Stationary Power Generation Research Articles

Theoretical analysis of organic Rankine cycle for maximum power generation in optimization operation conditions

The global critical issue in energy scarcity should be appropriately solved to realize a sustainable society. Effective use of Rankine cycle is one possible way since it provides most of worldwide electricity production. In this paper, theoretical analysis model of organic working fluids R717, R134a, R1234yf, R290, R245fa and R1233zd in Rankine cycle for maximum power generation in optimization operation using low-temperature heat sources are proposed and studied for development next generation green and zero-carbon energy generation system to promote the race to zero. Results show that temperatures of warm and cold water at inlet, mass flow rate of the warm water and performance of the evaporator play a key role to obtain the theoretical optimization operation conditions for maximum power generation. In the case of same initial conditions of temperatures of warm water (85 Celsius degree) and cold water (15 Celsius degree) at inlet, mass flow rate of the warm water (10kg/s) and performance of the evaporator (100kW/K), R717 has the best performance in terms of the maximum power output 56.0kW with thermal efficiency of 8.6%, and the next is the R1233zd (54.4kW, 8.3%), R245fa (54.0kW, 8.2%), R134a (52.8kW, 7.9%), R290 (52.7kW, 7.9%), and R1234yf (51.7kW, 7.7%). Here, it should be noticed that other optimization conditions are almost the same (mass flow rate of the cold water 9.1∼9.2kg/s; performance of the condenser 91∼92kW/K) to get their maximum power output of ORC. In addition, it also known that low-GWP R1233zd (GWP: 1) can deserve the best option to replace R245fa (GWP: 950) and R1234yf (GWP: 4) also can replace r134a (GWP: 1430) since their optimization operation conditions are almost same.

Reversible solid oxide cells-based hydrogen energy storage system for renewable solar power plants

The power-H2-power system based on reversible solid oxide cell is a promising pathway for large-scale renewable energy storage but not well understood due to the absence of comprehensive system analyses. In this study, a reversible solid oxide cell-based H2 energy storage system for a 100 % renewable solar power plant is proposed and analyzed through detailed modeling approach and optimization framework. The detailed parametric analyses and economic evaluations are performed in electrolysis (12:00 pm, sufficient solar energy) and power generation (6:30 am, insufficient solar energy) conditions. Notably, it is found that larger stack capacity (Ncell) and higher operating temperature (TReSOC) of the cell enhances system net H2 production and system economics despite additional investment cost. Afterwards, the optimal system performance is obtained (VH2,produce = 498.40 Nm3·h−1, Z=263.59 $·h−1 for electrolysis, and VH2,consume = 380.33 Nm3·h−1 for power generation) through multi-objective optimization by fully considering cell internal operating characteristics and system energy-exergy-economic factors. Besides, it is also found that the performance of power-H2-power system is still limited by remarkable fuel (H2) costs for nighttime power generation (daytime H2 production is smaller than nighttime H2 consumption when Wtot = 1 MW). Therefore, the critical power capacity (Pcritical) is obtained, offering a convenient approach to determine the maximum output capacity (Pcritical = 880 kW) to make the power-H2-power system profitable at specific solar energy input. This study provides valuable insights between system capacity, economics, and cell operating features in solar power plants, which are useful for the design and optimization of practical power-H2-power systems for renewable energy storage.

Transient synchronization stability of a weak‐grid connected VSC considering the interaction of outer control loops and PLL dynamics

AbstractSince these large‐scale renewable power generation (RPGs) stations are always located far away from load centres, voltage source converters (VSCs) always operate in weak‐grid connected conditions, due to the long distance of transmission line and increasing capacity of RPGs. Large power disturbance of RPGs easily causes weak‐grid connected VSCs (WG‐VSCs) suffering from transient synchronization instability issue, which is lack of theoretical and quantitative analysis. This paper is motivated to fill this gap. By considering the dynamic interaction of outer DC voltage control, reactive power loop, and phase‐locked loop (PLL), an equivalent synchronization model of a WG‐VSC system is established first. Then, the mechanism of transient synchronization instability is revealed by the combination of equal area criterion and numerical integration method. Furthermore, the concept of feasible region of active power disturbance (FR‐APD) is introduced for the first time. With the constructed FR‐APD, the transient stability of the WG‐VSC system can be confirmed. Finally, experimental results based on the RT‐BOX hardware‐in‐the‐loop platform are presented to verify the theoretical analysis.

