System Performance Parameters Research Articles

The Effect of Radiation Intensity on the Performance of Direct-Expansion Solar PVT Heat Pump Systems

The objective of this study was to investigate the impact of solar radiation intensity on the performance of direct-expansion solar PVT heat pump systems. To this end, an experimental setup was constructed for direct-expansion photovoltaic (PVT) solar heat pump water heating systems and photovoltaic (PV) power generation systems. The system performance and main parameters were analyzed and discussed under different solar radiation intensities. The winter experiments in southern China revealed that the exhaust temperature of the heat pump unit varied considerably under clear conditions, while the back temperature remained stable, fluctuating between approximately −13.5 °C and 24 °C. In contrast, the power generation of PVT panels increased with the increase in radiation intensity, from 78.33 W to 122.68 W, for an increase of 56.6%. Furthermore, the total electricity generation of the PVT panels was higher than that of PV panels, with an increase of 8.7–8.3%. Nevertheless, discrepancies between experimental and theoretical data were observed, particularly under overcast conditions, where the back panel temperature error was pronounced. Additionally, the system exhibited enhanced stability at elevated temperatures in comparable environments, accompanied by an improvement in the system’s coefficient of performance (COP) by 5.67%.

Impact of visibility limiting conditions on satellite and high-altitude platform quantum key distribution links

Satellite and aerial platforms are critical in the deployment of global quantum communications networks. Currently, there remain significant challenges including operation during daytime and robustness to visibility limiting conditions. In this work we investigate, through simulation, the impact of visibility limiting conditions on low-Earth orbit CubeSat dimensioned satellites, small satellites and high-altitude platform implementations. Three different operational wavelengths were considered: currently used near-infrared (at 850 nm); next-generation short-wave infrared (at 1550 nm); and a candidate longer wavelength (at 2133 nm). We present channel attenuation and consider quantum key distribution (QKD) system performance parameters. Results indicate that the “best wavelength” for an implementation depends on the minimum visibility rated and the single-photon detector technology utilized. In the cases where tolerated meteorological visibility is short, 1550 nm and 2133 nm wavelengths provide better performance. In cases when the visibility is long, the operational wavelength of 850 nm provides better QKD system performance.

Error analysis and calibration based on division-of-aperture bionic polarization navigation systems

Bionic polarization navigation technology has become an important navigation technology due to its non-dependence on satellite technology, and strong anti-jamming ability. However, in practical applications, the performance parameters of the structure of division-of-aperture polarization navigation systems limit the accuracy of polarization navigation. Therefore, this paper investigates the measurement error model and the corresponding calibration method for the multi-channel structure of division-of-aperture polarization navigation systems. In this paper, we first establish a mathematical model between the error of skylight polarization information and the performance parameters of navigation systems for the unique multi-channel structure of division-of-aperture polarization navigation systems. Secondly, for the first time, a mathematical model is used to quantitatively analyze and give the performance parameters suitable for the acquisition of skylight polarization information (polarizer installation errors ≤2°, grayscale non-uniformity ≤10(DN)). Then, a polarizer installation errors calibration algorithm based on Singular Value Decomposition (SVD) with linear fitting for grayscale non-uniformity response calibration algorithm is proposed and validated through indoor and outdoor calibration experiments. The experimental results show that the azimuth accuracy after calibration of polarizer installation errors can reach 0.382°, and the azimuth accuracy after calibration of grayscale non-uniformity response can reach 0.101°.

Hydrogen storage systems performance and design parameters using response surface methods and sensitivity analysis

