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[Display omitted] • Office paper waste is processed using physiochemical and enzymatic hydrolysis. • The yeast is isolated from rotten banana for the fermentation process. • Box-Behnken analysis was used to determine optimal conditions for key variables. • A blended membrane was applied for the purification process. • Amicon cell and polymeric membrane dehydrate ethanol–water combinations. One potential replacement for fossil fuels is the generation of biofuel from biomass feedstock. To reach the global sustainability goals, it is also necessary to address a number of issues, such as reducing environmental pollution, climate change, and carbon emissions. This work was aimed to convert the office paper waste as biomass feedstock into bioethanol through a sustainable pathway. The office paper waste was hydrolyzed via physiochemical and enzymatic hydrolysis, the liberated glucose was estimated at 15.72 g/L using the optimum conditions of 15 % HCl and 6 % office paper waste followed by enzymatic hydrolysis. The yeast isolate B2 that was applied for the fermentation process was isolated from rotten banana, identified as Hanseniaspora uvarum (STDF-B2) and submitted to GenBank with accession number (OP800106). The Box-Behnken design was applied to estimate the optimal conditions for the three most significant variables depending on the one variable at a time results. A blended membrane of sulphonated polyvinyl chloride with poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (SPVC-PAMPS) was applied for the purification of both standard ethanol and produced bioethanol via pervaporation technique (PV). The morphology, chemical composition, mechanical properties and permeability of the membrane were all analyzed in various ways. Following purification using a membrane-integrated amicon cell, the total permeate flows of the laboratory-prepared ethanol and generated bioethanol were 289.54 and 253.06 (g/m2 h), respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • A two-phase mass transfer model of paper-based microfluidic fuel cell is proposed. • The coupling characteristics of capillary action and two-phase flow are revealed. • The fluctuation mechanism of cell performance and gas distribution is explored. • Gas removal strategies are summarized, with a maximum gas removal rate of 42.30%. Paper-based microfluidic fuel cell powered by capillary force has the advantages of compactness, low cost, and high sensitivity, presenting broad application prospects in portable electronic devices. However, the gas-liquid mass transfer mechanism within the porous medium remains unclear, with a lack of two-phase flow theories adapted to the unique paper-based system. In this study, a two-dimensional two-phase numerical model of a Y-shaped paper-based microfluidic fuel cell is developed to reveal the two-phase flow characteristics under capillary action and explore gas removal strategies. The reliability of the model is validated by real experimental data. By coupling multiple physical fields, the study elucidates the working principle and gas-liquid flow phenomena within the cell. Then, the effects of contact angle, inlet fuel concentration, and paper type on output performance, gas distribution, parasitic effect, and fuel utilization are discussed. The results indicate that increasing the contact angle and using paper with a larger average pore size and porosity as the channel substrate are ideal for promoting gas discharge. The optimal gas removal rate reached 42.30 %, with a favorable power density of 33.92 mW/cm2. This study provides a theoretical basis for a deeper understanding of the two-phase mass transfer process in paper-based microfluidic fuel cell. [ABSTRACT FROM AUTHOR]

• Efforts to enhance PMFC performance are reviewed. • Both exciting advancements and current limitations are discussed. • An innovative strategy of multi-scale simultaneous optimization is proposed. Paper-based microfluidic fuel cell (PMFC) has attracted great attention in the microfluidic fuel cell field in recent years. It utilizes the spontaneous capillary flow of reactant solutions in paper-based porous substrate to achieve passive transportations of fuel and oxidant, solving the fluid driving issue encountered in traditional microfluidic fuel cells and thus having broad application prospects in medical detection, wearable devices, micro sensors, environmental monitoring, and many other fields. However, the commercialization of this technology is impeded by the low output performance caused by the limited mass and energy transfer in PMFCs. To enhance the mass and energy transfer in PMFCs, numerous research studies have been conducted via experimental optimization of the cell materials and structures. Numerical analyses focusing on the structure–activity relationship of PMFCs were also performed recently. To provide a comprehensive and thorough review about the efforts devoted to improving performance of PMFC, research papers relevant to PMFC since its invention in 2014 have been extracted in this work and significant works were filtered to highlight the exciting advancements. The experimental studies were classified and discussed based on the key components involved in the PMFC system, followed by a critical review of the limited computational models. Potential directions for future research were also provided, aimed at overcoming the current technological challenges in PMFCs. Importantly, an innovative strategy of multi-scale simultaneous optimization of the cell properties is proposed considering the typical multi-scale feature of the PMFC system, which could inspire the designing of advanced cell materials with optimal multi-scale structures for applications of PMFCs. [ABSTRACT FROM AUTHOR]

Pyrolysis of paper mill sludge (PMS) was conducted to produce syngas (H 2 and CO) and fabricate magnetic biochar (PMS biochar) for use as an adsorbent for As(V). The enhanced generation of CO was observed in the CO 2 atmosphere due to reactions triggered by CO 2 . Particularly, the generation of syngas from pyrolysis of PMS in CO 2 (9.6 mol% at 720 °C) was superior to the cases of pyrolysis of acid-washed PMS ( i.e. , minerals-eliminated PMS) in CO 2 (2.9 mol% at 720 °C), which evidences catalytic effects attributed by Fe and Ca species contained in PMS. Based on the results of X-ray diffraction (XRD), pyrolysis of PMS in CO 2 led to the conversion of Fe species into magnetite (Fe 3 O 4 ) solid phase that imparted the magnetic property to the biochar (saturation magnetization: 28.4 emu g −1 ). The PMS biochar exhibited high As(V) adsorption capacity of 34.1 mg g −1 in a given condition, which could be attributed to the great adsorption affinity of Fe 3 O 4 /CaCO 3 mixture toward As(V). The integrated approach for the utilization of PMS could satisfy growing demand for renewable energy and environmental sustainability. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility of combining different forest industries (a pulp and paper mill, its supply chain, and a wood-pellet plant) into an integrated industrial site in which they share a common heat and power utility. Advanced process integration and optimization techniques are used to study the site from both material and energy viewpoints. An existing pulp and paper mill is used as the site core plant and its pulp and paper production rates are kept fixed as they are in reality, while the other material flow links among the plants are based on the current industrial situation in Sweden. Different scenarios are evaluated in order to reflect the two main objectives that can be pursued (increased electricity production or biomass resource saving) and the two technologies that can be considered for the shared CHP system (boilers and product gas fired gas turbines). The corresponding non-integrated (standalone) configurations are compared to these scenarios to quantify the potential benefits of the integration. Investment opportunity is also calculated for the considered scenarios as an indicator of the economic convenience. [ABSTRACT FROM AUTHOR]

Pulp and paper mill effluent (PPME), a rich cellulosic material, was found to have great potential for biohydrogen production through a photofermentation process. However, pretreatments were needed for degrading the complex structure of PPME before biohydrogen production. The aim of this study was to gain further insight into the effect of an ultrasonication process on PPME as a pretreatment method and on photofermentative biohydrogen production using Rhodobacter sphaeroides NCIMB. The ultrasonication amplitudes and times were varied between 30–90% and 15–60 min, respectively, and no dilution or nutrient supplementation was introduced during the biohydrogen production process. A higher biohydrogen yield, rate, light efficiency and COD removal efficiency were attained in conditions using ultrasonicated PPME. Among these different pretreatment conditions, PPME with ultrasonication pretreatment employing an amplitude of 60% and time of 45 min (A60:T45) gave the highest yield and rate of 5.77 mL H 2 /mL medium and 0.077 mL H 2 /mL h, respectively, while the raw PPME without ultrasonication showed a significantly lower yield and rate of 1.10 mL H 2 /mL medium and 0.015 mL H 2 /mL h, respectively. The results of this study demonstrated the potential of using ultrasonication as a pretreatment for PPME because the yield and rate of biohydrogen production were highly enhanced compared to the raw PPME. Economic analysis was also performed in this study, and in comparison with raw PPME, the highest net saving was $0.2132 for A60:T45. [ABSTRACT FROM AUTHOR]

Pyrolysis is a promising technology for the production of marketable energy products from waste mixtures, as it decomposes heterogeneous material into homogenous fuel products. This research assessed the ability of slow pyrolysis to convert three waste streams, composed of fibre residues contaminated with different plastic mixtures, into char and tarry phase products at three different temperatures (300, 425 and 550 °C). The products were characterised in terms of mass yield, higher heating value (HHV) and gross energy conversion (EC). Significant amounts of hydrocarbon plastics in the feed materials increased the calorific values of the char (up to 32.9 MJ/kg) and tarry phase (up to 42.8 MJ/kg) products, comparable to high volatile bituminous A coal and diesel respectively. For all three waste streams converted at 300 °C, the majority of the energy in the feedstock was recovered in the char product (>80%), while deoxygenation of fibre component resulted in char with increased calorific value (up to 31.6 MJ/kg) being produced. Pyrolysis at 425 °C for two of the waste streams containing significant amounts of plastic produced both a valuable char and tarry phase, which resulted in an EC greater than 74%. Full conversion of plastic at 550 °C increased the tarry phase yield but dramatically decreased the char HHV. The influence of temperature on product yield and HHV was discussed based on the pyrolysis mechanisms and in relation to the plastic composition of the waste streams. [ABSTRACT FROM AUTHOR]

A large amount of sheep dung (SD) produced on farms in China is a potential feedstock for production of clean energy in the form of biogas. Similarly, waste paper can be a notable energy source that is worth exploiting. In this study, we assessed the feasibility of co-digesting nitrogen-rich SD with the carbon-rich corrugated board (CB) or waste office paper (OP) in varying volatile solids (VS) ratios, to produce methane. Synergistic effect of co-digesting SD with CB and SD with OP on methane production was found in this study. The highest methane yields of 151.62 and 198.85 mL/g-VS were obtained during the co-digestions of SD with CB at 4:1 ratio (SDCB) and SD with OP at 2:3 ratio (SDOP), respectively. High-throughput 16 S rRNA gene sequencing demonstrated that the microbial diversity and richness in SDCB and SDOP co-digests were higher than in SD and OP mono-digests, respectively. Characteristic bacteria and archaea in the digests were strongly substrate-related and might contribute to methane production. The validated results indicated that methane production through anaerobic co-digestion of SD and waste paper can be an efficient way that could not only reduce environmental pollution but also contribute to methane production. [ABSTRACT FROM AUTHOR]