Highly robust and porous cathode current collecting layer for flat-tubular solid oxide fuel cell stack applications

Solid oxide fuel cells (SOFCs) have gained great attention as a stationary power generation application due to their high efficiency, fuel flexibility and environmental friendliness. The devices and power age could be revolutionized with the commercialization of these technologies. The SOFC-based stationary power generator is one step closer to commercialization however, it is delayed due to the inherent bottleneck of insufficient long-term durability. The cathode current collecting layer (CCCL) is crucial in stack applications to minimize the contact loss between cell and metallic interconnects. Herein, we report an easy-to-fabricate and highly robust CCCL to boost electrochemical performance and long-term durability of flat tubular (FT) short stack. The tailored structure of the CCCL was employed in the fabrication of the FT short-stack. The G/Ag porous structure exhibited increased porosity of 61.2 %, thereby enhancing the mass transport and improving the overall performance and long-term durability. The four-cell FT stack was manufactured without an interconnect and open air-gas channel. Subsequently, the FT short-stack is tested for performance and long-term durability for elapsed 5000 h at a chronopotentiometry test. The porous layer of graphite/Ag on the cathode layer maintained structural integrity without defects and mechanical failure. Consequently, the stack voltage remains stable throughout operation owing to improved structural stability and uniform temperature distribution across four FT cell stack.

Advanced Nafion/nanofiller composite proton exchange membranes for fuel cell applications

Proton exchange membrane fuel cells (PEMFCs) exhibit increasing potential in a variety of applications, from automotive to stationary power generation, due to their superior advantages such as high efficiency, quick start-up and low emissions. The cell performance and operation life of PEMFCs are directly affected by the proton exchange membranes (PEMs). Nafion, a well-known perfluorosulfonic acid polymer, represents the state of the art of PEMs. To further improve the performance of Nafion, various nanofillers are incorporated into Nafion matrices, leading to the formation of composite PEMs with enhanced proton conductivity, mechanical strength and chemical stability. This review summarizes the recent advancements in Nafion composite PEMs based on four typical kinds of nanofillers: framework nanomaterials, carbon nanomaterials, polyoxometalate nanoclusters, and inorganic oxide nanoparticles. The preparation strategy, structure-property relationship and fuel cell applications of these membranes are discussed comprehensively, particularly focusing on the synergistic effect between Nafion and nanofillers. This review can provide an instructive insight for designing high-performance PEMs towards emerging energy technologies.

Study on dynamic stress variation of head cover bolt during transient operation of pump turbine

Abstract The head cover bolt is an important connecting part of pump turbine, if it is damaged, it will affect the operation safety of the unit and the power station. During the transient process, such as start-up and load rejection in extreme case, the head cover bolt is subjected to complex load action, and its stress also changes, and extreme cases may occur. The dynamic stress level of the bolt will have a certain influence on its fatigue life, therefore, in order to further study the dynamic stress level and variation law of the bolt, this paper relies on a pumped-storage station, the dynamic stress of the head cover bolt during the start-up and load rejection is measured, and the pressure pulsation between the head cover and the runner and the bladeless zone are collected synchronously. Through the data analysis, the bolt dynamic stress level and variation law and the correlation between stress and pressure fluctuation under the power generation and pumping conditions are summarized.