DesignDesign of metal hydride-based hydrogen storage reactors is often performed using numerical/experimental modelling which is computationally/economically difficult. This paper investigates the applicability of Response Surface Methodology (RSM) coupled Local/Global Sensitivity Analysis (L/GSA) to investigate – i) the applicability of advanced RSMs in predicting the responses for storage systems efficiently, ii) the applicability of advanced RSMs to perform L/GSA to identify the sensitive input design parameters based on their effect on the Outputs of Interests (OIs), i.e., reaction fraction (i.e., C) and bed temperature (i.e., T), and iii) the dependence of importance ranking of design parameters on the employed L/GSA methodology. The study is conducted in two stages. In the first stage, the most accurate RSM was identified among fourteen traditional and advanced RSMs, i.e., radial basis, kriging, quadratic, moving least square, support vector machine etc., employing a measure of precision, i.e., Nash–Sutcliffe Efficiency (NSE). RSMs were constructed based on the values of OIs estimated using finite element simulation using COMSOL software for random realizations of inputs generated via Latin Hypercube Sampling (LHS). In the second stage, the importance ranking of design parameters was estimated for both OIs using six different L/GSAs based on the input-output relationships estimated in stage one. All the codes of RSMs and L/GSAs were written and validated in MATLAB. Finite element simulations of the random realizations were performed using COMSOL software. For the present study, NSEs of the considered RSMs were ranging between 0.6262-0.8544 and 0.4652–0.8081 for C and T respectively, indicating the importance of selection of appropriate RSM. RBF-augmented Compact-I and kriging were the most accurate RSMs with NSEs approximately 10%–20 % higher to those of frequently used polynomial RSM. Time (t) and mass of hydrogen to be stored (MH) were the most; and external temperature (Text) and porosity (E) were the least sensitive inputs corresponding to C and T, with differences of 80–90 % in the sensitivity indices respectively. The ranking prediction was highly dependent upon the employed L/GSA methodology, with Morris's screening observed to be the least accurate. The RSM methods described in this study help to design and investigate the metal hydride reactors for various applications (space heating, hydrogen storage, storage for vehicular application, metal hydride compressor) without undergoing detailed mathematical modelling of the system. The proposed methodology may significantly assist the designers to focus (or vary) on the sensitive inputs only during the physical modelling of systems to improve their performance. This sensitivity analysis is helpful to find out the most advance sensitivity analysis method which can be used to find out the most sensitivity parameter which can be varied according to their rankings to achieve the required performance of metal hydride reactor for the particular application. The advanced RSMs assist to identify these sensitive inputs quickly by reducing the mathematical efforts in the L/GSA by providing the accurate input-OIs relationships based on the limited numerical simulations. This will significantly save the resources and time of industries required in physical modelling/numerical simulations significantly, which otherwise would have been invested on investigating the non-sensitive inputs.

Forward osmosis membrane process: A review of temperature effects on system performance and membrane parameters from experimental studies

Forward osmosis (FO) offers a promising solution for concentration and material recovery, characterized by its low energy consumption and high separation efficiency. Temperature exerts a significant influence on FO, affecting permeation performance, membrane characteristics, and solution chemistry. The review article shows that increasing temperatures enhance forward permeate flux and solvent recovery by modifying mass transfer coefficients, membrane structure, and solution properties like osmotic pressure, diffusivity, and viscosity. This helps alleviate concentration polarization, a key challenge in FO applications. However, higher temperatures can exacerbate reverse solute flux, diminish solute rejection, and amplify membrane fouling, impacting operational efficiency and effluent quality. Studies involving thermoresponsive compounds or high-solute-content solutions yield conflicting results, further complicated by thermo-osmosis in scenarios with temperature gradients between solutions. In water and wastewater treatment, a huge quantity of solutions is treated, and temperature control is difficult. Managing solution temperatures through the utilization of waste hot streams or available heat sources can offer a viable strategy for enhancing system efficiency and mitigating the detrimental impacts of temperature fluctuations, while the solution volume should be effectively reduced before the treatment. A nuanced comprehension of temperature’s impacts is imperative for refining FO systems and addressing challenges across various industrial and environmental sectors.

