Reduce Energy Losses Research Articles

Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network.

The current study concentrates on the planning (sitting and sizing) of a renewable integrated energy system that incorporates power-to-hydrogen (P2H) and hydrogen-to-power (H2P) technologies within an active distribution network. This is expressed in the form of an optimization model, in which the objective function is to reduce the annual costs of construction and maintenance of integrated energy systems. The model takes into account the planning and operation model of wind, solar, and bio-waste resources, as well as hydrogen storage (a combination of P2H, H2P, and hydrogen tank), and the optimal power flow constraints of the distribution network. Electrical and hydrogen energy are administered in an integrated energy system. The modeling of the uncertainties regarding the quantity of load and renewable resources is achieved through stochastic optimization using the Unscented Transformation method. The novelties of the scheme include the sizing and placement of a combined hydrogen and power-based renewable integrated energy system, the consideration of the impacts of bio-waste units, P2H, and H2P systems on the planning of the integrated energy system and the operation of the active distribution network, and the modeling of uncertainties using the Unscented Transformation method to reduce the calculation time. The study's results demonstrate the scheme's ability to improve the technical conditions of the distribution network by considering the optimal planning of integrated energy systems. In comparison to the network power flow, the operation status of the network has been improved by approximately 23-45% through the optimal siting, sizing, and energy management of hydrogen storage equipment, as well as renewable resources in the form of integrated energy systems. In other words, optimal energy management and planning of the integrated energy systems in the distribution network has been able to reduce energy losses and voltage drop by 44.5% and 42.4% compared to the load flow studies. In this situation, peak load carrying capability has increased by about 23.7%. In addition, compared to the case of the network with renewable resources, the overvoltage has decreased by about 43.5%. Also, Unscented Transformation method has a lower calculation time than scenario-based stochastic optimization.

Fullerene-hybridized Fused-ring Electron Acceptor with High Dielectric Constant and Isotropic Charge Transport for Organic Solar Cells.

A novel isotropic fullerene-hybridized fused-ring electron acceptor, designated C60-Y, has been synthesized via a mild [4+2] Diels-Alder cycloaddition reaction with fullerene C60 to enhance the performance of organic solar cells (OSCs). Comparative analysis shows that C60-Y significantly outperforms the control acceptor Me-Y, with a notable increase in the relative dielectric constant from 2.79 to 3.95. This improvement enhances exciton dissociation and reduces non-radiative energy losses. Additionally, the isotropic molecular packing of C60-Y, similar to fullerene, facilitates efficient interface formation with donor polymers and improves charge mobility. As a result, incorporating C60-Y as an electron acceptor increases the power conversion efficiency (PCE) of binary OSCs to 15.02%, surpassing the 13.31% achieved with Me-Y. Moreover, when integrated into a ternary blend system, an impressive PCE of 19.22% is achieved, top-performing among reported ternary OSCs utilizing fullerene derivatives as the third component. These results suggest that fullerene-hybridized acceptors like C60-Y hold great potential for advancing high-efficiency OSCs by enhancing exciton dissociation, reducing energy losses, and improving charge mobility.

Mathematical Optimization of Electric Motor Designs

When designing and improving the performance of electric motors, mathematical optimization is very important. The main goals are usually to make the motors more efficient, lower their costs, and work within certain limits. The main topic of this study is how to improve electric motor designs using advanced optimization methods, such as multi-objective optimization. The study looks at how to use different types of computer algorithms together, like gradient-based methods, genetic algorithms, and particle swarm optimization, to solve difficult design problems. Some of these problems are reducing energy loss, making the best use of materials, and finding the right balance between different performance measures such as speed, power density, and temperature management. Building mathematical models of the motor's physical and functional features is the first step in this method. Then, optimization methods are applied to these models. Finite element analysis (FEA) is used to correctly model the motor's electric behavior. This makes sure that the optimization process considers physical limits and nonlinearities that happen in the real world. The study also looks into how different design factors, like the shape of the motor's core, the way the windings are set up, and the materials used, affect its total performance. The study also looks at the fact that motor design has more than one goal by using Pareto front analysis to find the best ways to balance different goals. This lets people come up with motor designs that are good for speed, efficiency, and cost-effectiveness. Case studies of the design of different kinds of electric motors, such as induction motors, permanent magnet synchronous motors (PMSMs), and brushless DC motors (BLDCs), show that the proposed optimization method works well. The results show that mathematical optimization has the ability to make the planning process a lot better. This could lead to motors that work better, cost less, and are better suited to certain uses. The study ends with a talk of how optimization methods could be used in the future to improve the design of electric motors, especially for new technologies like electric cars and green energy systems.