Study of the Impact of High Temperature of Cooling Water and Hydrocarbon Waste Discharged from Musayyib Thermal Station to the Euphrates River Using Remote Sensing Stations

The spread of industrial activities, especially electrical power generation stations on the banks of rivers, increases the pollution of the surrounding water environment as a result of the release of industrial water that is not treated adequately. Among these stations is the Al-Musayyib Thermal Power Station. The research focused onstudying the quality of the water entering and leaving the station by installing two sensing stations. Remote monitoring of the Euphrates River, as the station contains several sensors, including measuring acidity, dissolved oxygen, turbidity, and the amount of total salts, in addition to a sensor for measuring refined fuel. These results are collected around the clock at a central station, where the results showed a decrease in the level of dissolved oxygen ranging between (3.5-5) RSD% 0.1-0.2 as well as an increase in The temperature of the excreted water ranging between from(30Cº-33Cº) RSD% 0.1-0.2, both of which negatively affect the environmental life of living organisms, as well as the appearance of a high percentage of pollutants resulting from refined fuel, ranging between (2.1-8.1) ppm, The findings will contribute to improving the efficiency of treatment plants to suit the environment surrounding the river, In order to preserve the water environment, it is necessary to place oil dispensers in the treatment units, as well as work to reduce the temperatures of the cooling water, which are at temperatures higher than the medical grades coming out of the station.

Experimental Study on a Photovoltaic Direct-Drive and Municipal Electricity-Coupled Electric Heating System for a Low-Energy Building in Changchun, China

This paper takes a low-energy building in Changchun, China, as an object to test and study the characteristics of two heating modes, AC/DC (Alternative current/Direct current) switching and AC/DC synthesis, from the perspectives of temperature change, irradiation intensity, power generation, electricity consumption, etc. Firstly, the experimental research was conducted under two heating cable modes by establishing mathematical models and a test rig, and it was found that the photoelectric conversion efficiency on sunny, cloudy, and overcast days was 18%, 14.5%, and 12%, respectively. A simulation model was established by TRNSYS to run an ultra-low-energy building throughout the year. It was found that the highest and lowest monthly power generation occurred in February and July, respectively. The annual power generation of the system was 6614 kWh, and the heating season power generation was 3293.42 kWh. In the current research, the DC electricity consumption was slightly higher than the AC electricity consumption. Under conditions of similar radiation intensity and power generation, the indoor temperature of the AC/DC synthesis cable heating mode were 1.38% higher than the AC/DC switching heating able mode, and the electricity consumption were 10.9% and 4.76% higher, respectively, than those of the AC switching heating cable mode. This is of great significance for clean-energy heating, energy savings, and emissions reduction in northern China.

Efficient shrinkage temporal convolutional network model for photovoltaic power prediction

Power stations operating on PhotoVoltaic (PV) power generation are challenged by demand forecasting as PV power generation is random and intermittent. This paper presents an Efficient Shrinkage Temporal Convolutional Network (ESTCN) model, which combines the Temporal Convolutional Network (TCN) and an improved Deep Residual Shrinkage Network (DRSN) to forecast PV power output. First, the attention sub-network of the DRSN is improved, the fully connected layer of the sub-network is canceled, and feature extraction is done directly on the model features following global average pooling using a one-dimensional convolution to obtain cross-channel interaction and increased model efficiency. Next, an improved attention mechanism and adaptive soft thresholding are introduced into TCN to automatically determine the noise threshold to address the issue of information weight dispersion caused by redundant information in the input samples. By incorporating dilated causal convolution, attention module, soft thresholding, and residual connection, the ESTCN model is formed and is shown to enhance PV power output prediction with only a minimal increase in the number of parameters. The power station in Ningxia, China is adopted as a validation example with data taken from the year 2020. The fitting and prediction results of the ESTCN model are compared against the Convolutional Neural Network, Long Short-Term Memory, and TCN models. The ESTCN model yielded the following values of the evaluation metrics: Root Mean Square Error (RMSE) of 1.47 kW, Mean Absolute Error (MAE) of 0.79 kW, and coefficient of determination of 0.999. Compared to the TCN model, the prediction errors based on RMSE and MAE improved by 0.39 kW and 0.18 kW, respectively. Applying the ESTCN model to predict PV power generation of power stations in two regions in China, Ningxia and Xinjiang, shows the ESTCN model to be superior, scalable, and universal over other deep learning models.