Influence and optimal operating parameters of slit make-up air system on low-energy kitchen environment

Low-energy buildings make it difficult for the waste heat and pollutants in the kitchen to escape from indoors to outdoors due to their high air tightness and low air permeability. Therefore, a local make-up air system is needed to enhance the air change rate in the kitchen area. This study presents a design for a three-side slit make-up air system and assesses its impacts on the thermal comfort and pollutant concentrations of low-energy kitchens in winter. Orthogonal experiments were conducted to quantitatively evaluate the exposure levels of PM2.5 and TVOC in the breathing area and to determine the optimal parameters for system design and operation. The results indicated that the maximum temperature difference between head and ankles with slit make-up air was 17.1 °C, which was 1.6 °C lower than that under the natural make-up air. The maximum vertical temperature increased by 5.8 °C as the make-up air temperature increased to −5 °C. Furthermore, the average concentrations of PM2.5 and TVOC in the breathing area decreased by 62.4 % and 40.5 %, respectively, compared with those without the slit make-up air system. The optimal parameters for pollutant control are make-up air velocity of 5 m/s, exhaust rate of 700 m3/h, and slit angle of 90°. These experimental results indicated that the slit make-up air system could improve thermal comfort compared with natural make-up air systems and effectively reduce the concentration of kitchen pollutants in low-energy buildings in severely cold regions. This study provided fundamental information for further investigations on improving the kitchen environment of low-energy buildings.

Experimental assessment of modal properties of hybrid CFRP-timber panels

Hybrid timber composites are becoming increasingly widespread to efficiently enhance timber performance. While carbon fibre reinforcement has been explored for strength in timber structures, its impact on vibration performance remains understudied and is crucial as mass timber buildings extend their spans and heights. This work explores the effect of carbon fibre reinforcement on the vibration performance parameters of CLT floor systems. Natural frequency, mode shape, damping and stiffness parameters are evaluated from experimental testing using the Natural Excitation Technique (NExT) combined with the Eigensystem Realization Algorithm (ERA) and robust techniques for selection of physical dynamic properties, verified against numerical finite element models. The findings reveal that, in the case of three-ply Cross-laminated Timber (CLT) panels with depths ranging from 115 mm to 135 mm, introducing reinforcement at ratios below 0.67% led to an enhancement in frequencies, registering an increase of 6% to 11%, although not explicitly accounting for changes in environmental conditions. Moreover, these reinforced panels showed a relevant increase in effective flexural stiffness, ranging from 15% to 22%, when compared to their unreinforced counterparts. This means an improved maximum span of around 4%–6% within current design limits for timber floors influenced by vibration performance. These findings enhance the understanding and design of high-performance composite timber floors, promoting the use of renewable building materials in construction.

Performance analyses on the air cooling battery thermal management based on artificial neural networks

Air cooling thermal management technology is a lightweight and cost-effective approach for managing heat in power battery packs for electric ships. However, it suffers from significant drawbacks such as poor temperature control and excessive noise generation. To address these challenges, this study proposes a method that combines fluid dynamics and artificial neural networks (ANNs) to optimize the thermal management and aeroacoustic performance of the air cooling battery thermal management system (BTMS) for marine power batteries. Initially, a thermal-flow coupled model and an acoustic model for the BTMS were developed to investigate the impact of system structural parameters (battery spacing d, and main channel inclination angle θ) and operating parameter (system inlet velocity v) on the thermal management performance indicators (maximum temperature Tmax, and maximum temperature difference ΔTmax) as well as the aeroacoustic performance indicator (overall sound pressure level, OSPL). Subsequently, a relationship between the system structural and operating parameters and performance indicators was established using the 50-layer Residual Network (ResNet-50) model, enabling accurate and rapid prediction of the system thermal management and aeroacoustic performance. Furthermore, by combining ResNet-50 with the evaluation method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), this study successfully obtained the optimal system structure and operating parameters. The research indicates that keeping the remaining parameters constant, increasing the battery spacing results in higher maximum temperature and maximum temperature difference, while decreasing the overall system sound pressure level. Conversely, increasing the main channel inclination angle results in lower maximum temperature and maximum temperature difference, but higher overall system sound pressure level. In addition, increasing the inlet velocity will result in higher maximum temperature and maximum temperature difference, as well as higher overall system sound pressure level. The optimal case were found to be a main channel inclination angle θ = 3°, battery spacing d = 2 mm, and inlet velocity v = 10 m⋅s−1. Compared to the base case, the optimal case shows a maximum temperature reduction of 10.63 K, a maximum temperature difference reduction of 9.41 K, and an overall sound pressure level reduction of 4.6 dB. The prediction errors for these values are 0.08 %, 2.64 %, and 1.36 % respectively. This research demonstrates an effective and rapid approach based on fluid dynamics and ANNs in the design and optimization of BTMS.

