Two-stage Configuration Research Articles

Two-Stage Optimal Configuration Strategy of Distributed Synchronous Condensers at the Sending End of Large-Scale Wind Power Generation Bases

The transmission end of large-scale wind power generation bases faces challenges such as high AC-DC coupling strength, low system inertia, and weak voltage support capabilities. Deploying distributed synchronous condensers (SCs) within and around wind farms can effectively provide transient reactive power support, enhance grid system inertia at the transmission end, and improve dynamic frequency support capabilities. However, the high investment and maintenance costs of SCs hinder their large-scale deployment, necessitating the investigation of optimal SC configuration strategies at critical nodes in the transmission grid. Initially, a node inertia model was developed to identify weaknesses in dynamic frequency support, and a critical inertia constraint based on node frequency stability was proposed. Subsequently, a multi-timescale reactive power response model was formulated to quantify the impact on short-circuit ratio improvement and transient overvoltage suppression. Finally, a two-stage optimal configuration strategy for distributed SCs at the transmission end was proposed, considering dynamic frequency support and transient voltage stability. In the first stage, the optimal SC configuration aimed to maximize system inertia improvement per unit investment to meet dynamic frequency support requirements. In the second stage, the configuration results from the first stage were adjusted by incorporating constraints for enhancing the multiple renewable short-circuit ratio (MRSCR) and suppressing transient overvoltage. The proposed model was validated using the feeder grid of a large energy base in western China. The results demonstrate that the optimal configuration scheme effectively suppressed transient overvoltage at the generator end and significantly enhanced the system’s dynamic frequency support strength.

A new adaptive Perturb & Observe controller via robust approach for PV grid-connected

Given the importance of renewable energies, several countries are integrating these energies into their energy strategies, such as their connections to the grid, in particular photovoltaic energy. In this paper, a PV grid-connected system in a two-stage configuration is studied. In this configuration, an improvement to a control MPPT is proposed. To achieve this, we propose a novel concept for MPPT control that consists of generating an adaptive step size for P&O control that is based on sliding mode control in order to minimise ripple phenomena and chattering phenomena. The proposed control approach was then tested using MATLAB/Simulink simulations under varying irradiation conditions. We compared this approach to the conventional P&O method as well as the adaptive step size of P&O and hybrid P&O-sliding mode control. The results of the test indicate that the proposed control strategy significantly minimises the two phenomena and improves overall efficiency.

A two-stage optimization configuration model for multi-type flexible resource considering spatiotemporal response characteristics

As China gradually transitions towards a low-carbon energy structure, the proportion of grid-connected new energy sources like wind and solar power continues to increase. To ensure the safe and reliable operation of the power system while meeting the capacity planning for future new energy installations, there is a need for flexible resources with corresponding adjustment capabilities in the power system. In response to this situation, this paper presents an optimization model for the allocation of multiple types of flexible resources that takes into account spatiotemporal response characteristics. Firstly, a flexibility evaluation model is developed based on spatial and temporal response characteristics. Flexibility evaluation indices, such as flexibility average deficit and flexibility coverage index, are constructed. These indices are used for screening nodes with inadequate flexibility in the power system and analyzing the flexibility adequacy at various nodes. Next, the adjustment characteristics of multiple types of flexible resources are analyzed, and a model for their adjustment capabilities is established. Finally, by considering constraints based on time flexibility evaluation indices, a two-stage optimization model for flexible resource allocation is constructed. This model leverages the multiscale matching characteristics between flexibility resources and the fluctuation patterns of new energy sources to guide the allocation of flexible resources at nodes with insufficient flexibility. The effectiveness and applicability of the proposed flexible resource allocation method are validated using the IEEE 9-node system.