Pulp and paper industry is a water-intensive industry. This industry commonly produces considerable amount of effluent, especially from virgin raw materials processing. The effluent, namely pulp and paper mill effluent has the potential to adversely affect the receiving watercourses. However, the nutrients in the pulp and paper mill effluent could be reused as a substrate in biohydrogen production. In this study, photofermentative biohydrogen production was investigated using Rhodobacter sphaeroides and pulp and paper mill effluent as a substrate. An application of low power ultrasound on R. sphaeroides was predicted to increase photofermentative biohydrogen production but excessive ultrasound effects might inhibit the production due to possible cell disruption. Hence, various ultrasonication duration (5, 10 and 15 min) and amplitude (15%, 30% and 45%) were applied on the bacteria to determine the recommended ultrasonication conditions for improving biohydrogen production. The recommended conditions were operated at ultrasonication amplitude and duration of 30% and 10 min, respectively. A maximum biohydrogen yield of 9.62 mL bioH 2 /mL medium was obtained under this condition, which was 66.7% higher than the result obtained using R. sphaeroides without undergoing ultrasonication (control). The light efficiency and cell concentration were increased by 67% and 150%, respectively, using ultrasonication amplitude and duration of 30% and 10 min, respectively as compared to the control. The present results demonstrated that moderate power of ultrasonication applied on R. sphaeroides was an effective method for enhancing photofermentative biohydrogen production using raw pulp and paper mill effluent as a bioresource. [ABSTRACT FROM AUTHOR]

The improvement of batch photofermentative biohydrogen production was investigated using ultrasonication pre-treatment on a combined effluent of palm oil and pulp and paper mills. The effects of the amplitude (30–90%) and ultrasonication duration (5–60 min) were investigated in terms of their influences on the biohydrogen yield and chemical oxygen demand (COD) removal. The recommended ultrasonication parameters were found at the higher ranges of amplitude and duration (A70T45). Using A70T45 ultrasonication, the production of biohydrogen at 30 °C could be enhanced up to 8.72 mL H 2 /mL medium , with a total COD removal of 36.9%. During pre-treatment at A70T45, an energy input of 775 J/mL was supplied to disintegrate complex compounds into simpler structures. As a result, an increase in the soluble organic matter concentration was achieved, which led to enhanced biohydrogen production. On the other hand, the lowest biohydrogen yield (4.67 mL H 2 /mL medium ) and total COD removal (28.8%) were obtained in the control without pre-treatment. The enthalpy of the photofermentation process was estimated to be 141.1 kJ/mol with a threshold temperature of 30.9 °C based on a modified Arrhenius approach. [ABSTRACT FROM AUTHOR]

The performance of vacuum, slow and fast pyrolysis processes to transfer energy from the paper waste sludge (PWS) to liquid and solid products was compared. Paper waste sludges with low and high ash content (8.5 and 46.7 wt.%) were converted under optimised conditions for temperature and pellet size to maximise both product yields and energy content. Comparison of the gross energy conversions, as a combination of the bio-oil/tarry phase and char (EC sum ), revealed that the fast pyrolysis performance was between 18.5% and 20.1% higher for the low ash PWS, and 18.4% and 36.5% higher for high ash PWS, when compared to the slow and vacuum pyrolysis processes respectively. For both PWSs, this finding was mainly attributed to higher production of condensable organic compounds and lower water yields during FP. The low ash PWS chars, fast pyrolysis bio-oils and vacuum pyrolysis tarry phase products had high calorific values (∼18–23 MJ kg −1 ) making them promising for energy applications. Considering the low calorific values of the chars from alternative pyrolysis processes (∼4–7 MJ kg −1 ), the high ash PWS should rather be converted to fast pyrolysis bio-oil to maximise the recovery of usable energy products. [ABSTRACT FROM AUTHOR]

[Display omitted] • Various carbon nanotube-based devices are developed for solar energy utilization. • The water evaporation system can generate freshwater (1.28 kg m−2h−1). • The solar-thermoelectric system can output a voltage and charge a cellphone. • The supercapacitor performs an areal specific capacitance of 19.6 mF cm−2. • The hybrid energy system can produce freshwater, generate and store electric power. Nowadays, multi-functional systems driven by solar energy have been explored to alleviate the crisis of energy and freshwater scarcity. However, it remains a great challenge to integrate multi-functions into one hybrid system with a monolithic material, which can harvest, convert and store solar energy synergistically. Here, we firstly propose a multi-functional carbon nanotube paper, which starts from a material level to solve these problems. The carbon nanotube paper is fabricated by vacuum filtration. It exhibits high efficiency of solar-thermal conversion. Secondly, three types of energy conversion/storage systems (e.g., solar-thermal evaporation system, solar-thermoelectric generation system, and supercapacitor) are constructed based on the carbon nanotube paper, which extend the research to a device level. The solar-thermal evaporation system shows an evaporation rate of 1.28 kg m-2h−1 under simulated sunlight irradiation of 1 kW m−2. The solar-thermoelectric generation system demonstrates a stable electric power generation with an output voltage of 100 mV under light irradiation of 1 kW m−2. The supercapacitors perform the energy storage function with an areal specific capacitance of 19.6 mF cm−2. These devices and systems can be used in freshwater generation (0.84 kg m-2h−1, sunlight irradiation of 1 kW m−2), water purification/desalination (inorganic ions rejection larger than 99.9%) and portable solar charging system (maximum output voltage of 5 V). Finally, a hybrid energy system is innovatively proposed from the system level to simultaneously produce freshwater, generate and store electric power. Through the synergetic coupling of solar conversion and storage technologies, the hybrid energy system can supply sustainable freshwater and electricity for remote areas in daily life, highlighting the superiority of multi-energy (thermal energy, electrical energy, and electrochemical energy) complementary. [ABSTRACT FROM AUTHOR]

Pyrolysis process of coffee paper cup samples was investigated in a flow stream of nitrogen at different heating rates (10, 20, 30 and 40°Cmin−1), using thermo-analytical techniques. It was found that second pyrolysis stage can be described by Šesták-Berggren (SB) autocatalytic model, with mechanism function f(α)=α0.011(1−α)1.459. Based on analysis of SB kinetic exponents (designated by M and N), it was found that second pyrolysis stage is mainly controlled by chemical process, involving reactions with reaction-order (n) higher than unity. Applying specific statistical analysis, in order to obtain precise distribution of reactivity, the discrete (binomial) distribution has shown that there are two important areas of current distribution for corresponding energy outcomes, within the apparent activation energy as random variable. The first "concentration" area of energy outcomes corresponds to start of chain end depolymerization reaction forming levoglucosan at high enough temperature region, while second "concentration" area of energy outcomes includes occurrence of macro-radicals in liquid phase propagate with radical addition on unsaturated C-C bonds, with cross-linking and formation of small chemical species. It was found that further elevating of temperature (above 340°C), will leads to fact that rate of tar-forming reactions increases and formation of char decreases. [ABSTRACT FROM AUTHOR]

An ultrasonication technique was applied intermittently onto photofermentation broth during the first six hours of photofermentation to improve biohydrogen production by using Rhodobacter sphaeroides NCIMB8253. In this research, photofermentation broth consisted of a combination of palm oil (25%, v/v), pulp and paper (75%, v/v) mill effluents as well as liquid inoculum. The effects of amplitude (10, 20 and 30%, A) and ultrasonication duration (5, 10 and 15 min, T) were investigated in terms of their influences on photofermentative biohydrogen yield and total chemical oxygen demand (COD total ) removal. The recommended ultrasonication parameters were found at the middle range of amplitude and duration (A20T10). Using A20T10 intermittent treatment, the production of biohydrogen could be maximized up to 14.438 mL H 2 /mL medium with a COD total removal and light efficiency of 52.2% and 7.412%, respectively. By comparing the treatment without intermittent ultrasonication, an increase of biohydrogen yield by 44.6% was achieved in A20T10 treatment. A total energy input of 306.1 J/mL (A20T10 treatment) was supplied to improve substrate consumption and light distribution during the photofermentation, which led to the increase of biohydrogen yield. [ABSTRACT FROM AUTHOR]

The thermal characteristics and kinetics of paper mill sludge (PMS), municipal solid waste (MSW) and their blends in the combustion process were investigated in this study. The mass percentages of PMS in the blends were 10%, 30%, 50%, 70% and 90%, respectively. The experiments were carried out at different heating rates (10 °C/min, 20 °C/min and 30 °C/min) and the temperature ranged from room temperature to 1000 °C in a thermogravimetric simultaneous thermal analyzer. The results suggested that the ignition temperature and burnout temperature of MSW were lower than that of PMS, and the mass loss rate of MSW was larger especially at low temperatures. There were only two mass loss peaks in the differential thermogravimetry (DTG) curve, while three mass loss peaks were observed when the blending ratios of PMS were 30%, 50%, 70%. The value of the comprehensive combustion characteristic index of the blends indicated a good combustibility when the percentage of PMS (PPMS) in the blends was less than 30%. There existed certain interaction between the combustion process of PMS and MSW, especially at high temperature stage. Activation energy ( E ) value obtained by the Ozawa–Flynn–Wall (OFW) method and the Starink method were very consistent. When the mass percentage of PMS in the blends was 80%, the E average value attained the minimum. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel method to estimate total technical potential for improving energy efficiency. • Bottom-up sector energy model used to characterize energy demands and opportunities. • Technology-explicit analysis framework used to estimate integrated energy savings. • Application to Canada's pulp & paper sector indicates major savings are possible. • Technical potential to reduce natural gas use by 95% and net electricity by 54% Industrial energy efficiency has long been recognized as a critical tool for energy management and emissions reduction and is increasingly considered to be an energy resource in its own right. However, the complexity of most industrial sectors creates barriers for modellers, companies, and policymakers in understanding and achieving the overall potential for efficiency-driven energy savings. To address this gap, we have developed a novel method that combines disaggregated bottom-up sector energy modelling with analysis of a comprehensive set of technology-explicit energy efficiency measures. This approach overcomes the deficiencies of top-down analyses and better represents the complexities of multi-measure efficiency investments compared to piecewise studies of individual measures. In this study, we demonstrated application of our method to the case of the Canadian pulp and paper sector. Our analysis shows that the sector can reduce its natural gas and electricity use by 95% and 41%, respectively, by adopting economical efficiency measures. This equates to 71 PJ of natural gas and 44 PJ of electricity saved annually and would result in cost savings of $81 per tonne of output sector-wide. Notably, we find that efficiency and fuel switching have the technical potential to reduce natural gas consumption by 98% across the sector. Taken together, the results provide quantitative evidence that energy efficiency is an underestimated resource for cost-effective energy savings in the Canadian pulp and paper sector. Our analysis framework can be applied to any industrial sector in any region to provide insights regarding energy conservation strategies and policy design. [ABSTRACT FROM AUTHOR]