Mathematical modeling of reverse osmosis system design and performance

ABSTRACT Reverse osmosis (RO) is one of the most effective technologies for water desalination. However, the RO system's performance is contingent on its design parameters and operating conditions. In this study, a computational model for RO desalination performance prediction was developed. The study compares the performance parameters of the RO system utilizing various types of membranes with the established model using a single pressure vessel and seven membrane elements within the pressure vessel. This study looked at two different feed water concentrations. The first is for saltwater with a concentration of 40,000 mg/L, while the second is for seawater with a concentration of 32,000 mg/L. WAVE software assessed the findings of the generated model to the recovery ratio, feed pressure, salt rejection, and permeate concentration of each membrane element inside the pressure vessel. The results of the study show good similarity between the simulation model results and the results obtained by WAVE software as they are illustrated in Figures 4–7.

Prediction Analysis of Fault Mode Sets for High Permeability Distributed Energy Distribution Networks Based on Multivariate Data

This technical abstract describes a prediction analysis methodology for fault mode sets in high-permeability distributed energy distribution networks (DEDNs). DEDNs are complex systems composed of multiple interconnected energy sources, storage units, and loads, which are managed and controlled by intelligent devices. These systems have become increasingly important in modern electricity networks due to their ability to integrate a high share of renewable and distributed energy resources. The proposed prediction analysis aims to identify and classify the various fault modes that can occur in high-permeability DEDNs based on multivariate data. It includes information about the system's operational parameters, such as voltage, current, and frequency, as well as data on weather conditions, load profiles, and the state of the network. The methodology involves collecting and pre-processing the data using suitable techniques, such as data filtering and noise removal.

Experimental studies on the impact of adsorbent particle size on the adsorption chiller performance

Adsorption chiller dynamics and its effect on the performance are greatly influenced by the adsorbent particle size because they govern both the micro (intra-particle) and macro (inter-particle) heat and mass transfer resistances within the adsorber bed. The net effect of adsorbent particle size and shape on the overall cooling system performance is addressed here. Initial CFD analysis of columnar adsorber bed with silica gel + water as the working pair, assuming uniform spherical adsorbent, showed increased uptake capacity with smaller sized (0.23 mm radius) particles over bigger sized (0.8 mm radius) ones despite smaller vapor penetration depth of the former. Subsequently, the effect of adsorbent particle size and shape on the overall cooling system performance is investigated experimentally in a single-stage one-bed mode for RD 2060 (0.8 mm radius) and RD 3070 (0.23 mm radius) silica gel specimens. Though the smaller size of RD 3070 is favourable for the adsorption kinetics at the particle level, its non-spherical shape and highly non-uniform size distribution resulted in significantly lower permeability and thermal diffusivity of the packed adsorber bed, thus hindering the cyclic steady state throughput. For the same operating conditions, RD 2060 and RD 3070 yield a cooling capacity (CC) of 107 W and 22 W, respectively. Further, the coefficient of performance (COP) drops by 73% in the case of RD 3070. The present study indicates that the adsorber bed design must consider both the adsorbent size and shape, in addition to other system operational parameters to enhance performance indicators.

Multivariate coupled full-case physical model of large chilled water systems and its application

Chilled water systems in large-scale central air conditioning consume more than 30 % of the total energy. To reduce this energy consumption, a model can be used to explore the optimal operating parameters of chilled water systems. The chilled water system is a multivariable highly coupled nonlinear system. The type and number of variables change with the hydraulic characteristics of the piping network and the operating data sparsity is high. For these reasons, data-driven methods are not suitable for modeling chilled water systems. Therefore, there is an urgent need to develop a model that is not constrained by the type and number of variables and can establish a complete data structure. According to the principles of differential pressure equilibrium, flow conservation, and thermal equilibrium, this study establishes a physical model of the hydraulic–thermal coupling of chilled water systems. The hydraulic–thermal characteristics of chilled water systems under multiple operating conditions were investigated, and the reliability of the model was verified through experiments. Furthermore, the difficulty of effective modeling owing to dynamic changes in the types of variables and lack of operating data were addressed. The study showed that the model has a wide range of applications, high reliability, and high computational efficiency.

