is to reduce the grid's dependence on the compressor's energy-intensive operation by employing a feedback-controlled variable frequency drive (VFD). Additionally, the possibilities involved with addressing the electrical and thermal energy requirements of an energy-efficient building was investigated utilizing the proposed system. R-32 refrigerant in the photovoltaic-thermal (PV-T) evaporator coils of the heat pump assembly help to cool the photovoltaic (PV) panel while delivering the absorbed heat in the condenser to heat water contained inside the storage tank. Outdoor experiments and theoretical investigations of the combined system were carried out to appraise the dynamic behavior under varying solar irradiation and ambient temperature conditions. The observations conveyed that the PV-THPWH system succeeded in reducing the PV panel operating temperature by 25%, which resulted in a 20% increment in PV power output. Also, the performance indicators, such as the instantaneous energy efficiency and instantaneous PV efficiency, were found to increase by 15% and 34%, respectively, resulting in an average coefficient of performance of 6.4. For a clear sky day, the recorded total PV energy output was 4.67 units, while the VFD compressor consumption was 3.42 units, and the surplus 1.25 units were sent to the grid. Furthermore, the economic analysis reported a payback period of 2.3 years for the developed PV-THPWH system.

Abstract Gold nanoparticles (Au-NPs) seeded plasmonic nanofluids (PNFs) have shown promising results in overall performance enhancement of direct absorption solar collector (DASC) due to localized surface plasmon resonance (LSPR) effect. For the work presented here, Au-NPs were synthesized by the wet chemical method and were utilized to prepare plasmonic nanofluid. The surface plasmon resonance peak of Au-NPs was observed at 531 nm using UV–Visible spectrophotometer study. The testing for performance enhancement of gold plasmonic nanofluid (GPNF) laden DASC so far is limited to laboratory scale setups or simulation studies. Considering the dearth of outdoor experimental studies, an attempt has been made in the present study to evaluate the thermal performance of Au-NPs (∼40 nm) based nanofluid (∼0.0002 wt%) in full scale DASC. The experiments have been performed at different flow rates under clear sky outdoor conditions in winter season at Jalandhar, India. The maximum collector outlet temperature was measured to be 55 °C with GPNF which is about 7 °C higher than the maximum outlet temperature obtained with de-ionized water as working fluid. Thermal efficiency with GPNF is about 33% higher than de-ionized water at the optimal flow rate of 0.030 kg/s.

Abstract DC microgrids have received wide interest in recent times because of the advantages related to improved power transfer capability, high efficiency, compatibility with distributed energy resources (DER) and reduced losses. However, the adoption of DC microgrids has been restricted because of the challenges in designing a reliable protection scheme. The challenge results from the high magnitude of the fault current without zero crossing, coupled with the requirement of high rapidity in fault detection. The scenario is further complicated during the variation in operational dynamics of microgrid either due to weather intermittency or network reconfiguration arising out of DER outage. Non-addressal of the above issues results in reduced grid resilience because of possible relay malfunction during stressed scenarios. In this regard, an ensemble classifier-based protection scheme has been proposed for DC microgrid with adaptability to system reconfiguration and weather intermittency. The adaptiveness has been achieved by online identification of network topology, while immunity to weather variation is attained by stochastic modelling of solar irradiance and wind speed. The use of local information for executing the protection tasks avoids the issues related to data loss and latency in the communication link. The task of operating mode detection, topology identification, fault detection/classification and section identification have been formulated as a set of classification problems and further solved using a random subspace sampling-based ensemble classifier technique. The reliability of the proposed scheme has been extensively validated for a wide range of fault scenarios involving wide variation in network topology, weather condition and fault parameters.

Abstract Designing a high-performance hydrofoil is a fundamental challenge for the current turbine blade designers. In this paper, the performance of S1210 hydrofoil, commonly used in the tidal current turbine blades, in presence of (i) Vortex Generators (VGs), and (ii) modified trailing edge is numerically studied. The results show that attaching counter-rotating VGs near the trailing edge of the foil can increase the lift coefficient by 17% and delay the stall angle from 10° to 12°. Constructing a rounded and thicker trailing edge can help to improve the hydrodynamic performance by increasing the lift coefficient by 13.5%. The combination of VGs (located near the trailing edge) and rounded trailing edge can increase the glide ratio significantly. These observations have been explained by plotting the pressure coefficients and velocity profiles at different locations on the foil surface. The findings will be useful to manufacture a stronger blade profile and extract more power from the current turbines that operate at wide current speed variation.

Longitudinal flow through central subchannel structures in an array of fuel rods in a nuclear reactor plays an important role in removing the heat generated inside the fuel rods. In this paper, an entropy generation analysis has been carried out for assessment of the performance of an infinite triangular as well as a square subchannel for single-phase forced turbulent flow. The performance is evaluated with the objective function being the overall entropy generation in a central subchannel. Various constraints such as dimensionless flow area subtended by the array of rods, pitch to diameter ratio for the configuration of rod bundles and volumetric heat generation to power density ratio of the subchannel imposed by power restrictions have been considered. The parameters include the dimensionless wall heat flux, duty parameter, length to diameter ratio for fuel rods, Reynolds number etc. It has been observed that for a pitch to diameter ratio constraint the square subchannel generates lesser amount of entropy and thus more acceptable compared to triangular structure. For the same constraint the optimum Reynolds number shifts towards higher value compared to triangular one. For dimensionless flow area constraint, on the other hand, the analysis reveals completely reverse phenomenon.