In the present study, the extraction of polyester like polyhydroxyalkanoates (PHAs) from enzymes extracted sludge was investigated by varying extraction time and chloroform – sodium hypochlorite dosage. Maximum of 874 mg/g of PHAs was achieved at an optimum extraction time of 120 min and chloroform – sodium hypochlorite dosage of 30% v/v. The characteristics of derived PHAs were examined using Fourier transform infrared (FTIR) spectroscopy and Nuclear magnetic resonance ( 1 H NMR) spectroscopy. Then, the effect of derived PHAs dosage on biomethane production from pulp and paper mill secondary clarifier (PPSC) sludge was studied. Higher amount of biomethane production was observed to be 174 L/(kg VS) at 35 mg of PHAs dosage when compared to other dosage. To further enhance biomethane production, disperser pretreatment method was carried out by optimization of specific energy. At optimum specific energy of 8547 kJ/kg TS, the maximum solubilization rate and suspended solids (SS) reduction were found respectively to be 19% and 15.8%. Then, biomethane assay was conducted on disperser pretreated sludge, disperser pretreated sludge with optimized PHAs dosage (35 mg) and control sludge. Among these, disperser mediated PHAs method exhibited maximal biomethane production and was observed to be 267 L/(kg VS). Hence, PHAs based sludge treatment method can be implemented in sludge management studies by retrieval of value added product and PHAs canbe used to enhance biomethane production sustainably. [ABSTRACT FROM AUTHOR]

In this work, the types of products and their proportions, the evolution characteristics of the functional groups and gases products, the pollutants emission of combustible solid waste (CSW), paper mill sludge (PMS) and their blends were investigated by Py-GC/MS and TG-FTIR. For the blends, the proportions of PMS were 10%, 30% and 50%. The percentage of pyrolysis products (acid, hydrocarbon, aldehyde, alcohol, benzene, furan, phenol, ester and ketone) was pointed out. Among these, the content of acid was the maximum. Blended with 10% PMS, the percentage of alcohol reached the greatest. Both single sample and blends could be divided into two decomposition phases. The residue mass of blends increased from 17.74% to 30.47% with the PMS ratio increased. O H, C H, C O, C O, SO 2 , NO, HCl, CO, CH 4 and CO 2 were the main functional groups and gases products surveyed from the FTIR spectrums during co-pyrolysis. Adding PMS into CSW could reduce the emission of the pollutants and the lowest yield of pollutants (SO 2 , NO, HCl, CO and CO 2 ) would be obtained covered with 50% PMS. [ABSTRACT FROM AUTHOR]

[Display omitted] • A methodical approach for understanding the paper-based microfluidic fuel cells. • Fabrication strategies of various paper-based microfluidic fuel cell has been reviewed. • Paper-based microfluidic fuel cells with different types of fuels are summarized and compared. • Stacking efficiency is compared among different paper-based microfluidic fuel cell stacks. • Applications, challenges and prospects have been discussed. Since they firstly appeared in 2014, paper-based microfluidic fuel cells (PMFC) have received great attention in the past few years, mainly being used for sensors, wearable devices, point-of-care testing and diagnostics. This fuel cell technology exploits the intrinsic characteristics of paper substrate and microfluidic flows of reactant streams eliminating the need for external pumps and conventional membranes. PMFCs operate in a co-laminar flow configuration, and the absence of convective mixing across the liquid–liquid interface of two streams forms a distinct diffusive mixing region, which acts as a pseudo–membrane. The hydrophilicity and porosity of paper substrate allows reactants to flow by capillarity with the assistance of an absorbent pad. Ions can be transported across the channel through the mixing region to reach the other side of the channel and complete ionic conduction. To date, several fuels have been utilised in PMFCs, such as formate, hydrogen, formic acid, hydrogen peroxide, hydrocarbons, borohydride, hydrazine, and biofuels, each of which has specific advantages and disadvantages. This review article summarises the growth of PMFC technology, from its invention in 2014 until the present, with emphasis on fundamentals, fabrication methods, unit cell performance with various fuels, performance achievements, design considerations, and scale-up options. The applications and main challenges associated with the current status of the technology are provided along with future perspectives. Investigations in recent years have shown that PMFCs developed with different fuels enhance power density from several µWcm−2 to several mWcm−2 and that stacking multiple individual cells increases the working voltage. Moreover, enzymatic and microbial PMFCs show great potential to be used as wearable devices, sensors and in lab-on-chip devices. [ABSTRACT FROM AUTHOR]

The pyrolysis characteristics of municipal solid waste (MSW), paper sludge (PS) and their blends were studied through a thermogravimetric simultaneous thermal analyzer from room temperature to 1000 °C. Meanwhile their kinetics were studied by Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) methods. The mass proportions of PS in the blends were 10%, 30%, 50%, 70%, 90%, respectively and the experiments were carried out at different heating rates (30, 40 and 50 °C/min). The initial temperature of MSW was lower than that of PS and the terminated temperature was higher than PS. The comprehensive characteristic index decreased progressively along with the decrease of the MSW proportion. The values of average activation energies calculated by FWO and KAS methods were highly consistent. The average activation energy reached the minimum number, 96.7 kJ/mol by KAS and 11.56 kJ/mol by FWO, with the proportion of PS was 50%. [ABSTRACT FROM AUTHOR]

Biomass from waste newspaper (WP) was first co-pyrolyzed with high-density polyethylene (HDPE) in order to enhance the oil yield and its fuel properties. The synergistic effects during co-pyrolysis were investigated in terms of entire pyrolysis process, products yield and properties of liquid products (aqueous phase and oil phase) using thermogravimetric analysis coupled with infrared spectroscopy (TG-FTIR), physical properties analysis, elemental analysis, Fourier transform infrared spectroscopy (FT-IR), and gas chromatography/mass spectrometry (GC/MS). The results showed that synergistic effect occurred at 400–500 °C resulting in an obviously increase in oil phase by 31.59% as compared to theoretical data. Positive synergistic effects on fuel properties of co-pyrolysis oil were observed, especially demonstrating dramatically decrease in viscosity and total acid number by 75.96% and 216.04% in comparison to theoretical data. WP pyrolyzed alone gives mainly oxygenated compounds in its derived oil, while HDPE give hydrocarbons. No cross reaction products appeared in co-pyrolysis oil, implying that the synergistic effects were determined by altering its compounds content rather than generating cross reaction products. Unfortunately, aqueous phase and oil phase exhibit similar composition. [ABSTRACT FROM AUTHOR]

• Different configurations of TEM were tested in this research. • 6-Jointed TEM provided around 100% higher COP in the same power input. • A comprehensive sensitivity analysis was carried out for 6-jointed mode. • Perforation technique was employed to further enhance the COP. • Spring wire was used to further improve the COP of the cooler. Although individual commercial thermoelectric module has been widely investigated and its cooling behavior is clear, jointed thermoelectric modules show completely different cooling behavior and higher coefficient of performance (without the change of input electrical power) which requires further study. At the first step of this research, cooling characteristics of 2-jointed, 4-jointed and 6-jointed thermoelectric modules are experimentally evaluated and discussed under the same range of input electrical power. In the same total input electrical power, 6-jointed TEM (thermoelectric module) provided around 100% higher COP (coefficient of performance) than the 2-jointed TEM which was significant. Cooling behavior of different-number jointed TEM (in the same input power) are analyzed and discussed in this paper. In the second step of this research, the COP of 6-jointed TEM cooler (selected from the first step) has been increased again by proposition of two new techniques based on the modification of the popular rectangular-fin heat sink. Attempts are made to further enhance the COP of the system by two methods including "perforating technique" and "spring wire technique" through a Peltier air cooler which have not been proposed before. In the same electrical power input, perforating technique enhanced the thermal performance of the Peltier air cooler around 50% (totally 150% compared to the 2-jointed TEM with simple heat-sink) and the use of spring-wire between the fins of heat-sink improved the COP around 130% (totally 230% compared to the 2-jointed TEM with simple heat-sink). Exact explanation of the quality/quantity and improvement reasons of each technique are described in this paper for different working conditions of the cooler. [ABSTRACT FROM AUTHOR]