Techno-exergy-economic assessment of humidification-dehumidification/reverse osmosis hybrid desalination system integrated with concentrated photovoltaic/thermal

Desalination is a process used to generate water for human consumption, irrigation, or industrial purposes. Assessment of desalination plants is crucial for freshwater productivity, energy consumption, exergy destruction, and economic feasibility calculations. Therefore, the study aims to conduct a technical, exergy, and economic analysis of a concentrated photovoltaic/thermal hybrid humidification-dehumidification reverse osmosis desalination system. The photovoltaic/thermal provides the electrical and thermal requirements for the hybrid desalination unit. Theoretical models for each unit are developed and integrated using the Engineering Equation Solver software. The sensitivity of system performance parameters was investigated under different climatic and operation factors. The analysis shows that the system produces 860 L per hour at the lowest specific energy consumption and water cost (3.3 kW-hours per cubic meter and 0.916 United States dollars per cubic meter), respectively, with a cost payback period of only 12 years compared to other green-powered desalination systems. The highest destruction portion of 84.6 % is at photovoltaic/thermal, while the largest cost portion of 68 % is at reverse osmosis. Productivity, energy consumption, and water cost are influenced by feed salinity, while destruction is most affected by solar irradiance. Ambient temperature, wind speed, and cooling fluid flow rate slightly affect the techno-exergy-economics of the system.

Research and application of bag filter system for railway ballast bed coal suction vehicles: An optimization and application study.

The current bag filter system used by railway ballast bed coal suction vehicles for cleaning coal dust from railway tunnels has low operational efficiency and generates significant volumes of dust. This paper describes a simulation test unit designed to enhance the dust removal performance in railway tunnels. The flow field inside the simulation test unit is investigated under different operating conditions through numerical simulations, and the variations in air volume and working resistance, total dust collection efficiency, and optimal operating parameters of a pulse cleaning system are identified through a series of experiments. The numerical results show that the pulse cleaning system does not significantly affect the uniformity of the flow field distribution at the bottom of the filter cartridge during the process of operation. The experimental research indicates that the simulation test unit satisfies the design requirements, achieving an average total dust removal efficiency of 99.93%. A field application shows that the total dust mass concentration at the operator position can be reduced from 335.8 mg∙m-3 to 4.2 mg∙m-3, effectively improving the operating environment within the tunnel.

Research of static and dynamic characteristics of a process system ‘electric drive-fluid-handling machine-pipeline’

<p>The paper offers the obtained quantitative assessment of the performance and energy parameters of a process system composed of an asynchronous motor, a fluid-handling machine and a pipeline when using two methods of performance control, in particular, throttling and speed control methods. Taking into account nonlinearity of mathematical representation of fluid-handling machines and asynchronous drive motors, the starting conditions were analysed using nonlinear differential calculus. The calculations for the models were performed using the MATLAB software package. Transient profiles of flow and head, stator current, angular frequency and torque of an asynchronous motor were obtained at pump startup and control of pump capacity. It has been found that the developed mathematical model of a process system composed of an asynchronous motor, a fluid-handling machine and a pipeline allows obtaining quantitative estimation of the performance and energy parameters of the unit when using two methods of the pump capacity control. The use of frequency method allows to decrease the pump rotation speed and significantly reduce the power consumed by the unit and provide energy-saving mode of operation, the economic efficiency of which depends on the range of feed control.</p>

Investigation on pulsed-electrocoagulation process for the treatment of wet coffee processing wastewater using an aluminum electrode