Abstract Thermal energy storage systems based on Phase change materials (PCM) are an attractive option to bridge the temporal and spatial gap between the energy demand and supply. But, these systems possess poor thermal conductivity causing reduced rate of heat transfer. The objective of the present study is to numerically analyze the melting process in an optimized finned latent heat storage system dispersed with varying volume fraction of Graphene nano plates (GNP). The individual effect of incorporating fins, GNP and a combination of both at different volume fraction has been studied. Effective thermal conductivity of nano-composite PCM has been theoretically evaluated including the effect of aspect ratio, interfacial thermal resistance, anisotropy, non-linear effects as well as concentration for the dispersed GNP. In this work, Dynamic differential scanning calorimetry tests are performed to evaluate the phase change temperature, latent heat and specific heat of the sugar alcohol (d- mannitol). Transient variation of liquid fraction, average temperature and radial/longitudinal temperature differentials are presented which would be useful for designing medium temperature (160–200 °C) storage systems for various applications. Fin height is varied to obtain an optimum fin size such that natural convection currents are not impeded. Various heat transfer models (including natural convection) are analysed using the actual plant data of a double effect solar absorption system at different arrangements of fins and GNP. Effect of Reynolds number and inlet temperature of HTF on the system performance have also been studied. A reduction of 68% in total melting time is observed in finned LHSS with 5% GNP as compared to a conventional system.

Abstract Hybrid nanofluids are a novel class of colloidal fluids which have drawn significant attention due to potential tailoring of their thermo-physical properties for heat transfer enhancement by a combination of more than one nano-additive to meet specific requirements of an application. In the present work, ceramic copper oxide/carbon (SiO2-CuO/C) nanoparticles in 80:20 (wt%) composition were prepared by ultrasonic-assisted wet mixing technique. The hybrid nanofluid was formulated by dispersing the nanoparticles into a base fluid mixture of 60:40 (% by mass) glycerol and ethylene glycol (G/EG) using the two-steps method. The influence of nanoparticles on the augmentation of specific heat, thermal conductivity and viscosity was examined in the volume concentration range of 0.5–2.0% in the temperature range of 303.15–353.15 K. The results demonstrate that the synthesized SiO2-CuO/C hybrid nanoparticles enhanced the thermo-physical properties of the base fluid mixture which is higher than using SiO2 alone. In the case of SiO2–G/EG nanofluid, the specific heat capacity decremented by a maximum value of 5.7% whereas the thermal conductivity and viscosity incremented by 6.9% and 1.33-times as compared with G/EG at maximum volume concentration of 2.0% at a temperature of 353.15 K. Comparatively, a reinforcement of 80% SiO2 with 20% CuO/C in G/EG mixture led to thermal conductivity and viscosity enhancement by 26.9% and 1.15-times, respectively with a significant reduction of specific heat by 21.1%. New empirical correlations were proposed based on the experimental data for evaluation of thermophysical properties.

Abstract It is well known that Espinosa-parades et al. (Espinosa-Paredes et al., 2011) proposed a fractional neutron point kinetic (FNPK) model with multi-group of delayed neutrons to describe dynamic behavior in a nuclear reactor. In (Aboanber and Nahla, 2016b), Aboanber and Nahla presented an extension of Espinosa-parades et al. FNPK model. This new model is called as the corrected fractional neutron point kinetic (CFNPK) model. The present study is concerned with the numerical solution of the CFNPK model (Aboanber and Nahla, 2016b) with six groups of delayed neutron precursors. The fractional derivative is described in the sense of Grunwald-Letnikov. An implicit finite difference method (FDM) is constructed for the solution of CFNPK model. The stability analysis of the method is carried out. We analyze the results of neutron density for different values of anomalous diffusion order, reactivity function, relaxation time and time step size. In addition, we compare the results corresponding to CFNPK model (Aboanber and Nahla, 2016b) with the results corresponding to the FNPK model proposed by Espinosa-parades et al. (Espinosa-Paredes et al., 2011). It is shown that as anomalous diffusion order decreases or simulation time increases the difference between the values of neutron density increases. We have investigated the effects of each term of the CFNPK.

Abstract This paper describes the development of a meta-heuristic based algorithm to solve the optimal transmission switching (OTS) problem. The approach solves the mixed-integer non-linear problem considering simultaneous optimization of transmission topology and generation dispatch. The algorithm is the first ever application of particle swarm optimization (PSO) to model OTS and operates using combined real and binary (CRB) variables to solve a weighted sum of interdependent multiple objective functions. The unique stochastic generation principle of combinatorial variables is based on a blend of both uniform and biased Gaussian probability distribution functions. The required binary values of swarms are generated from the continuous values of the random Gaussian distribution with the application of the Heaviside function. All the transmission lines are considered as potential switch variables the operations of which are limited by different aspects. The algorithm can tackle the complex optimization problem with many constraints of varying difficulty. The randomness in CRB variables and unpredictability in switching may generate infeasible particle(s) resulting in island formation. The algorithm also proposes regeneration of these infeasible particle(s) by modifying them to a feasible one to avoid this islanding as well as to have stable switching possibilities. The improvement in the computational efficiency of the algorithm is proposed with the adoption of Micro-PSO for small load deviations. A wide range of unique solutions are obtained based on the preferences of the system operator. This OTS algorithm is tested using the IEEE 57 bus and the IEEE 118 bus system and encouraging results are obtained.