• Operation and construction of an energy hub based upon the flexibility. • The flexibility index covers maximum system capacity and system response time. • Effect of energy hub flexibility on battery aging. • Consumer participation rate prediction in demand response programs by deep learning. Energy hubs (EHs), hold promise for improving energy efficiency and mitigating carbon emissions. The increasing renewable energy resources, with its inherent uncertainty and variability in power generation, presents challenges for power systems, thereby highlighting the importance of flexibility. This paper proposes a multi-objective framework for enhancing EH flexibility. It is expected that flexibility can induce battery aging which is demonstrated in this paper. The framework leverages a novel flexibility index encompassing both capacity and response time to optimize EH configuration and operation. In this paper employs a data-driven approach to analyze battery degradation under varying flexibility demands. This analysis informs the acceleration of aging associated with increased flexibility. Given the critical role of flexibility, this paper investigates the tripartite relationship between flexibility, time, and battery lifespan. Additionally, considering Demand Response Programs as crucial flexibility resources, the proposed framework utilizes deep learning to forecast consumer participation rates. Utilizing historical data on temperature, price, and participation, various deep learning models are compared. Results indicate a 30% reduction in operating costs associated with a 12% increase in flexibility. However, this flexibility comes at the cost of increased manufacturing expenses and a 20% decrease in battery lifespan due to operational fluctuations. [ABSTRACT FROM AUTHOR]

• Optimize retrofitting strategies by simulation-based multi-objective optimization. • Compare the retrofitting strategy and reconstruction strategy by emergy analysis. • Consider the large domain strategy space of building retrofitting strategy. • NSGA-III algorithm, EnergyPlus software, emergy analysis and LCA are integrated. • The retrofitting strategy is better than the reconstruction strategy. Building renewal has become a promising approach for improving energy efficiency and reaching carbon neutrality targets. Two renewal strategies, namely, the retrofitting of existing buildings and their demolition and reconstruction of a new one, are often explored and compared to determine which strategy is the optimal one. However, the decision is still uncertain due to the large domain space of strategies and the lack of comprehensive methods. This paper, therefore, presents a novel hybrid method to help decision-makers identify the optimal building renewal strategy based on the integration of multi-objective optimization algorithm with emergy analysis. A simulation-based non-dominated sorting genetic algorithm is developed to select the optimal retrofitting strategy, where dynamic simulation model is created in EnergyPlus software and non-dominated sorting genetic algorithm is written in Python. Then, the equivalent reconstruction strategy is projected by the optimal retrofitting strategy while meeting mandatory standards. A comparison between the optimal retrofitting strategy and the equivalent reconstruction strategy can be made by applying emergy analysis considering the whole life cycle phase. A fictional office building was chosen as a case study to illustrate the practical implementation of the proposed method. High-cost building retrofitting strategies were found to consistently yield the highest energy savings and thermal comfort, and the energy use decreased by 4.63 % to 48.25 %. The input emergy of the original building, retrofitting building and reconstruction building are 3.16E + 20 sej , 1.41E + 21 sej , and 1.46E + 21 sej , respectively, and the output emergy are 2.39E + 20 sej , 1.66E + 20 sej , and 4.76E + 19 sej. The results also indicate that the sustainability of the retrofitting strategy is better than that of the reconstruction strategy. This paper provides a guidance method and framework for decision-makers and policy-makers to identify the optimal building renewal strategy for reducing the energy use and achieving carbon peak targets. [ABSTRACT FROM AUTHOR]

Design of hybrid Nano-Grid system (HNGS) necessitates a careful thought to benchmark reliable and cost effective solutions for remote areas. Optimal sizing of HNGS using Honey Badger Algorithm (HBA) for futuristic residential area in Mahendragarh, Haryana, India is presented in this paper. The HNGS comprise combination of solar panels, wind turbines, storage batteries, diesel generator, inverter and residential load components. The primary objective functions considered in this paper are Cost of Electricity (COE) and Net Present Cost (NPC), in continuation these problems are stated as multi objective optimization issues. Numerous permutations of diverse resources were examined to assess parameters such as NPC, COE, battery storage, land utilization, emission and potential employment opportunities. HBA is almost independent of traps in the local minimum, therefore the results obtained are superior as compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Biogeography Basic Optimization (BBO), Improved Artificial Ecosystem Optimization (IAEO) and Grey Wolf Optimization (GWO) as well as HOMER software, in order to determine the quality of solution the proposed HBA algorithm has obtained. HNGS system can be readily and efficiently optimized using the suggested HBA algorithm a detailed sensitivity analysis is done to better understand the system behavior for a wider region use. • A well optimized HNGS design is cost-effective, highly reliable and simple system for remote areas. • An optimization problem is formulated and solved by means of Honey Badger algorithm. • The optimization aim is to find HNGS size in terms of number of individual sources which supplies demand successfully. • Outcomes show that HBA effectively optimizes HNGS by lowering the NPC and CoE, ensuring the electricity supply. • The HBA's results has been compared to GA, PSO, BBO, IAEO, and GWO, as well as HOMER software. • Sensitivity analysis has been used to explore the impact of weather and component parameters on COE and NPC. [ABSTRACT FROM AUTHOR]

[Display omitted] • A method for predicting the irradiance of PV greenhouse in many cases was proposed. • Four models were discussed at variable time, data size and climatic conditions. • The instantaneous irradiance prediction under 9 weather conditions was provided. • Transformer model had the best prediction effect for dataset at one year of usage. • Pyraformer model had the best prediction effect on winter and summer. Photovoltaic power generation can provide energy for greenhouses and achieve high quality and high yield of crops. In reality, solar irradiance is fluctuating and intermittent. Thus, the key to ensure efficient photovoltaic power use under greenhouse environmental conditions is to provide an accurate prediction of solar irradiance. Yet, currently studies on irradiance prediction in terms of the variable time lengths, multi-parameter and full climate conditions are rather limited. To improve the comprehensive performance of the prediction model, this paper proposes models of irradiance time series prediction such as Pyraformer, Informer, Transformer and TimesNet. Those models were tested based on the synergistic combination of weather conditions (WC), sunshine time accumulation (STA/h), instantaneous total irradiance (ITI/(W/m2)) and irradiance daily accumulation (IDA/(MJ/m2)). The model performance was rigorously evaluated with 9 prediction lengths, 5 training days, 4 seasons and 5 days for 9 weather conditions. The results showed that the Transformer model had the best overall prediction performance for STA, ITI, IDA and WC at different time steps of 10 min to 24 h. All models were suitable for predicting time series within 1 h. However, TimesNet model was not suitable for predicting time series with steps outside 1 h. On the other hand, by using the sun combination dataset, the Transformer model had the best performance at a time step of 10 min. The mean absolute error (MAE), mean-square error (MSE), root mean squared error (RMSE) and coefficient of determination (R2) of ITI were 0.118 W/m2, 0.059 W/m2, 0.243 W/m2 and 93.9 %, respectively. When exploring the minimum dataset, with the increase of data samples, the prediction effect of TimesNet showed an increasing trend. While, Transformer had the best prediction effect for the dataset with one year of use. When exploring seasonality, Pyraformer model had the best prediction effect on winter and summer, and TimesNet had the best prediction effect on autumn and spring. Local prediction of 9 climate conditions showed that the effects of snow and dust storm were not ideal. The research results showed that the characterization factors that were closely linked to irradiance. The prediction scheme proposed in this paper combined the advantages of different time steps, different factor combination datasets, different data volumes and seasonality, which greatly improves the generalization ability of the model. This study can provide a reference for irradiance prediction and more refined management of photovoltaic (PV) greenhouse. [ABSTRACT FROM AUTHOR]

• Develop algorithms for sizing grid-connected bifacial PV power plants. • HHOSA identifies the optimal configuration of components and installation parameters for bifacial PV power plants, maximizing or minimizing performance metrics. • HHOSA efficiently handles multiple design options within a short timeframe. • Techno-economic analysis of bifacial PV power plant. • Sensitivity analysis on bifacial PV parameters, cost considerations, and tailored ground cover enhance bifacial PV power plant success. This paper presents an optimal design for ground-mounted grid-connected bifacial PV power plants using a Computational Intelligence (CI)- based Harris Hawks Optimization (HHO) algorithm. This HHO algorithm identifies the best configuration of components and installation parameters for the bifacial PV power plant, aiming to maximize the final yield, minimize the Levelized Cost of Electricity, and boost the Net Present Value. Four variables were optimized: the bifacial PV module model, inverter model, tilt angle, and module elevation. Furthermore, the paper introduces a Harris Hawks Optimization Sizing Algorithm (HHOSA) to address the sizing challenges. The presented HHOSA was purely developed in Matlab R2017b. The usage of PVsyst was only limited to the derivation of irradiation data at different tilt angle of PV array. These data were later used in HHOSA. To verify its effectiveness, HHOSA was benchmarked against other CI algorithms, including the Slime Mould Algorithm (SMA), Firefly Algorithm (FA), Manta Ray Foraging Optimization (MRFO), and Cuckoo Search Algorithm (COA). The evaluation considered the algorithm's stability, local search capability, convergence rate, computation time, and required population size. Findings suggest that the HHOSA outperforms its peers, marking it as a potential leader for designing bifacial PV power plants. The results indicate that the HHOSA algorithm exhibits superior performance in these aspects, making it a promising approach for optimizing the design of bifacial PV power plants. Moreover, this study provides insights into the economic and technical viability of bifacial PV systems under various environmental and system conditions. A sensitivity analysis, focusing on the interplay of three decision variables − albedo values (25 %, 50 %, and 75 %), tilt angles (10°, 25°, and 35°), and module elevations (0.5 m, 1.5 m, and 2 m) − was conducted. It assessed their influence on final yield, additional bifacial PV module yield, Levelized Cost of Electricity, and the system's Net Present Value. The results emphasize the importance of carefully considering the impacts of albedo, module elevation, and tilt angle on the financial performance of bifacial PV installations. [ABSTRACT FROM AUTHOR]