Development and Experimental Validation of a Two-stage Thermoelectric Heat Pump Computational Model for Heating Applications

The utilisation of thermoelectric technology as a heat pump in heating applications necessitates comprehensive investigation. The scalable nature of thermoelectric technology enables its operation at elevated temperatures without the requirement of refrigerants. In this work, an accurate computational model that can simulate one- and two-stage thermoelectric heat pumps is developed. This model uses the electric-thermal analogy and the finite difference method, including the thermoelectric effects, temperature dependent properties, thermal contact resistances and all heat exchangers, even the intermediate heat exchanger in the case of a two-stage configuration. Moreover, the model has been experimentally validated by built and tested prototypes, being the first time that a two-stage thermoelectric heat pump model is experimentally validated.The discrepancy between the simulated and experimental results is below the ± 10 % for COP, ± 8 % for generated heat and temperature lift in the airflow, and less than the ± 6 % for consumed power. Additonally, the model simulates real tendencies under different operating conditions, proving the reliability of the developed thermoelectric heat pump model.Finally, the model is used to optimise a thermoelectric system combining one- and two-stage thermoelectric heat pumps, and hybridising them with electric resistances. An airflow of 16.5 m3/h is heated from 25 °C to 160 °C, achieving a maximum COPtot of 1.21. Lastly, the importance of considering the thermal resistances of the heat exchangers is computationally modelled and demonstrated. Not taking them into account would overestimate the performance of the TEHP system by more than the 7 %.

Enhancement of Biodegradability of Chicken Manure via the Addition of Zeolite in a Two-Stage Dry Anaerobic Digestion Configuration.

Leach bed reactors (LBRs) are dry anaerobic systems that can handle feedstocks with high solid content, like chicken manure, with minimal water addition. In this study, the chicken manure was mixed with zeolite, a novel addition, and packed in the LBR to improve biogas production. The resulting leachate was then processed in a continuous stirred tank reactor (CSTR), where most of the methane was produced. The supernatant of the CSTR was returned to the LBR. The batch mode operation of the LBR led to a varying methane production rate (MPR) with a peak in the beginning of each batch cycle when the leachate was rich in organic matter. Comparing the MPR in both systems, the peaks in the zeolite system were higher and more acute than in the control system, which was under stress, as indicated by the acetate accumulation at 2328 mg L-1. Moreover, the presence of zeolite in the LBR played a crucial role, increasing the overall methane yield from 0.142 (control experiment) to 0.171 NL CH4 per g of volatile solids of chicken manure entering the system at a solid retention time of 14 d. Zeolite also improved the stability of the system. The ammonia concentration increased gradually due to the little water entering the system and reached 3220 mg L-1 (control system) and 2730 mg L-1 (zeolite system) at the end of the experiment. It seems that zeolite favored the accumulation of the ammonia at a lower rate (14.0 mg L-1 d-1) compared to the control experiment (17.3 mg L-1 d-1). The microbial analysis of the CSTR fed on the leachate from the LBR amended with zeolite showed a higher relative abundance of Methanosaeta (83.6%) compared to the control experiment (69.1%). Both CSTRs established significantly different bacterial profiles from the inoculum after 120 days of operation (p < 0.05). Regarding the archaeal communities, there were no significant statistical differences between the CSTRs and the inoculum (p > 0.05).

Optimizing Micro Friction Stir Spot Welding (mFSSW) of Aluminum Alloy AA1100 Using Neural Network Model

This study explores the optimization of Micro Friction Stir Spot Welding (mFSSW) by investigating the influence of tool profiles on welding outcomes, using aluminum alloy AA1100 with a 0.42 mm thickness as the specimen material. Monitoring temperature and RPM during welding with thermocouples and tachometers, mechanical properties are assessed through tensile shear tests, microhardness measurements, and macrostructural observations. The findings serve as the basis for developing Neural Network models using Rapidminer software, marking a transformative development that positions Neural Networks as potent tools for optimizing welding processes, potentially leading to achieving optimal weld quality. The investigation also delves into three welding tool configurations – the two-stage pin, one-stage pin, and pinless mFSSW probes – highlighting their distinct impacts on tensile shear test values and overall welding quality. Notably, the two-stage pin configuration emphasizes the significance of larger pin diameters and controlled heat generation for enhanced weld strength, while the one-stage pin configuration underscores the pivotal role of pin diameter and elevated temperatures in improving weld quality. The pinless mFSSW probe configuration, on the other hand, emphasizes the importance of shoulder diameter and temperature control for superior tensile shear test results. Leveraging Neural Network modeling for optimization, this study advances our understanding of parameter interactions and underscores the efficacy of Neural Networks in achieving superior tensile shear test values and welding quality in mFSSW, offering valuable insights for future endeavors in the field..