RuSiNPs@N,S-GQDs as self-enhanced anodic electrochemiluminescent immunobeacons for the highly sensitive quantitation of okadaic acid in shellfish.

Acompetitive electrochemiluminescence (ECL) immunosensor isproposed to accurately and rapidly assess okadaic acid (OA) levels in shellfish using a novel self-reinforced solid-state ECL marker, which is essential for ensuring seafood safety. Graphene quantum dots doped with nitrogen and sulfur (N,S-GQDs) were synthesized, for the first time, through the electrolysis of graphite in 3-(N-morpholine) propane sulfonic acid solution. Intriguingly, these N,S-GQDs exhibited exceptional co-reactant properties, significantly enhancing the anodic ECL performance of Ru(bpy)32+ in a phosphate-buffered saline solution. Following the functionalization of Ru(bpy)32+-doped silica nanoparticles (RuSiNPs) with poly(diallyldimethylammonium) chloride, we achieved a well-dispersed assembly of N,S-GQDs on the exterior of the RuSiNPs through electrostatic interactions. Importantly, the core-shell structure of RuSiNPs@N,S-GQDs efficiently encapsulated both the luminophore and co-reactant, thus improving the transfer rates of electrons, shorting interaction distances, and reducing energy loss during light emission. Leveraging this "bright" ECL beacon, theECL immunosensor demonstrated remarkable analytical performance, yielding a low half maximal inhibitory concentration (IC50) of 0.14ngmL-1, an extensive linear range spanning 0.003-40ngmL-1, and impressively low limit of detection of 0.001ngmL-1 for OA determination.

A new analytical technique for obtaining the optimal sizing, location, and scheduling of BESS in a grid-connected microgrid with multiple cases of heavy DG penetration

This paper aims to provide an optimal location, power, and energy rating for a battery energy storage system (BESS) in a grid-connected microgrid. The microgrid is pre-installed with heavy renewable distributed generations like solar and wind power plants. The paper suggests a straightforward optimal operating schedule for BESS, considering real-time data on solar irradiance, wind speed, load profile, and electricity tariff obtained from the US Energy Information Administration. The proposed method analytically identifies the optimal size and location of the storage system using the modified Q-PQV load flow technique. The method also proposes incorporating seasonal variations of the real-time data to obtain the optimal BESS size. A detailed cost-benefit analysis is exhibited to validate the economic feasibility. The methodological superiority is established by comparing the proposed algorithm with other soft computing techniques like PSO, GA, and JAYA algorithms. The novel technique is executed on 33-bus and 136-bus test systems with multiple cases of solar and wind-distributed generations. The proposed method provided a significant reduction in annual energy loss with a definite improvement in the voltage profile and overall profit of the system.

An improved energy saving clustering method for IWSN based on Gaussian mutation adaptive artificial fish swarm algorithm

The current industrial wireless sensor network (IWSN) cluster routing methods suffer from energy inefficiency. Designing efficient cluster-based routing protocols is crucial for improving network performance and energy efficiency. Therefore, this paper first designs a new clustering model to achieve efficient cluster head (CH) selection and data transmission performance by comprehensively considering multiple key factors such as CH energy, base station (BS) distance, packet loss rate, and data delay. Based on this clustering model, a novel cluster routing protocol based on Gaussian mutation adaptive artificial fish swarm algorithm (GAAFSA) is proposed. At the same time, a new Gaussian mutation strategy and an adaptive strategy were introduced to effectively promote the protocol to avoid local optima and prevent premature convergence. The GAAFSA based cluster routing protocol was experimentally compared with five popular schemes, namely CMSTR, D2CRP, EEHCHR, ESCVAD and BAFSA. The results showed that the proposed protocol outperformed the other four schemes in terms of network energy consumption, system lifetime, data transmission reliability, and latency. Specifically, GAAFSA has improved network lifespan by at least 15.68%, BS received packets by at least 7.46%, and reduced packet loss rate by at least 15.28%. Therefore, GAAFSA effectively optimizes network performance and extends network lifespan, greatly reducing energy loss within the network and significantly improving network quality of service (QoS).