The use of conventional direct current-electrocoagulation in wastewater treatment is limited by its drawbacks, which include electrode passivation, high energy consumption, and significant sludge generation. Therefore, to address these issues, pulsed-electrocoagulation (PECP) has been developed. The PECP is an advanced wastewater treatment technique that uses intermittent electrical pulses to target and break down organic compounds in wastewater. It offers several benefits, including enhanced removal of organic compounds, reduced chemical consumption, energy efficiency, treatment of complex wastewater composition, pathogen inactivation, environmental compliance, and potential for water reuse. In this research, removal efficiency of % Chemical Oxygen Demand (COD), % Color, % Turbidity, % phosphate, and %nitrate was investigated for the wet coffee processing wastewater by using PECP and the obtained results as the COD-98.75%, color-99.92%, turbidity-99.00%, phosphate-99.02%, and nitrate-98.83%, respectively. Independent variables were the major significant factors and the optimum value was investigated and obtained at pH of 7, electrolyte dosage of 0.75 g L−1, electrolysis time of 45 min, and current of 0.45 Amp. As a result, PECP with NaCl and CaCl2 as an electrolyte is an effective treatment technique for pollutant removal from wastewater. As a consequence, the specific benefits may vary depending on the system design, operational parameters, and wastewater characteristics. The pilot-scale studies and optimization are essential for assessing PECP feasibility and performance.

Model of current threats to security of confiden-tial data in divisional information systems

The paper proposes a model for determining actual threats to the information security of distributed information systems, based on algorithms of fuzzy inference and the theory of fuzzy neural systems, unlike known ones, uses sufficient and necessary indicators, excludes expert errors, increases the detection of the number of actual threats to information security of distributed systems by 5 %, reduces the cost of purchasing information protection equipment from 15 to 30%. It takes into account the following factors: the IT infrastructure of the distributed information system, the capabilities of attackers and their level of motivation in the distributed information system, the list of existing protection tools in the distributed information system.
 The proposed approach differs from existing ones in the following: lack of involvement of highly qualified specialists in the field of information security; the process is automated, has a low computational complexity; absence of deficiencies in expert assessments; allows you to determine the list of current information security threats in information systems of various classes and types.
 The task of ensuring the security of confidential information becomes the most urgent, which is due to the growth of computer attacks and leaks of information, which are reflected in the statistical data on the commission of crimes in the field of high technologies, the growth of criminal activity using modern communication devices and the Internet.
 Existing methods of modeling current threats to information security and assessing the effectiveness of the information protection system cannot be used at all stages of the life cycle of distributed information systems - they do not take into account the following indicators in the complex: IT infrastructure of distributed information systems, current threats to information security, security requirements for confidential information, a list of means of protecting confidential information and their value as important indicators when solving these problems.
 In order to achieve the goals of ensuring the security of confidential information, it is necessary to: organize the effective creation of an information protection system (information security system), effective modeling (identification of the list) of current threats to information security, identification of the current violator, and also provide the opportunity to conduct a qualitative assessment of the effectiveness of the information security (protection) system.
 One of the most important tasks of ensuring the security of confidential information is the assessment of the effectiveness of the protection (security) system. In this regard, the goal of the work (research) is to improve the quality of the evaluation of the effectiveness of the protection (security) systems of distributed information systems by determining sufficient and necessary evaluation indicators using modern (promising) information technologies that allow the most effective solution of the following tasks: determination operating parameters of adaptive production fuzzy neural systems, which are most suitable for solving the tasks, application of Data Science technologies in data processing, fuzzy output algorithms.

Techno-economic and environmental assessments of optimal planning of waste-to-energy based CHP-DG considering load growth on a power distribution network