• An adaptive MAE evaluation for the lithium battery in hybrid UAV applications was proposed. • An OSMO was developed to estimate the real-time lithium battery OCV. • Adaptive MAE evaluation for the lithium battery can be achieved with the real-time estimated OCV. • The MAE evaluation method was adaptive to dynamic ambient temperature and uncertain aging levels. Accurate evaluation of the maximum available energy (MAE) of the lithium battery is crucial for energy management and optimization in hydrogen-electric hybrid unmanned aerial vehicle (UAV) applications. However, uncertainties in ambient temperature and cell aging level would affect the MAE of the lithium battery, posing challenges for its accurate state evaluation. This paper presents an adaptive MAE evaluation method based on an optimized sliding mode observer (OSMO) for the lithium battery. The study begins by conducting comprehensive long-term experimental tests to analyze the dependencies of the lithium battery's MAE on different ambient temperatures and cell aging levels. Subsequently, an OSMO with a Kalman filter is developed to estimate the variations of the battery's open circuit voltage (OCV) on the basis of a dynamic lithium battery model. Furthermore, the real-time OCV is successfully used to achieve accurate adaptive MAE evaluation for the lithium battery. The originality of this paper is that the model parameters and proportional coefficients can be updated adaptively based on the OSMO with the Kalman filter. In this case, the OCV can converge to their actual value such that accurate MAE evaluation can be guaranteed, even with uncalibrated model parameters under dynamic ambient temperature and uncertain aging levels. Finally, experimental and simulation results verify that the proposed method exhibits a convergence speed four times higher than the traditional method. The mean absolute percentage error (MAPE) of MAE evaluation is less than 1.5 % under dynamic ambient temperature and uncertain aging levels. [ABSTRACT FROM AUTHOR]

• High specific speed Francis turbine as an alternative to low specific speed Kaplan/semi-Kaplan/Propeller turbine. • Comprehensive experimental studies of the high specific speed Francis turbine. • Multi-aspect experimental approach to determining the Thoma cavitation number. • Comprehensive vortex visualization for various cavitation states in the draft tube. • Saddles were found on the performance characteristics for high guide vane opening angles. The paper presents comprehensive experimental research on a high specific speed model Francis turbine with a characteristic runner diameter of 250 mm under the head of 12 m. Essentially, the turbine was designed for use at heads between 10 and 50 m, which are typical for installations with low specific speed Kaplan turbines. The basic performance, cavitation and runaway characteristics of the machine, which were determined as a result of the work, are quite rarely available in the literature in the case of high specific speed Francis turbines. The turbine achieved the maximum efficiency of 91%, kinematic specific speed of 82, and relatively wide operation range, so that it can be attractive as an alternative to the low specific speed Kaplan, semi-Kaplan or propeller turbines. In result of the basic laboratory tests, the performance characteristics of the machine operation in a wide range of guide vane opening angles between 9° and 36° as well as the shell efficiency characteristics were determined. On the characteristics plotted vs. rotational speed, the saddle effect was identified for the guide vane opening angles with values greater than the optimal one (22°). During the operation of the machine in the area of saddles, the change in the flow rate took quite surprising patterns. The share of the turbine thrust torque in the total torque was also determined, the characteristics of which are also burdened with a similar saddle effect. In the case of cavitation tests, a multi-aspect approach to cavitation diagnostics was used to characterize the cavitation phenomenon from the viewpoint of various criteria. Following this approach, the signals of the draft tube wall acceleration, acoustic emission at the draft tube cone upper flange, and pressure fluctuations inside the draft tube were used. The determined cavitation characteristics indicate little cavitation susceptibility of the Francis turbine blade system, despite the presented turbine having been designed to operate at higher flow rates than the classic high head Francis turbines with long interblade channels. The cavitating flow in the draft tube, directly below the runner, was also visualized during the cavitation tests. The paper presents the results of visualization for all cavitation states at five selected settings of the guide vane opening angle (two states in Partial Load, two states in High Load area and one state in the Best Efficiency Point), thanks to which it was possible to track the development of vortices during pressure reduction in the flow system. The runaway coefficient was determined as a result of the runaway tests. The value of 1.497 was reached at the optimum guide vane opening angle. Additionally, the work also presents in detail the efficiency scale effects to be expected at prototype turbines, i.e. those intended for operation at a higher head and with larger runner diameters. The efficiency of the machine with a runner diameter of 1.5 m and working at a head of 50 m reaches ∼93%. The influence of water viscosity on the change in efficiency of the prototype turbine is also shown. The presented methodology can be used for the proper selection of turbines intended for hydropower plants and for the proper installation of the runner in respect to the tailwater level in order to avoid the phenomenon of cavitation erosion. [ABSTRACT FROM AUTHOR]

• A novel wind power prediction method based on influencing factors is proposed. • A multivariate model based on TCN-ReOSELM is proposed for the first time. • PC technology is utilized to process the input data of the model. • An improved AHA algorithm is introduced to optimize the TCN-ReOSELM model. • The superiority of the proposed model is verified by ten benchmark models. Highly accurate wind power prediction is important for the operation and management of wind farms, energy utilization and power supply. In recent years, in order to further improve prediction accuracy, some researchers have considered utilizing factors such as wind speed and wind direction to establish prediction models. However, this often results in input redundancy due to a lack of technical means. In this paper, a multivariate prediction model for wind power based on variational mode decomposition (VMD), fuzzy entropy (FE), partial auto-correlation function and cross-correlation function (PACF&CCF, abbreviated as PC), improved artificial hummingbird algorithm (IAHA), temporal convolutional network (TCN), and regularized online sequential extreme learning machine (ReOSELM) is proposed. To address the nonlinearity and non-stationarity of the original wind power time series and decrease computational costs, the VMD combined with FE data preprocessing technique is employed. Considering the information redundancy in the multivariate data, the PC technique is utilized to conduct correlation analysis on the input data and select highly correlated features as inputs. When the input is multivariate and high-dimensional, the ReOSELM model struggles to achieve satisfactory prediction performance. Therefore, a new model based on TCN-ReOSELM is constructed. Additionally, to overcome the drawbacks of manual parameter adjustment, an IAHA algorithm is proposed, which integrates Latin hypercube sampling and chaotic local search strategies, to optimize the crucial parameters of TCN-ReOSELM. The experimental results demonstrate that the multivariate method proposed in this paper reduces the RMSE by 31% compared to the univariate method. Specifically, the proposed VMD-FE-PC-TCN-ReOSELM model reduces the RMSE, MAE, and SMAPE by 60–64%, 55–58%, and 10–36%, respectively, compared to the PC-TCN-ReOSELM model. [ABSTRACT FROM AUTHOR]

• The novel preignition event (PEMC) was explored on HDI engines. • PEMC event occurred in the early/mid compression stroke and with the peak pressure at TDC. • PEMC events worsened NOx emissions, BP, and BTE in most cases. • Delaying injection timing beyond 180° CA BTDC could totally prevent PEMC events. • The established RF prediction model has excellent robustness and reliability. The potential use of hydrogen in automotive internal combustion engines could aid in the energy transition and contribute to achieving carbon neutrality. This paper has investigated the impact of operating parameters boundary for a novel preignition event on a 2.0L hydrogen direct injection (HDI) engine to address the challenge of abnormal combustion limiting the application of HDI engines. The identified characteristics of the event and its potential harm to the engine has been summarized. Experiments have shown that the novel preignition event predominantly occurred mainly during 170−80°CA BTDC, hence the name PEMC (preignition in the early/mid compression stroke) event, and caused a surge in cylinder pressure. In 77.2 % of the selected cases, the PEMC events resulted in increased NOx emissions. In 93.1 % and 91.5 % of the cases, there was a decrease in brake power and brake thermal efficiency, respectively. Unlike the low speed, high load preignition of gasoline engines, PEMC events were more likely to occur in the torque range of 70–100 Nm and could be monitored in a lean mixture environment with λ = 1.5–3.3. PEMC events were found in the interval of 180−320° CA BTDC at injection timing and were most intense at 240−250° CA BTDC. To prevent PEMC events completely, it is recommended to delay the injection timing beyond 180° CA BTDC. The paper has employed a model based on experimental data and Random Forest algorithms to predict PEMC events. The model demonstrated an accuracy of 98.76 % and 97.69 % for the training and test data, respectively. It has been effective in predicting the occurrence of PEMC events under various operating conditions. The paper has offered an alternative solution for the novel preignition in HDI engines. [ABSTRACT FROM AUTHOR]

[Display omitted] • Calcium looping (CaL) captures carbon dioxide and waste heat from industrial flue gases. • Methane dry reforming (MDR) produces blue hydrogen with high thermal energy penalty. • Synergy of MDR and CaL shows huge potentials for industry decarbonisation. • Major challenges are catalyst deactivation, sorbent sintering and system integration. Industry is the biggest sector of energy consumption and greenhouse gas emissions, whose decarbonisation is essential to achieve the Sustainable Development Goals. Carbon capture, energy efficiency improvement and hydrogen are among the main strategies for industrial decarbonization. However, novel approaches are needed to address the key requirements and differences between sectors to ensure they can work together to well integrate industrial decarbonisation with heat, CO 2 and hydrogen. The emerging Calcium Looping (CaL) is attracting interest in designing CO 2 -involved chemical processes for heat capture and storage. The reversibility, relatively high-temperature (600 to 900 °C) and high energy capacity output, as well as carbon capture function, make CaL well-fit for CO 2 capture and utilisation and waste heat recovery from industrial flue gases. Meanwhile, methane dry reforming (MDR) is a promising technology to produce blue hydrogen via the consumption of two major greenhouse gases, i.e., CO 2 and CH 4. It has great potential to combine the two technologies to achieve in-situ CO 2 utilization with multiple benefits. In this paper, progresses on the reaction conditions and performance of CaL for CO 2 capture and industrial waste heat recovery, as well as MDR were screened. Secondly, recent approaches to CaL-MDR synergy have been reviewed to identify the advantages. The major challenges in such a synergistic process include MDR catalyst deactivation, CaL sorbents sintering and system integration. Thirdly, the paper outlooks future work to explore a rational design of a multi-function system for the proposed synergistic process. [ABSTRACT FROM AUTHOR]