Data-Driven Day-Ahead Dispatch Method for Grid-Tied Distributed Batteries Considering Conflict Between Service Interests

The rapid advancement of battery technology has drawn attention to the effective dispatch of distributed battery storage systems. Batteries offer significant benefits in flexible energy supply and grid support, but maximising their cost-effectiveness remains a challenge. A key issue is balancing conflicts between intentional network services, such as energy arbitrage to reduce the overall electricity costs, and unintentional services, like fault-induced unintentional islanding. This paper presents a novel dispatch methodology that addresses these conflicts by considering both energy arbitrage and unintentional islanding services. First, demand profiles are clustered to reduce uncertainty, and uncertainty sets for photovoltaic (PV) generation and demand are derived. The dispatch strategy is originally formulated as a robust optimal power flow problem, accounting for both economic benefits and risks from unresponsive islanding requests, alongside energy loss reduction to prevent a battery-induced artificial peak. Last, this paper updates the objective function for adapting possible long-run competition changes. The IEEE 33-bus system is utilised to validate the methodology. Case studies show that, by considering the reserve for possible islanding requests, a battery with limited capacity will start to discharge after a demand drop from the peak, leading to the profit dropping from USD 185/day (without reserving capacity) to USD 21/day. It also finds that low-resolution dynamic pricing would be more appropriate for accommodating battery systems. This finding offers valuable guidance for pricing strategies.

A comprehensive simultaneous allocation algorithm of charging stations and vehicle to grid operation in radial networks

The widespread adoption of electric vehicles (EVs) helps improve air quality by minimizing pollutants and promoting sustainable transportation practices. The integration of a substantial fleet of EVs leads to an increase in the installation of charging stations. The unplanned allocation of these loads impacts the distribution systems, such as increasing power loss. This paper introduces an algorithm that proposes an optimal allocation strategy for charging stations (CSs) in a distribution system. The allocation process aims to minimize the total apparent energy losses and ensure that the system voltage profile remains within limits. Load profile, charging and discharging profiles of CSs are considered. Vehicle-to-Grid (V2G) mode is one of the merits of integrating EVs in the grid, so this feature has been used to maintain system voltage stability and minimize energy loss. Power rating and locations of V2G mode are optimally determined to guarantee power quality indices. A hybrid algorithm of genetic algorithm (GA) and Self-Adaptive Multi-Population Elitist JAYA (SAMPE-JAYA) is developed to simultaneously allocate CSs and V2G in the systems. The proposed algorithm is verified on standard systems, IEEE 33, and 69-bus systems. The proposed algorithm is verified on standard IEEE 33-bus and 69-bus systems. V2G integration with CSs results in a reduction of energy losses by 6.33% and 22.25%, respectively, and voltage deviation improvements to 7.61% and 7.88% for the two systems.

Working Condition Sensitivity Analysis and Optimal Structure Parameter Determination of IVT Based on CFD and Orthogonal Experiment

To address liquid accumulation in horizontal gas wells, a specialized internal vortex tool (IVT) was developed for use in the horizontal sections, functioning as a drainage gas recovery device. This tool operates by leveraging centrifugal forces generated during fluid swirl to separate liquid from gas. The study examined the performance of IVT under various operational conditions and sought to identify optimal structural parameters. Through a controlled variable approach, the impact of inlet velocity and the water-gas volume ratio on pressure drop range, MGV (maximum gas velocity), and MVFLP (maximum liquid phase volume fraction) was analyzed. The results indicated that when the inlet velocity is between 2-4m/s and the water to gas volume ratio is between 0.5-2m3/104m3, the smaller the inlet velocity and the smaller the water to gas volume ratio, the better the gas-liquid separation effect of the IVT. An orthogonal test was subsequently employed to fine-tune the tool's structural parameters for different conditions, culminating in the creation of a comprehensive optimization chart for IVT. This study can effectively design drainage gas production tools for gas wells under different working conditions, reduce energy loss during drainage gas production, effectively utilize downhole resources, and achieve the goal of increasing natural gas well production and reducing costs.