Load growth puts pressure on existing electric infrastructure and impacts on the system's performance parameters which may necessitate network expansion. Conventionally, electric network expansion is done by building new substations or reinforcing the existing ones with new transformers and upgrading the network feeders. However, optimal allocation of combined heat and power distributed generators (CHP-DGs) on distribution networks (DNs) can be adopted for network expansion planning problem. Optimal DG allocation is an optimisation problem which requires an efficient optimisation approach. In this paper, an improved particle swarm optimisation (IPSO) based on weighted randomised acceleration coefficient and adaptive inertia weight is proposed for optimal DG allocation problem. The considered CHP-DGs include internal combustion engine (ICE) and fuel cells (FCs) powered by biogas obtained from anaerobic digestion of food wastes. The proposed IPSO is tested on IEEE 69 bus radial distribution network under single and multi-objectives considering constant and mixed seasonal voltage-dependent load models. Some of the key findings show that integrating ICE-based CHP-DGs operating at optimal power factor in winter day mixed voltage dependent load in base year achieves 97.63 % active power loss reduction in comparison to 77.14 % loss reduction for unity power factor operating FC-based CHP-DG. Economic and environmental evaluation indicate that FC-based CHP-DG records a net present value of over 29.29 million $, levelised cost of energy of 0.0493 $/kWh and zero pollutant emission in comparison with 28.40 million $, 0.0501 $/kWh and 0.2817 million kg pollutant emission for ICE-based CHP-DG over the planning horizon. In comparison with the standard PSO, the proposed IPSO performs better in terms of solution quality, convergence speed and statistical results.

Design, Installation, and Performance Monitoring of a 105 kWp Rooftop Solar PV System

Rooftop Solar PV systems are gaining growing attention on the path toward carbon neutrality. Hence, a great effort must be exerted to ensure smooth and efficient penetration of such systems into the existing utility grids. In the current work, a 105 kWp rooftop solar system is designed and installed to fulfil part of the electric demand of the faculty of Engineering, Zagazig University, Egypt. The performance parameters of this grid-connected solar PV system are optimized for the least-cost of electricity supply through using industry-standard software NREL SAM. For the current rooftop system, fixed orientation of an optimized tilt angle of 23 degrees is preferred over sun-tracking systems due to the reduced operating and maintenance costs. The annual energy production of the system is 175,700 kWh with a capacity factor of 19.1%. Through using parametric optimization and inter-connected financial analysis algorithms, it was possible to define the least cost for the electricity supplied to the grid to be 0.55 EGP/kWh, which achieves grid parity in Egypt. The project is finically profitable without any subsidy, with a discounted payback period of 7.9 years, and IRR (on equity) of 20.1 % and saves 1882-ton CO2 over its lifetime. Sensitivity analysis showed that the electricity escalation rate greatly enhances the project finances. In the first year of operation, the system performed fairly well compared with the theoretical design, provided that the system is frequently cleaned (at least once a week) and continuously connected.

Coupling of high-temperature proton exchange membrane fuel cells with methanol steam reforming: Modeling and simulation for an integrated coupled for power generation system

This study established a zero-dimensional numerical model integrating methanol steam reforming (MSR) and high-temperature proton exchange membrane fuel cells (HT-PEMFC), systematically investigating the effects of parameters such as steam-methanol (S/C) ratio, reformer reaction temperature, methanol catalytic combustion ratio, fuel cell number, and anode stoichiometry on the thermal, mass, electrical, and efficiency performance parameters of the integrated system. The results confirmed that the integrated system can achieve thermal self-sustained operation without the need for additional heat from methanol catalytic combustion. Improved insulation quality enables the attainment of thermal self-sufficiency at lower operating conditions. The molar ratio of CO in the reformate increases with a decrease in the S/C ratio and an increase in the reformer reaction temperature. The system achieves maximum output power and efficiency when S/C equals 1.25 and the reformer temperature is 513 K, with increases of 8.6 % and 37.1 %, respectively. The system efficiency is highly sensitive to the anode stoichiometry of the fuel cell, showing an 11.7 % improvement as the stoichiometry decreases from 2.0 to 1.2. Based on these results, three improvement measures were proposed to enhance the performance of MSR and HT-PEMFC integrated systems: improving system insulation to lower thermal self-sufficiency conditions, optimizing the stoichiometry of the bipolar plates for significant efficiency improvement, and selecting appropriate operating parameters for system components to enhance overall performance. This study quantitatively demonstrates the potential of these measures to improve system performance, providing valuable insights for the design and optimization of integrated systems.