Characterization testing of the Thales LPT9310-HP cryocooler

Two Thales LPT9310-HP commercial off-the-shelf (COTS) cryocoolers were parametrically performance tested for cold tip temperatures between 50 K and 250 K and heat rejection temperatures between 0°C and 40°C. Both coolers had identical transfer line configurations. The test results revealed small unit-to-unit thermodynamic performance variation. They are compared to test results of a COTS LPT9310 cooler with the same transfer line configuration. The effect of compressor temperature and pulse tube inclination angle are also discussed. In addition, the off-state heat leak as a function of inclination angle is presented. Finally, the feasibility of using a single LPT9310-HP COTS cooler in a two-stage configuration is discussed.

A two-stage robust configuration optimization model and solution algorithm for new flexibility resources considering uncertainty response characterization

As the proportion of new energy continues to increase, the safety and stability of the new power system are challenged, urgently requiring the allocation of new flexible resources. This paper proposes a two-stage robust capacity optimization model considering flexibility demand constraints. Firstly, the uncertain characteristics of new energy are described, and a model of flexible resource adjustment capacity is established. Then, uncertain parameters are introduced to construct a robust capacity optimization model considering supply-demand balance, solved by column constraint generation algorithm and KKT theorem. Finally, a power system in a certain region of China is selected as the simulation object for empirical analysis to verify the effectiveness of the constructed model. The results show that the two-stage robust configuration optimization model constructed in this paper can address the uncertainty of power system and the flexibility demand brought by new energy, and the planning results can achieve a balance between the safety and economy of the new power system.

Revealing the comprehensive impact of organic compounds on the partial nitrification-anammox system during incineration leachate treatment: metabolic hierarchy and adaptation

Organics, as widespread pollutants in high-strength ammonia wastewater, typically exert adverse effects on the performance of partial nitrification-anammox (PNA) systems. However, the in-depth knowledge on how microbial consortia respond to these disturbances remains limited. In this study, we unveiled the evolution of complex organic matter flow and its impact on the metabolic hierarchy and adaptation of microbial consortia, employing multi-omics approaches, i.e., 16S amplicon sequencing, metagenomics, and metabolomics. In a two-stage PNA system sequentially treating synthetic wastewater and incineration leachate over 230 days, partial nitrification stayed stable (nitrite accumulation > 97%) while anammox efficiency dropped (nitrogen removal decreased from 86% to 78%). The phenomenon was revealed to be correlated with the evolution of dissolved organic matter (DOM) and xenobiotic organic compounds (XOCs). In the PN stage, ammonia-oxidizing bacteria (AOB) exhibited excellent adaptability through active metabolic regulation after treating leachate. Numerous heterotrophs proliferated to utilize DOM and XOCs, triggering a “boom” state evident in the glycerophospholipid metabolism. However, in the anammox stage, the competition between carbon fixation and central carbon metabolism within autotrophs and heterotrophs became evident. Increased biosynthesis costs inhibited the central metabolism (specific anammox activity decreased by 66%) and the Wood-Ljungdahl pathway of anammox bacteria (AnAOB) in the presence of recalcitrant organics. Additionally, the degradation of organics was limited, exhibiting a “bust” state. This study revealed the metabolic adaption and susceptibility of AOB and AnAOB in response to organics from the leachate, demonstrating the applicability of the two-stage configuration for treating high-strength wastewater containing abundant and diverse organics.