Optimizing Nitrate Fertilizer Production Using Plasma-Activated Water (PAW) Technology: An Analysis of Dielectric Properties

This study investigates the potential of Plasma-Activated Water (PAW) technology for the production of nitrate fertilizer, focusing on the dielectric properties of plasma-treated water, such as the dielectric constant and dielectric loss factor. The research aims to elucidate the impact of plasma treatment and varying water flow rates on these properties. An experimental approach was employed wherein ion-free water was subjected to plasma treatment at different flow rates (0.5, 1.0, and 2.0 L/min) and durations (1, 2, and 3 h). The results reveal a marked enhancement in the dielectric properties of the water following plasma treatment, with the most significant improvements observed at a flow rate of 0.5 L per minute and a treatment duration of 3 h, and dielectric efficiencies of 97.82%, 97.21%, and 96.61% achieved at flow rates of 0.5, 1.0, and 2.0 L/min, respectively. These findings demonstrate that PAW technology enhances the efficiency of nitrate fertilizer production by optimizing energy storage and reducing energy losses. The study underscores the potential of PAW as a sustainable, environmentally benign alternative to conventional chemical fertilizers, contributing to more efficient and sustainable agricultural practices.

The output flexibility optimization control of load-side wind turbine considering client demand response

Abstract This study focuses on optimizing the output flexibility control of load-side wind turbines considering client demand response. Considering the potential and role of client demand response, a load-side wind turbine output objective function was constructed, client demand response constraints were designed, and a two-layer model for flexible optimization control of load-side wind turbine output was constructed. The top is the power allocation hierarchy, and the core objective of this layer is to achieve power optimization distribution of wind turbines under various constraint conditions. The lower layer is the frequency control layer, which optimizes and controls the dynamic frequency of load-side wind turbine output. The experimental results show that the optimized control strategy not only enhances the efficiency of wind turbines, but also effectively reduces energy loss and enhances the stability and reliability of the power grid. Through precise calculation and real-time adjustment of the double-layer model, we can more accurately predict and control the output of wind turbines, thereby ensuring the supply-demand balance of the power grid and reducing potential risks caused by frequency fluctuations and power offsets.

A molten salt energy storage integrated with combined heat and power system: scheme design and performance analysis

To investigate the flexibility and economic characteristics of a molten salt-combined heat and power (CHP) integrated system under different heat sources, this paper proposes a design scheme for a molten salt-CHP system based on flue gas heat storage, comparing it with main steam heat storage and reheated steam heat source schemes. First, a molten salt heat release sub-loop is designed, where the steam heated by the molten salt can either compensate for heating demands or enter the low-pressure turbine for work, meeting the flexible operation requirements of the unit. Secondly, in response to fluctuations in temperature and pressure parameters of the main steam and reheated steam in the flue gas heat storage scheme, a water-spray desuperheating device is arranged. Finally, a simulation experiment based on a 350 MW CHP was conducted, and the results show that the flue gas molten salt heat storage technology significantly reduces energy loss on the boiler side. Underrated load, compared to the main steam and reheated steam heat storage schemes, the flue gas heat storage scheme has the highest boiler exergy efficiency and total energy utilization efficiency, at 55.8% and 59.1% respectively. During the thermal storage process, the coal consumption index of the flue gas heat storage scheme decreases with increasing load, while conversely, during the heat release process, it increases with the load. The peak-shaving capacity increases with the load, reaching 78.4 MWh under the 75% THA condition. In the steam extraction heating scenario, coupling with the molten salt subsystem can expand the safe heating operation range of the original unit, increasing the maximum peak shaving range by 13.9%, and increasing the maximum heating capacity by 65.4%.

A Study on the Influence of Mobile Fans on the Smoke Spreading Characteristics of Tunnel Fires