• A dynamic model for a 300 MW subcritical power plant boiler is developed. • A novel dynamic exergy analysis and assessment model is proposed. • The influence of drum level control on dynamic exergy behavior is evaluate. • The asynchronous responses are discussed in flow and heat transfer processes. • The dynamic exergy analysis reveals exergy destruction rates of heating surfaces. In the era of high penetration of renewable energy sources (RESs), traditional coal-fired power plants are facing increasing requirements of operational flexibility which is limited by the inherent slow dynamics of boiler. To this end, this paper presents a comprehensive dynamic model of the heating surfaces for a 300 MW power plant boiler and analyzes the exergy performance from the perspective of transient responses. Based on the object-oriented modelling language Modelica, the multi-domain first-principal model is developed by unifying the equations of thermal, mechanical, liquid and control components and interfaces. The model accuracy is validated by the field measurements. The model takes into account the multi-scale time constants in terms of the flow and heat transfer processes and drum level control. As an extension to the conventional steady-state thermodynamic analysis, a methodology of dynamic exergy analysis and evaluation is proposed. Dynamic simulation results well describe the initial reverse response of the drum level, i.e., false water level indicator, as a result of which the mass flow rate of feedwater exhibits the oscillatory performance. It is revealed that the step disturbances of flue gas mass flow and feedwater temperature, respectively, renders the temperature responses in different positions being of multi-scale setting-time and magnitudes. The exergy evaluation reveals that the water-wall suffers from the largest dynamic exergy destruction, approximately 8.2 and 8.5 times higher than the superheater and economizer, respectively. Economizer is the most sensitive component to the drum level control performance, whose dynamic exergy performance oscillates significantly. The proposed dynamic modelling and analysis method in this paper lays a solid foundation for the development of dynamic optimal control in power plants. [ABSTRACT FROM AUTHOR]

• Biomass oxygen fuel combustion is a potential technology for carbon neutrality. • Supercritical carbon dioxide integrated circulating fluidized bed combustor was modelled. • Excess oxygen ratio affected the energy penalty of compression and purification unit. • Waste paper resulted in highest efficiency of 35.76% • Excess impurities reduced carbon dioxide storage capacity and purification effect. Biomass have serve as a sustainable fuel source to mitigate environmental concerns in power generation. Developments in advanced coal combustion technologies have presented several promising solutions probable to be integrated with biomass combustion. Indirect supercritical carbon dioxide cycle incorporated with oxygen fuel circulating fluidized bed combustor was proposed to improve the power efficiency for domestic waste biomass resources, such as waste paper, waste wood, and cow manure. The thermodynamic analysis of the proposed cycle was analysed using Aspen Plus software within the excess oxygen ratio ranged between 0.97 and 1.05 and compared with coal fuelled supercritical carbon dioxide cycle. As excess oxygen ratio reached 1.01, with approximation of 27% of inlet oxygen concentrations, energy penalty by the compression and purification unit was minimized. The maximum net efficiency was 35.76% for waste paper, 27.74% for waste wood, and 31.12% for cow manure. The stored carbon dioxide at the same excess oxygen ratio for waste wood, waste paper and cow manure was 92.60%, 92.33% and 90.91% respectively. The proposed power cycle fuelled with waste paper resulted in a net efficiency slightly lower than coal fuelled power cycle. This work highlighted the potential of proposed biomass oxygen fuel circulating fluidized bed combustor integrated supercritical carbon dioxide cycle to serve as a future power technology for negative carbon dioxide emission. [ABSTRACT FROM AUTHOR]

• An inflatable structure is designed for Savonius wind turbine. • A double-layer fabrication process is proposed for the inflatable wind turbine. • Geometry parameters of the inflatable wind turbine are optimized based on CFD. • Static and dynamic performances are investigated through wind tunnel tests. • The inflatable wind turbine shows high portability and rapid deployment capability. Faced with the increasingly severe issue of the greenhouse effect, wind power emerges as a sustainable solution. However, the large size, heavy weight, and high risk associated with traditional wind turbines restrict their widespread deployment in urban, rural, and outdoor settings , wasting a vast amount of untapped wind energy resources. To address these challenges, this paper proposes an inflatable structure for the Savonius wind turbine and explores a double-layer fabrication process to manufacture the inflatable Savonius wind turbine (ISWT). 2D simulations are carried out on ANSYS-Fluent. Within predetermined parameter ranges, this paper successfully identifies the optimal geometric parameters for the ISWT model, with a blade thickness of 7 cm and a blade arc angle of 120°. This model exhibits the maximum power coefficient (C p) of 0.1912 at the tip speed ratio (λ) of 0.7. The manufactured ISWTs are fabricated based on the optimal geometric parameters. Due to deformation after inflation, the actual blade arc angle of the first ISWT sample is only 89.7°. Therefore, by adjusting the fabric template, an approximate blade arc angle of 120° is achieved for the second ISWT sample. Both ISWT samples are subjected to open-section wind tunnel tests. The results revealed that while the C p curves of Sample 1 and Sample 2 display trends similar to those in numerical results, the overall performance is lower. The reasons for the deviation include the simplification of vertical flow in 2D simulation and the lack of endplates. Specifically, Sample 2 also achieves the highest C p value of 0.1486 at λ = 0.7. Due to an inflation time within 60 s to the required pressure of 1.4 bar and a compressed volume lower than 0.021 m3, the ISWTs demonstrate rapid deployment capability during installation, portability during transportation, and storability during severe weather. [ABSTRACT FROM AUTHOR]

• Spatio-temporal correlation analysis is performed for different power supply characteristics. • A combination model of MI-DFS-K2-Bayes is proposed to solve the spatio-temporal problem. • The improved k -means algorithm improves the accuracy of multiple power center curves. • Matching of running scenarios to point predictions is solved by setting upper and lower bounds. This paper proposes a novel method for scenario generation and scenario forecasting considering wind-photovoltaic-hydro-thermal power sources. With the rapid development and application prospects of energy internet and grid modernization, accurate source-side multiple output modeling and forecasting is essential to observe and estimate the multiple curves. It is becoming more and more important to optimize the operation efficiency of power grid. The traditional methods mainly focus on multi-scene generation of a single power source. Grid scheduling requirements that could not take into account multiple time correlations and multiple scenario forecasting. The paper proposes a scenario forecasting method considering scenario generation. Firstly, mutual Information (MI) and depth-first traversal (DFS) are combined to analyze the factors associated with power generation and build the MI-DFS-K2-Bayes network to generate multiple scenarios of wind- photovoltaic-hydro-thermal power. Secondly, the improved k -means algorithm is proposed to obtain the center curve of each power source. The algorithm improves the accuracy of the multivariate clustering center curve. It solves the problem that the initial clustering center and the number of clusters are difficult to select, and builds the multivariate running state. Finally, the upper and lower interval of point forecasting constrained by confidence parameters is proposed to make the running state scene match the point forecasting. The future state curves of each power source in short time scale are obtained. The future state scenario is implemented. Numerical examples demonstrate that the proposed method reduces the modeling error of wind- photovoltaic-hydro-thermal power curves by 0.13%–0.4%. The overall forecasting accuracy is significantly better than the state of the study. [ABSTRACT FROM AUTHOR]

[Display omitted] • Biomass gasification to produce tunable syngas for methanol model was developed. • Overcame the challenge that biomass syngas cannot be directly utilized for methanol. • Effects of Steam/BBF, CaO/BBF and CO 2 /Biochar on the syngas were investigated. • Conducted exergy and global warming potential analyses of the system. The production of methanol through biomass gasification is a hot topic in current research. However, the challenge lies in obtaining the correct H 2 /CO ratio, as the syngas generated from biomass gasification cannot be directly utilized for methanol synthesis. This paper proposed a biomass sorption-enhanced gasification coupled with carbon utilization to produce tunable syngas for methanol synthesis model in Aspen Plus. The effects of Steam/BBF, CaO/BBF and CO 2 fraction on the composition and high heating value (HHV) of syngas were evaluated. This paper focused on the H 2 /CO ratio, the exergy efficiency and the global warming potential (GW). The study found that with the CO 2 fraction of 0.6, the H 2 /CO ratio in the syngas approximated 2, with a yield of 257.19 kmol/h, making it suitable for methanol synthesis. The exergy efficiency of the system was ∼ 64 %, with the sorption enhanced water gas shift unit, gasification unit, power generation unit and methanol synthesis unit being the primary sources of exergy loss. Furthermore, in the global warming potential analysis, BBF gasification for methanol production stage and the biomass processing stage accounted for more than 97 % of the total GW. Improving the gasification for methanol production unit was crucial for enhancing the overall sustainability of the system. This study provides valuable insights into biomass sorption-enhanced H 2 production and biomass-to-methanol conversion. [ABSTRACT FROM AUTHOR]

Changes in wind speed directly affect the output of wind turbines, so in power system planning, accurate prediction of future wind speed can help adjust the stability and reliability of power networks. In order to solve the problem that unknown wind speed prediction systems are unable to select features autonomously and to alleviate the insufficient prediction accuracy of single interval type 2 fuzzy models, this paper proposes a new deep convolutional interval type 2 fuzzy system (DCIT2FS) based on adaptive feature selection. First off, type 2 fuzzy sets are employed in the construction of two stage interval type 2 fuzzy curves and surfaces to address the issue of dimensionality explosion brought on by complex system modelling. By removing inaccurate and redundant information, this strategy achieves automated screening of key input aspects of an unknown system. Second, the model's interpretability is improved by the addition of the interval type 2 fuzzy system to the deep convolutional structure, which also addresses the issue that a single interval type 2 fuzzy model cannot achieve the required level of prediction accuracy. Thirdly, the incorporation of the feature pyramid structure boosts the mining of underlying data to increase the model's capacity to predict outcomes accurately while simultaneously strengthening its resistance to interference. Finally, model prediction performance tests are completed using meteorological feature data for both time periods, and generalisability tests are conducted using the benchmark dataset. The experimental results show that the prediction accuracy of the model proposed in this paper is improved by at least 7.70% and 1.23% in two wind speed prediction experiments compared to other models. • A new deep convolutional interval type 2 fuzzy prediction model is designed. • The feature pyramid structure is added to DCIT2FS in an innovative way. • A method TSIT2FCS is designed to realise the automatic selection of input features. • The hybrid model TSIT2FCS-DCIT2FS is successfully applied in wind speed prediction. [ABSTRACT FROM AUTHOR]