A new approach to MPPT hybrid incremental conductance-sliding mode control for PV grid-connected

As photovoltaic energy is clean, renewable, and less noisy, it is increasingly integrated into the grid. This integration aims to overcome energy deficits and get rid of pollution from conventional sources. In this paper, a two-stage configuration of PV energy conversion to a three-phase grid has been studied. The control of this configuration can be divided into two parts, such as DC bus control and AC bus control. The DC bus is controlled by MPPT control. The AC bus is controlled by DC link voltage control, phase-looked loop control, and voltage source inverter control. The contribution in this study aims to improve the quality of energy injected via a new hybrid approach to MPPT control. The proposed control is a combination of robust sliding-mode control and incremental inductance. Unlike conventional hybridization, the proposed control estimates correct the error upon entry of the conductance incremental control. This correction provides an adaptive incremental step for increment conductance control. The proposed control is compared with three other controls under MATLAB/Simulink. Such as incremental conductance, variable step size incremental conductance, and conventional hybrid MPPT incremental inductance-sliding mode control. The simulation results show a remarkable minimization of the ripple phenomenon and the chatter phenomenon. Thus, the quality of the energy injected into the network is improved, such as by reducing the total harmonic distortion of the current and increasing efficiency.

Vacuum ammonia stripping from liquid digestate: Effects of pH, alkalinity, temperature, negative pressure and process optimization

High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste. Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen, which has attracted a lot of attention in recent years. To investigate the parameter effects on the efficiency and mass transfer, five combination conditions (53 °C 15 kPa, 60 °C 20 kPa, 65 °C 25 kPa, 72 °C 35 kPa, and 81 °C 50 kPa) were conducted for ammonia stripping of sludge digestate. The results showed that 80% of ammonia nitrogen was stripped in 45 min for all experimental groups, but the ammonia transfer coefficient varied under different conditions, which increased with the rising of boiling point temperature, and reached the maximum value (39.0 mm/hr) at 81 °C 50 kPa. The ammonia nitrogen removal efficiency was more than 80% for 30 min vacuum stripping after adjusting the initial pH to above 9.5, and adjustment of the initial alkalinity also affects the pH value of liquid digestate. It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency, while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity. In terms of the mechanism of vacuum ammonia stripping, it underwent alkalinity destruction, pH enhancement, ammonia nitrogen dissociation, and free ammonia removal. In this study, two-stage experiments of alkalinity destruction and ammonia removal were also carried out, which showed that the two-stage configuration was beneficial for ammonia removal. It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.

Enhancement of the Power-to-Heat Energy Conversion Process of a Thermal Energy Storage Cycle through the use of a Thermoelectric Heat Pump

The principal strategy for achieving a neutral climate entails enhancing the share of renewable energies in the energy mix, in conjunction with promoting innovation in efficient technologies. Thermal energy storage systems have the potential to efficiently handle the intermittent nature of renewable energy sources. Furthermore, these systems can effectively handle shifts in both heat and electrical demand. Thus, efficient power-to-heat technologies are needed to boost thermal energy storage. This manuscript explores the potential of utilising a thermoelectric heat pump system in conjunction with electric resistances for charging a thermal energy storage. In order to achieve elevated temperatures, the thermoelectric system integrates thermoelectric heat pump blocks in a two-stage configuration. Air has been employed as a heat transfer medium for sensible heat storage. Higher airflow rates improve the performance of thermoelectric heat pump system. Moreover, its impact on the optimal voltage supply of the thermoelectric system is observed when it is combined with an electric resistance to achieve elevated temperatures. In comparison to the basic charging process that solely relies on the electric resistance of a thermal energy storage at 120 °C, a significant 30 % increase in power-to-heat energy conversion has been achieved by including the thermoelectric heat pump system. In fact, it efficiently elevates the temperature from the initial ambient temperature of 25 °C to a remarkable 113.1 °C, achieving a coefficient of performance of 1.35 with an airflow rate of 23 m3/h. Therefore, the use of this technology to enhance a complete process of storing excess renewable energy in the form of heat for subsequent use in both heat and electricity through a combined heat and power cycle is demonstrated.