Mobile fans, as flexible and convenient new longitudinal ventilation and smoke extraction equipment for tunnels, demonstrate more significant effectiveness in an emergency response to tunnel fires compared to traditional smoke extraction methods. This study employs computational fluid dynamics simulation methods, selecting two fire scenarios to investigate the effects of fan inclined angles and fan airflow volumes on the longitudinal temperature distribution and smoke back-layering length in tunnels. The results indicate that when using mobile fans for longitudinal ventilation in tunnels, at a lower fan airflow volume, the temperature distribution along the longitudinal axis is nearly symmetrical. The fire source and the fan installed in the upstream are within a certain range, and it is more effective to use the horizontal angle for longitudinal ventilation. As the fan airflow volume increases, the back-layering length significantly decreases (210,000 m3/h < V < 270,000 m3/h). However, as the fan flow volume continues to increase (270,000 m3/h < V < 300,000 m3/h), the reduction in the back-layering length becomes less pronounced, the smoke spread distance of the latter is only 11% of that of the former. Therefore, selecting appropriate fan airflow volumes and fan inclined angles them can effectively enhance the performance of tunnel smoke extraction systems. Moreover, by comparing with traditional fans, we find that mobile fans provide an alternative effective strategy during firefighting by allowing adjustments in distance from the fire source and fan inclination angles, enhancing fire suppression effectiveness while reducing energy losses. The research findings can serve as a reference for tunnel fire prevention design.

Accelerating T1 relaxation time measurements of noble gas using transverse low-frequency square-wave magnetic field modulation.

The longitudinal relaxation time (T1) of noble gas nuclear spins is a critical parameter for evaluating the performance of an atomic comagnetometer, significantly influencing the signal-to-noise ratio of the system. Traditional measurement techniques, such as the free induction decay method combined with the spin growth technique (FIDSG), are time-consuming for gases with extended T1 durations, such as 21Ne, and are prone to substantial environmental variability. Here, we propose the transverse low-frequency square-wave magnetic field modulation (LSMM) method for the rapid measurement of T1. The experiment indicates that the LSMM significantly condenses the measurement time to 19.2% of the original, thereby diminishing the robustness demands of the system. Although a minor discrepancy of up to 3 min (or 1.3%) exists between LSMM and FIDSG results, the LSMM method provides strong support for calibrating the performance of comagnetometer cells and conducting various nuclear spin polarization experiments, thereby improving efficiency and reducing energy loss.

Designing a Highly Crystalline Polymer Donor with Alkylsilyl and Fluorine Substitution to Achieve Efficient Ternary Organic Solar Cells.

Adopting a ternary strategy is an effective approach to enhance the power conversion efficiency (PCE) in organic solar cells (OSCs). Previous research on highly efficient ternary systems has predominantly focused on those based on highly crystalline dual small molecule acceptors. However, limited attention has been given to ternary systems utilizing dual polymer donors. Herein, by incorporating the fluorine and alkylsilyl substitution, a new polymer donor named PX1 is developed, which demonstrates strong crystallinity and excellent miscibility with polymer PM6. Moreover, PX1 broadens and enhances the absorption properties of the PM6:L8-BO blends, and its molecular orbital energy level is situated between those of PM6 and L8-BO, highlighting its suitability as a third component. Introducing 20% PX1 into the PM6:L8-BO system resulted in a high PCE of 18.82%. PX1 effectively suppresses charge recombination and reduces energy losses, while also serving as a morphology modulator that enhances the crystallization and improves the molecular packing order of the active layer by shortening the π-π stacking distance and extending crystalline coherence length. These factors collectively contribute to the performance improvements in ternary devices. This study demonstrates that employing a dual polymer donor strategy is a promising approach for achieving high-performance ternary OSCs.

Enhanced energy storage performance in NBT-based MLCCs via cooperative optimization of polarization and grain alignment

Dielectric ceramics possess a unique competitive advantage in electronic systems due to their high-power density and excellent reliability. Na1/2Bi1/2TiO3-based ceramics, one type of extensively studied energy storage dielectric, however, often experience A-site element volatilization and Ti4+ reduction during high-temperature sintering. These issues may result in increased energy loss, reduced polarization and low dielectric breakdown electric field, ultimately making it challenging to achieve both high energy storage density and efficiency. To address these issues, we introduce a synergistic optimization strategy that combine polarization engineering and grain alignment engineering. First principles calculations and experimental analyses show that the doping of Mn2+ can suppress the reduction of Ti4+ in Na1/2Bi1/2TiO3-based ceramics and enhance ion off-centering displacements, thereby reducing energy loss and improving polarization. In addition, we prepared multilayer ceramic capacitors with grains oriented along the <111> direction using the template grain growth method. This approach effectively reduces electric-field-induced strain by 37% and markedly enhances breakdown electric field by 42% when compared with nontextured counterpart. As a result of this comprehensive strategy, <111 >-textured Na1/2Bi1/2TiO3-based multilayer ceramic capacitors achieve an ultra-high energy density of 15.7 J·cm−3 and an excellent efficiency beyond 95% at 850 kV·cm−1, exhibiting a superior overall energy storage performance.