• Proposed a novel advanced solar-driven combined heat and power system. • Constructed the overall heat current model and exergy analysis expression. • Analyzed the exergy loss and efficiencies of each component and the system. • Analyzed the influences of various parameters on the system exergy efficiency. Conducting research on advanced cycle of distributed energy system and improving energy utilization efficiency is an important approach to promote the development of distributed energy systems. The paper proposed a novel solar-driven supercritical carbon dioxide-heat pump cogeneration system based on solar power tower system and performed the overall modeling of the system using the heat current method. The overall exergy loss calculation model of the system was established by applying the exergy analysis method incorporating the standard thermal resistance-based entropy generation rate expression. The calculation results present that under rated condition, irreversible loss mainly occurs in the solar energy conversion part, accounting for 73.83 %, and the system exergy efficiency is 34.69 %. Besides, the paper investigated the steady state performance of the system under different working conditions and the influence of the turbine inlet temperature and the intermediate pressure on the system performance. When the direct normal irradiance increases, the proportion of exergy loss in solar energy conversion part increases by 62.13 %, while the change of system exergy efficiency depends on the operating state of the system. The optimum intermediate pressure is 11.72 kPa, when the net power output and the exergy efficiency of the whole system reaches the maximum. Finally, the proposed system contributes to the improvement of cascade utilization of energy, and the modeling method is effective for solar-driven supercritical carbon dioxide cogeneration systems. [ABSTRACT FROM AUTHOR]

• Hemicelluloses-rich aqueous byproducts from WTCPs are often disposed of as waste. • Valorization of hemicelluloses-derived products into fuels, chemicals, and bioproducts. • Circular bioeconomy and use of all biomass processing byproducts from WTCPs. • Challenges to integrate and scale up aqueous byproduct processing in biorefineries. Thermochemical pretreatments are employed prior to energy, chemicals, and fuels production from biomass. Wet thermochemical processes (WTCP) are treatments used to modify biomass properties in water as the primary solvent, with or without added reactants/catalysts. WTCP includes hot water extraction, steam explosion, hydrothermal liquefaction, hydrothermal carbonization (HTC), and supercritical water gasification. WTCP also includes processes that add chemicals to reduce reaction time and improve efficiency, i.e., organosolv, alkali, and low acid pretreatment. Operational parameters in WTCP are usually selected to optimize the yields of sugars after enzymatic hydrolysis of the resulting solids and biogas from the pretreated solids, or to ensure that hydrochar (e.g., from HTC) performs adequately in environmental applications. However, a key byproduct from WTCPs is an aqueous fraction (rich in nutrients, hemicellulose-derived sugars, and chemicals) often disposed of as waste. The necessity of resource conservation and proper management and the need to make WTCP-based biorefineries economically and environmentally sound require using all the byproducts of biomass processing. Options for downstream conversion of the WTCPs' aqueous byproducts are dispersed in the literature. Thus, this paper aims to put together works that report the parameters of WTCPs that allowed removing hemicellulose-derived fractions and nutrients from biomass (either partially or almost entirely), the yields and properties of this aqueous byproduct, methods of characterization, current and expected uses, and the challenges for scaling up WTCPs and using the aqueous stream. The paper focuses on expected and existing methods that allow the valorization of the aqueous fraction and reduce wastes within a circular bioeconomy framework. [ABSTRACT FROM AUTHOR]

• The thermal, rheological, and optical properties of ferrofluids and how they change with magnetic fields were discussed. • The utilization of ferrofluids in solar energy systems was detailed in a state-of-the-art analysis. • The recommendations aimed to optimize the use of ferrofluids and magnetic fields in energy systems to enhance performance. Solar energy technologies play a crucial role in the transition to sustainable energy sources; however, there is an ongoing challenge in optimizing their efficiency and performance. This review paper thoroughly exposes the potential for enhancing solar systems by incorporating ferrofluids and utilizing magnetic fields. It provides a comprehensive examination of the rheological, thermal, and optical properties of ferrofluids, as well as their behavior when exposed to magnetic fields. The paper emphasizes the ability of ferrofluids to improve heat transfer efficiency, adapt to changing conditions, and enable precise control in the conversion of solar energy. Furthermore, the review addresses the obstacles and limitations associated with integrating ferrofluids into solar technologies, proposing potential solutions and outlining future research directions. [ABSTRACT FROM AUTHOR]

In their quest to enhance energy efficiency and carbon footprint management, many enterprises are turning their attention towards optimizing their facilities through amplified data monitoring and innovative control methods. In this context, this research highlights a practical solution in a commercial building located in the United States. It explains the creation, implementation, and costs of a universally applicable model predictive control (MPC) framework for the building's heating, ventilation, and air conditioning (HVAC) system. The paper elaborates on both the hardware and software used to accumulate pertinent data and the formulation of the MPC system. This approach leverages cloud-based microservices and can be seamlessly integrated into current building management systems. In this regard, this paper presents three innovative strategies: Proportional–integral (PI)+Preheating, MPC, and occupancy-based control. These scenarios were designed to improve energy efficiency and thermal comfort significantly by reducing temperature fluctuations and adhering more closely to the setpoint temperature. The implementation of these strategies resulted in substantial energy savings, with reductions in energy consumption of 12.83%, 19.21%, and 14.98%, respectively. • A novel cloud-based MPC scheme is proposed for controlling the educational building HVAC system. • Real-world case installation details are provided with a focus on cost and sensor information. • A comprehensive discussion on thermal modeling, occupants' comfort, and control performance. [ABSTRACT FROM AUTHOR]

Medium and long-duration energy storage systems are expected to play a critical role in the transition towards electrical grids powered by renewable energy sources. ACAES is a promising solution, capable of handling power and energy ratings over hundreds of MW and MWh, respectively. One challenge with ACAES is achieving the required highly efficient operation in the compressor over the range of conditions encountered in the system as the pressure in the air store changes. In this paper, an application-oriented axial-flow compressor is designed, aiming towards efficient operation throughout the operation range, whilst also associating the performance prediction to a practical compressor geometry. A two-step design methodology based on inviscid, axisymmetric flow conditions has been implemented, leading to the flowtrack, blade-row geometries and the compressor performance map. The compressor model is integrated into an ACAES model, including two compression spools, two expansion stages with preheat, a constant volume high pressure storage operating between 5.5 and 7.7 MPa and two separate Thermal Energy Storage units. While the existing ACAES literature either ignores the transient off-design operation or uses generic numerical correlations (which are not associated to a particular geometry), the key novelty of this paper is the application of a detailed design method for turbomachinery to ACAES. The results indicate that the designed compressor requires 33 stages over the two spools, and is able to operate efficiently over the storage pressure range, showing that if the application-oriented design procedure is applied to the compressor, it does not stop ACAES reaching 70% round-trip efficiency, outputting 35MW for approximately 15 h. Importantly, the specific ACAES requirement of conserving heat at higher temperatures has been fulfilled by decreasing the number of intercoolers. Finally, it is recommended that a similar level of scrutiny is applied to the other components (i.e. expanders, heat exchangers and TES units), keeping in mind the unique set of operational requirements of ACAES. This work is an important step towards removing the common misconception that off-the-shelf components can be easily be used in typical ACAES designs. • ACAES imposes unique conditions on its components, aiming system reversibility. • The compressors must run efficiently and keep the airflow temperature high. • This paper develops an axial-flow compressor geometry and performance map for ACAES. • The compressor is integrated into an ACAES model, operating within 5.5 and 7.7 MPa. • The ACAES system results indicate the system reaches 70% RTE after stabilisation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Assessed concepts combine biogas- and electricity-based methanol production • Adding electricity-based hydrogen increases methanol production by 28 to 67% • Tri-reforming enables high biogas conversion for a total carbon utilization of 97% • Bi-reforming exceeds energy efficiency of tri-reforming by 5%pt. in overall concept • Methanol production costs are estimated at 1,300 € 2022 /t The limited potential of sustainably available biomass requires efficient conversion to defossilize future demands of carbon-based chemicals and energy carriers. Therefore, integrating electricity-derived hydrogen into biomass-based production concepts appears promising, maximizing carbon utilization while minimizing biomass requirement. However, specific process concepts and analyses are still lacking to quantify the potential technical and economic benefits of such hybrid production processes. Thus, this research paper investigates this novel approach for decentralized methanol production from biogas within a techno-economic analysis, considering two production configurations. One configuration (BiRef) utilizes electrically heated bi-reforming for syngas generation, while the other configuration (TriRef) uses autothermal tri-reforming. Based on stationary process simulations, in-depth knowledge about process behavior is gained, efficiencies and costs are determined, and influencing factors are assessed. Within the reference case, the BiRef configuration achieves a carbon efficiency of 93 %, while the TriRef configuration reaches 97 % due to its enhanced methane conversion. Energy efficiency is 5 %pt. higher within the BiRef configuration (74 %), primarily due to the lower hydrogen demand. Carbon and energy efficiency are crucially affected by reforming temperature and inert gas fraction in the syngas. The economic analysis shows methanol production costs of ca. 1,300 € 2022 /t for both configurations. Variations in economic parameters emphasize advantages for the TriRef configuration when low hydrogen costs (<6 € 2022 /kg) are achievable. The comparison with purely biogas-based methanol production shows that hydrogen addition increases production capacity by up to 67 %. Cost advantages result against purely electricity-based production, while cost parity is achieved with purely biogas-based production. This paper demonstrates the potential of hybrid methanol production for efficient biogas utilization and highlights decisive parameters influencing technical and economic efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sorting strategies based on source, physical and chemical properties were compared. • The gasification efficiency of sorted RMSW was 40.89% higher than that of unsorted. • The yield of syngas can be increased by 37.14% after waste sorting. • The emission of CO 2 can be reduced by 81 t·per year after waste sorting. • Elemental composition based sorting method benefited to efficient gasification. Gasification is a promising way to convert residual municipal solid waste (RMSW) to high-valued syngas. Waste sorting is helpful to alleviate the heterogeneity problem of waste on gasification. This paper aimed to search for an optimal sorting strategy and evaluate the influence of waste sorting on downstream gasification. A sorting strategy based on elemental composition was proposed and compared with common source and density based strategies. The results validated the enhancement of waste sorting on RMSW gasification, where the elemental composition based strategy showed optimal gasification. The yield of syngas, cold gas efficiency, the lower heating value of syngas and H 2 /CO were increased by 37.14 %, 38.95 %, 2.18 % and 8.81 %, respectively. It also showed a good effect on the improvement of air gasification compared with the literature, especially for H 2 /CO. This paper also discussed the economic and environmental potential of the elemental composition based sorting method. The waste sorting can help increase 29,250 RMB/year and reduce CO 2 emission by 81 t/year. This method has potential for industrial application. It is suggested that further fast elemental composition characterization technologies and intelligent sorting equipment can be developed. Limitations and future perspectives were discussed from gasification simulation models, more energy utilization technologies, the underlying logic of waste sorting and sustainability evaluation. It is hoped that this work can provide insightful fundamentals to their applications in RMSW sorting, thus benefiting resource recovery and circular economy. [ABSTRACT FROM AUTHOR]