Performance Evaluation of Two Stages Parallel Flow Indirect Evaporative Cooling with Aspen Pads in Baghdad Climate Conditions

This study delves into the realm of advanced cooling techniques by examining the performance of a two-stage parallel flow indirect evaporative cooling system enhanced with aspen pads in the challenging climate of Baghdad. The objective was to achieve average air dry bulb temperatures (43 oC) below the ambient wet bulb temperatures (24.95 oC) with an average relative humidity of 23%, aiming for unparalleled cooling efficiency. The research experiment was carried out in the urban environment of Baghdad, characterized by high temperature conditions. The investigation focused on the potential of the two-stage parallel flow setup, combined with the cooling capability of aspen pads, to surpass the limitations imposed by conventional cooling methods. The empirical findings underscored the capacity of the two-stage parallel flow configuration to achieve air-dry bulb temperatures surpassing the ambient wet bulb temperature. Nonetheless, it was evident that an excessive application of water (exceeding 9 lpm) onto the aspen pads within the wet channels yielded adverse repercussions on the cooler's performance metrics, specifically in terms of wet bulb effectiveness and coefficient of performance. A range of air flows spanning from 150 CMH to 350 CMH was analyzed, revealing the influence of heightened air flow rates on the resultant dry bulb temperatures delivered by the cooling system. Notably, the peak wet-bulb effectiveness registered at 1.08, concurrently yielding a coefficient of performance measuring 7.8.

Adaptive Hybrid NFS-MSOGIQ Control Technique for Improving Power Quality in Solar PV Distributed Generation System

A two-stage circuit configuration with 3-phase utility grid assisted solar power generation system is designed. In order to track the solar PV arrays maximum peak power (MPP), a DC boost converter with Composite Incremental Conductance (InC) MPP technique is employed in first stage. In Second stage, a grid-tied four-leg DC-AC converter, is employed to provide the solar power that was extracted into the utility grid and to enhancing power quality. An adaptive hybrid Multi-Second Order Generalized Integrator-Quadrature (MSOGI-Q) control algorithm, in conjunction with Neuro Fuzzy system (NFS) is proposed for controlling this DC-AC converter. MSOGI-Q reference current generation strategy is designed to mitigate current harmonics by retrieving the fundamental constituents from non-linear load. The Neuro Fuzzy system along with PID controller, by adjusting the voltage from dc link keeps consistent power in between AC and DC sides for varying isolation condition. To get the peak power out of a PV panel even in different environmental conditions, the composite incremental conductance algorithm is used. To upgrade the dynamic performance of voltage variation at Point of Common Coupling (PCC) a feedforward descriptor for Photovoltaic contributions has been implemented. In addition, a comparison between the proposed NFS-MSOGIQ control technique and the existing adaptive control technique is done to assess the effectiveness of the proposed adaptive control technique. The proposed adaptive control technique for the distributed generation system is designed and stimulated in MATLAB/SIMULINK and the simulation outcomes verify the effectiveness of the proposed control technique under various transition circumstances. A laboratory prototype model of the proposed system is developed for theoretical analysis and its results are found to be compliant with IEEE standards. Furthermore, THD values of voltage and current are found to be within standard limits.