Aspect ratio optimization of piezoelectric extensional mode resonators for quality factor and phase noise performance enhancement

Abstract This study focuses on optimizing the resonator geometry via the aspect ratio design of a width-extensional mode resonator to improve its quality factor (Q), which is one of the critical performance parameters for resonators in either sensing (Allan deviation) or frequency reference (phase noise) applications. The proposed approach uses finite element analysis to reduce the strain energy at anchor supports by altering the resonator geometric structure, thereby reducing energy loss through anchors. Moreover, process limitations on feature sizes are used as constraints to find aspect ratios that can not only increase the Q but also reduce spurious modes near the targeted frequency. The devices were fabricated using AlN thin film piezoelectric on a substrate (TPoS) process. The simulated energy dissipation trends for specific length-to-width (L/W) ratios closely match the measured changes in the resonator Q values in vacuum. In vacuum, the highest Q-factor achieved by the device is close to 8816, with a motional resistance of a few tens of ohms. Additionally, a board-level oscillator realized using a commercial low-noise amplifier exhibits phase noise performance of −141.21 dBc Hz−1 and −164.25 dBc Hz−1 at 1 kHz and 1 MHz frequency offsets, respectively. The calculated figures of merit for these offsets are 204 and 168, respectively.

Power Factor Optimization with Cos Phi Mode Trainee

The power factor cos phi measures the efficiency of using electrical power in a system. A low power factor indicates the presence of high reactive power consumption, which can lead to increased energy losses and operational costs. To overcome this problem, an effective power factor regulation system is required. This research designed and developed the Cos Phi Trainer, which operates in two modes, manual and automatic, to improve the power factor at an electrical load. The system is designed to give users a practical understanding of measuring and improving power factors by setting up compensation capacitors. In manual mode, the user directly sets the value of the capacitor used to fix the power factor. While in automatic mode, the system uses current and voltage sensors to measure the power factor value in real-time and automatically adjusts the capacitor to achieve the optimal power factor. The trainer has an easy-to-use interface and a measurement panel that displays important parameters such as current, voltage, active power, reactive power, and power factor. The test results show that the system can significantly increase the power factor in manual and automatic modes. Thus, this Cos Phi Trainer is an effective tool for training in the laboratory of Indorama Engineering Polytechnic and teaching about electrical power management and energy loss reduction in the electrical system. Keywords: Power factor, manual, active power, reactive power, trainer

Impact of magnetic field variation on thermally annealed tantalum-filled vertical superconducting interconnects for scalable quantum computing systems

Efforts to scale down advanced quantum processors with more numbers of qubits offer challenges since the integration of qubits is a significant obstacle in the path. Superconducting vertical interconnects in 3D IC integration can provide a crucial solution for wiring complexities, as shorter interconnections reduce energy loss when working in cryogenic conditions with better signal fidelity. Using the time-dependent Ginzburg–Landau equation, this simulation study analyzes vertical superconducting interconnects filled with materials like tantalum, niobium, and thermally annealed tantalum. It also investigates how London penetration depth (temperature-dependent) and magnetic fields affect Cooper pair density and, consequently, current density.

An inclined magnetic field and slip effect on heat and mass transfer analysis in the peristaltic flow of immiscible fluid through an asymmetric porous channel

In this work, authors have studied peristaltic flow of immiscible type of couple stress and Newtonian fluid via an asymmetric horizontal channel filled with porous material by taking slippage into account at the channel wall which was ignored in previous published literature under the influence of thermal radiation and magnetic field. The study of peristaltic flow of considered immiscible fluids will play an important role in maximizing system efficiency, reducing energy losses, and improving performance of various fluid transport. In the present problem, the linearized form of governing equations has been solved by direct method with the use of Mathematica 14 software to obtained the closed form solutions of various flow variables. In this work, the impacts of various influencing factors on the model's flow, thermal, and concentration properties have been analyzed graphically. The work presented here leads to the significant result that large Schmidt number values in a porous filled duct reduces the mass diffusivity. Another key finding of this work is that the formation of entropy is reduced when low permeability porous material is used. Our research concludes that entropy creation in the asymmetric porous channel is decreased when the slip length increases on the channel's static borders.