The objective of this paper is to implement an automated system for the control of all energy resources and devices within smart buildings. The paper develops a Two-Layer Electric Water Heater Management (TL-EWHM) system tailored for efficient power distribution within a smart microgrid connected to both a photovoltaic (PV) system and the Electric Grid (EG). The TL-EWHM consists of two distinct layers: the Offline Optimization Layer (OFF-OL) and the Online Optimization Layer (ON-OL). Within the OFF-OL, an optimization algorithm known as Particle Swarm Optimization (PSO) is employed to determine the optimal power settings for Electric Water Heaters (EWH) based on forecasts of several factors including PV generation, ambient temperature (A T), water demand (W D), and the consumption of fixed appliances (F A C) for the upcoming 24 h. These parameters are forecasted using a novel prediction algorithm referred to as regressor stacking, which is developed based on actual data. Within the ON-OL, real-time data is effectively utilized, and an Extremum-Seeking (ES) Controller is employed to continuously adapt the EWH power settings in response to uncertainties in the predictions. Furthermore, a strategic approach is being devised to generate the water temperature setpoints (W T S) by considering dynamic data factors like P V power, total energy consumption (P L), and the water demand profile to ensure that user comfort is maintained. A comprehensive comparative analysis is carried out to evaluate the effectiveness of our strategy approach. This strategy is characterized by the inclusion of a Water Temperature Setpoint Generator (W T S G) and the integration of a two-layer optimization methodology that combines the OFF-OL and the ON-OL. In this comparative study, our strategy is assessed in comparison to other conventional approaches, with the objective of highlighting the distinctive advantages of our method in terms of cost reduction and the enhancement of user comfort. On the one hand, comparisons are made with strategies that give priority to offline optimization. On the other hand, the strategy that maintains a constant water temperature setpoint throughout the day. The results of this paper establish the effectiveness of the proposed strategy. In particular, the energy cost savings associated with the two-layer optimization approach is 13.73%. Even more noteworthy is the significant reduction in energy costs, which reaches an impressive 18.63% when the variation of water temperature setpoints is taken into account. These results underscore the significant benefits of using a two-stage optimization strategy over relying solely on offline optimization. They also underscore the value of incorporating a WTSG as opposed to maintaining WTSC. • Real-time optimization of a electric water heater (EWH) under model uncertainties. • The two-layer management approach enhances robustness to operating conditions. • This paper proposes a new strategy for variable water temperature setpoints. • The objective is to minimize energy costs while maximizing occupant comfort. • MLP stacking reduces overfitting, boosts flexibility by diverse dataset training. [ABSTRACT FROM AUTHOR]

• This study reports a novel approach for hydrogen production and measurement of coated 3D-printed electrodes for hydrogen evolution reaction in alkaline water electrolysis. • The initial hydrogen rate is reported to be 2.48 × 10-9 kg/s and 2.37 × 10-9 kg/s respectively for nickel-copper non-conductive PLA-conductive nickel paint electrodes and nickel-copper-coated conductive PLA. • The approaches investigated provide the potential for optimizing the electrodes for electrolysis, offering a promising avenue for design improvements. This paper introduces a unique approach for hydrogen production and measurement of coated 3D-printed electrodes for hydrogen evolution reaction in alkaline water electrolysis. The method investigated in this study involve using non-conductive and conductive polylactic acids (PLAs) followed by various coating techniques to fabricate cathodes for alkaline water electrolysis. During the electrodeposition process, nickel and nickel alloys, including nickel-copper, nickel-iron and nickel-molybdenum, are investigated as coating materials. This paper also provides valuable data on hydrogen production and the respective cathode energy and exergy efficiencies. The study finds that the hydrogen production rate is the highest at the start and declines over time. The hydrogen rate for the first 15 min is reported to be 2.48 × 10-10 kg/s and 1.38 × 10-10 kg/s after 30 min for nickel-copper coated electrode where non-conductive PLA is used along with conductive paints. In comparison, the hydrogen rate for the electrode with nickel-copper coated directly on the conductive PLA is 2.37 × 10-10 kg/s for the first 15 min and 1.35 × 10-10 kg/s after 30 min. Interestingly, the coated conductive PLA electrodes are shown to be more efficient despite slightly lower hydrogen production rates. Moreover, the unique approaches employed in this paper are expected to provide a potential cost-effective approach for improving the performance of the electrodes for electrolysis which can lead to the development of more efficient hydrogen production for industrial applications. [ABSTRACT FROM AUTHOR]

• Constructed the cross-scale dynamic model by standardized thermal resistance method. • Proposed a thermo-electric coupling analysis method to describe the dynamic response characteristics. • Developed multi-scenario parameter influence analysis on the response characteristics. • Obtained a better response characteristic with the fuel inlet temperature and excess oxygen coefficient. Analyzing the dynamic characteristics of pairs of polymer electrolyte membrane fuel cell (PEMFC) is crucial for enhancing the efficiency and flexibility of the system in which it is utilized. In order to accurately reflect its dynamic process and investigate the interaction between the heat and electricity, this paper adopted the standardized thermal resistance method to build a dynamic model of PEMFC. On this basis, a simulation comparison with the experimental data is performed to verify the accuracy of the proposed model. Moreover, we propsoed a two-stage comprehensive response analysis method of the PEMFC under thermo-electric coupling with corresponding key parameters, such as the fuel inlet temperature, gas excess coefficient and load variation amplitude in multiple scenarios. The results show that the comprehensive response characteristics are better when fuel gas inlet temperature is 40℃ or excess oxygen coefficient is 2.4 in the corresponding scenarios. The model, analysis method and findings in this paper provide an effective reference for the development of optimal control strategies for the PEMFC stack temperature as well as other parameters to improve its comprehensive dynamic response performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proposed a low-carbon fuel ship power system configuration approach. • Ship demands from the perspective of water area, routes and ship types. • Constructing green low-carbon fuel ship power system from five dimensions. • Demand-configuration-integration-evaluation form a selection framework. The current global consensus to reduce greenhouse gas emissions has placed the maritime industry under increasing pressure to achieve carbon reduction and decarbonization. Low-carbon and zero-carbon power stand out as crucial means for ships to effectively cut emissions. However, implementing such power for ships is immensely intricate due to constraints like water conditions, routes, vessel types, demand, alternative fuels, and carbon reduction policies. Addressing these challenges, this paper establishes a high-level framework for low-carbon power systems in ships. Firstly, it focuses on low-carbon fuels like liquefied natural gas (LNG), liquefied petroleum gas (LPG), methanol, and biofuels, analyzing and summarizing the demands for low-carbon power in ships. Secondly, it offers a comprehensive overview of the configuration elements of low-carbon ship power systems across five dimensions: fuel, power module, propulsion method, aftertreatment module, and propulsion module. Based on this analysis, the paper proposes a configuration approach termed "demand-configuration-integration-evaluation" and presents six typical configurations for low-carbon ship power systems. Lastly, the paper outlines steps for evaluating low-carbon power systems. This framework and methodology cater to various water conditions (inland/offshore/offshore) and are adaptable to different vessel types (container ships, bulk carriers, cruise ships, and offshore engineering vessels). This systematic study offers crucial insights and references for ship designers and owners in the selection and design of new low-carbon power ships. [ABSTRACT FROM AUTHOR]

[Display omitted] • Explores catalysts and reactors in vital methanol production. • Covers methanol synthesis comprehensively. • Includes cutting-edge research on catalysts and reactors. • Offers valuable guidance for efficient methanol production. • Essential for industry professionals, revealing innovations. • Guides future research in an evolving industry. This review paper extensively examines the significance of methanol as a vital commodity chemical with broad applications in chemical synthesis and as a fuel source. The production of methanol heavily relies on the utilization of catalysts and industrial reactors. The primary focus of this paper is to provide a comprehensive analysis of various catalysts and reactor companies that play a crucial role in methanol production. The review delves into the synthesis of methanol, encompassing the feedstock used, reaction conditions, and the diverse catalysts and reactors employed in the process. Among the discussed reactor types and catalysts are prominent names such as Lurgi, Casale, Linde, Toyo, Mitsubishi, and Haldor Topsøe. The advantages and disadvantages of each catalyst and reactor technology are carefully evaluated, considering their performance, selectivity, stability, and cost. Furthermore, this study incorporates the most recent advancements in research and development endeavors geared towards enhancing methanol production. This includes innovations in catalyst and reactor design, as well as the exploration of alternative feedstocks. By thoroughly reviewing the current state of the field, the paper concludes by offering valuable recommendations for future research, aimed at addressing the key challenges faced by the methanol production industry. In essence, this paper is a valuable resource for researchers, engineers, and industry professionals actively engaged in methanol production. It sheds light on the latest developments in catalyst and reactor technology and their potential impact on the industry, making it a comprehensive and informative source of knowledge. [ABSTRACT FROM AUTHOR]