Design and development of photovoltaic solar system based single phase seven level inverter

For solar photovoltaic (PV) systems, an upgraded triple gain seven-level inverter that works both independently and while connected to the grid is proposed. The two-stage configuration of the system is boost cascaded. The first stage has a one switch improved gain converter (OSIGC) to increase and normalize the input direct current (DC) voltage, and the second stage includes a unique seven level alternating current (AC) is produced via a multilevel inverter (MLI) design with triple voltage gain. The proposed OSIGC is appropriate for a broad range of conversions. The voltage gain in MLI was achieved using switched capacitor techniques. The DC-DC converter can achieve a maximum voltage gain of twelve and the MLI can achieve a maximum voltage gain of three, resulting in a DC-DC-AC voltage that can reach 36. Maximum power point tracking (MPPT) technique based on modified perturb and observe (PO) is used in OSIGC to maximise PV module power utilisation, and MLI control utilises sinusoidal pulse width modulation (SPWM) realistically. For the purpose of analysing the suggested system, a 200 Watt prototype statel is created. With a total harmonic distortion (THD) of 0.181%, up to 92.12% of the converter system’s overall efficiency is possible.

Investigation of no emission characteristic of ammonia-hydrogen flame in a two-stage model combustor

The laminar burning velocity and NO formation process of ammonia-hydrogen combustion within a two-stage combustion chamber were investigated numerically in the present study. A chemical reactor network method involving perfectly stirred reactor, plug flow reactor, and partially stirred reactor configurations with the 24-species Xiao mechanism was implemented to simulate the premixed ammonia-hydrogen-air combustion process. The effects of inlet temperature and pressure conditions on the laminar burning velocity were investigated. Results proved that elevated pressure condition decreased primary flame thickness leading to lower laminar burning velocity while inlet temperature increased flame temperature which in turn increased the laminar burning velocity. Investigation of the effect of humidification on the laminar burning velocity showed that humidification can counteract the effect of high inlet temperature. The NO emission studies indicated a twofold impact of pressure on NO formation processes: preventing NO formation in the primary combustion zone, and promoting thermal NO formation in the lean combustion zone. The minimum amounts of NO emission were obtained at total equivalence ratios of 0.4. Humidification prevented the NO formation in the lean combustion through the competitive effect of H2O on O, whilst temperature effect was comparatively small. Humidity and pressure were optimized in the two-stage configuration achieve both low emission and high efficiency.

Effect of reactor operation modes on mitigating antibiotic resistance genes (ARGs) and methane production from hydrothermally-pretreated pig manure

Numerous efforts have been made to enhance the performance of anaerobic digestion (AD) for accelerating renewable energy generation, however, it remains unclear whether the intensified measures could enhance the proliferation and transmissions of antibiotic resistance genes (ARGs) in the system. This study assessed the impact of an innovative pig manure AD process, which includes hydrothermal pretreatment (HTP) and a two-stage configuration with separated acidogenic and methanogenic phases, on biomethane (CH4) production and ARGs dynamics. Results showed that HTP significantly increase CH4 production from 0.65 to 0.75 L/L/d in conventional single-stage AD to 0.82 and 0.91 L/L/d in two-stage AD. This improvement correlated with a rise in the relative abundance of Methanosarcina, a key methanogenesis microorganism. In the two-stage AD, the methanogenic stage offered an ideal environment for methanogens growth, resulting in substantially faster and higher CH4 production by about 10% compared to single-stage AD. Overall, the combined use of HTP and the two-stage AD configuration enhanced CH4 production by 40% compared to traditional single-stage AD. The abundance and diversity of ARGs were significantly reduced in the acidogenic reactors after HTP. However, the ARGs levels increased by about two times in the following methanogenesis stage and reached similar or higher levels than in single stage AD. The erm(F), erm(G), ant(6)-Ia, tet(W), mef(A) and erm(B) were the six main ARGs with significant differences in relative abundances in various treatments. The two-stage AD mode could better remove sul2, but it also had a rebound which elevated the risk of ARGs to the environment and human health. Network analysis identified pH and TVFAs as critical factors driving microbial communities and ARG proliferation in the new AD process. With the results, this study offers valuable insights into the trade-offs between AD performance enhancement and ARG-related risks, pinpointing essential areas for future research and practical improvements.

A two-stage robust configuration optimization framework for integrated energy system considering multiple uncertainties

The optimal configuration of integrated energy system (IES) is the cornerstone of efficient investment and low-carbon operation, which is of high importance for realizing energy system sustainable transformation. Yet, the intermittency of renewable energy and uncertainty of multiple energy demands pose severe challenges to IES configuration and operation. To address the issue, this research presents a two-stage robust configuration optimization model incorporating the multiple uncertainties of supply and demand. The model takes economic benefits, environmental benefits and energy utilization efficiency as objective functions, and is executed by column and constraint generation algorithm. A case study justifies the proposed model. The findings indicate the uncertainty from renewable energy and demand raises the equipment capacity and results in an increase of investment cost. Contrasted with the deterministic scenario, the total costs in the uncertainty scenario increase from 7043795.8CNY to 7785296CNY, but the performance shows more robust and the loss of load penalty is saved up to 296888CNY. Sensitivity analysis reveals energy price fluctuations primarily impair the operating costs, whereas they cause moderate effects on the configuration results. Load fluctuations cause greater consequences on both configuration and operating costs. The research provides references for IES configuration under multiple uncertainties with renewable energy penetration.

Continuous slurry hydrotreating of sewage sludge-derived hydrothermal liquefaction biocrude on pilot-scale: Comparison with fixed-bed reactor operation

In this study, we demonstrate the continuous catalytic hydrotreating of sewage sludge-derived hydrothermal liquefaction oil on a versatile, pilot-scale testing unit, equipped with both a slurry and a fixed-bed reactor. Comparison of the two reactors shows that slurry hydrocracking is consistently more efficient in both heteroatom removal and cracking performance compared to the fixed-bed operation. The upgraded HTL oil from the slurry reactor contains 35% less nitrogen that the equivalent oil produced from the fixed-bed reactor at 350 °C and is lighter, consisting of 84 wt% molecules in the gasoline and diesel range, compared to 63 wt% in its counterpart. This is tentatively ascribed to the higher residence time and the lower mass-transfer limitations in the slurry reactor that enhance the hydrogenation and cracking reactions. Upgrading the HTL oil in a two-stage configuration improves only the nitrogen removal, which increases from 40‐55% in the one-stage process to 83%. Overall, slurry hydrocracking appears to be a promising strategy for the upgrading of bio-oils from renewable feedstocks, such as waste and biomass. Further research is required to study operability and stability issues for longer time-on-stream and investigate the process in the presence of dispersed liquid catalysts.

Investigations on a solar humidification dehumidification desalination system equipped with various packing materials and multi-stage bubble column dehumidifier.

This work presents the theoretical and experimental investigation of a solar-powered humidification dehumidification desalination (HDD) system with different humidifier packing materials and a two-stage bubble column dehumidifier (BCD). Naturally available coconut shells (CS) and coconut shells with drilled holes (CSH) on the surface to improve water permeability were used as packing materials in the humidifier, and their performance was compared with that of commercial-type pall ring (PR) and raschig ring (RR) packings. An in-house developed numerical model of the HDD system in conjunction with a flat plate solar water collector was used in this study. Steady-state experimental results showed that CSH packing exhibited the highest volumetric mass transfer coefficient (0.00852kg/s), resulting in maximum humidifier efficiency (96%) and freshwater yield (2.16kg/hr), followed by PR (0.00841kg/s, 94%, and 2.137kg/hr), CS (0.00831kg/s, 90%, and 2.127kg/hr), and RR (0.0081kg/s, 81%, and 2.087kg/hr) at feedwater mass flow rate of 1.5kg/min and humidifier inlet temperature of 75 [Formula: see text]. Furthermore, transient outdoor test results showed that using a two-stage configuration in a BCD increased the daily average effectiveness to 0.93, as against 0.79 for a single-stage BCD. Employing CSH instead of PR and RR packings in the humidifier reduced freshwater costs by 6.2% and 7.6%, respectively.