Grid‐forming control for inverter‐based resources in power systems: A review on its operation, system stability, and prospective

AbstractThe increasing integration of inverter based resources (IBR) in the power system has a significant multi‐faceted impact on the power system operation and stability. Various control approaches are proposed for IBRs, broadly categorized into grid‐following and grid‐forming (GFM) control strategies. While the GFL has been in operation for some time, the relatively new GFMs are rarely deployed in the IBRs. This article aims to provide an understanding of the working principles and distinguish between these two control strategies. A survey of the recent GFM control approaches is also delivered here, expanding the existing classification. It also explores the role of GFM control and its types in power system dynamics and stability like voltage, frequency etc. Practical insight into these stabilities is provided using case studies, making this review article unique in its comprehensive approach. Lacking elsewhere, the GFMs' real‐world demonstrations and their applications in several IBRs like wind farms, photovoltaic power generation stations etc., are also analyzed. Finally, the research gaps are identified, and the prospect of GFM is presented based on the system needs, informed by GFM real‐world projects. This work is a potential road map for the GFM large‐scale deployment in the decarbonized IBR‐based bulk power system.

Nanostructured Materials for Enhanced Performance of Solid Oxide Fuel Cells: A Comprehensive Review

Solid oxide fuel cells (SOFCs) have emerged as promising candidates for efficient and environmentally friendly energy conversion technologies. Their high energy conversion efficiency and fuel flexibility make them particularly attractive for various applications, ranging from stationary power generation to portable electronic devices. Recently, research has focused on utilizing nanostructured materials to enhance the performance of SOFCs. This comprehensive review summarizes the latest advancements in the design, fabrication, and characterization of nanostructured materials integrated in SOFC. The review begins by elucidating the fundamental principles underlying SOFC operation, emphasizing the critical role of electrode materials, electrolytes, and interfacial interactions in overall cell performance, and the importance of nanostructured materials in addressing key challenges. It provides an in-depth analysis of various types of nanostructures, highlighting their roles in improving the electrochemical performance, stability, and durability of SOFCs. Furthermore, this review delves into the fabrication techniques that enable precise control over nanostructure morphology, composition, and architecture. The influence of nanoscale effects on ionic and electronic transport within the electrolyte and electrodes is thoroughly explored, shedding light on the mechanisms behind enhanced performance. By providing a comprehensive overview of the current state of research on nanostructured materials for SOFCs, this review aims to guide researchers, engineers, and policymakers toward the development of high-performance, cost-effective, and sustainable energy conversion systems.

Predictive Maintenance Framework for Fault Detection in Remote Terminal Units

The scheduled maintenance of industrial equipment is usually performed with a low frequency, as it usually leads to unpredicted downtime in business operations. Nevertheless, this confers a risk of failure in individual modules of the equipment, which may diminish its performance or even lead to its breakdown, rendering it non-operational. Lately, predictive maintenance methods have been considered for industrial systems, such as power generation stations, as a proactive measure for preventing failures. Such methods use data gathered from industrial equipment and Machine Learning (ML) algorithms to identify data patterns that indicate anomalies and may lead to potential failures. However, industrial equipment exhibits specific behavior and interactions that originate from its configuration from the manufacturer and the system that is installed, which constitutes a great challenge for the effectiveness of ML model maintenance and failure predictions. In this article, we propose a novel method for tackling this challenge based on the development of a digital twin for industrial equipment known as a Remote Terminal Unit (RTU). RTUs are used in electrical systems to provide the remote monitoring and control of critical equipment, such as power generators. The method is applied in an RTU that is connected to a real power generator within a Public Power Corporation (PPC) facility, where operational anomalies are forecasted based on measurements of its processing power, operating temperature, voltage, and storage memory.

Simulation methodology and numerical comparison of boxer and opposed free piston linear generator configuration in 0D/1D environment

Free Piston Linear Generators (FPLGs) are thermal machines suitable for both stationary power generation unit (PU) and vehicle propulsion. They convert chemical energy from the fuel into electric energy to charge a battery using a linear electric generator. Due to the reduction of friction losses and the ability to work with different compression ratios, FPLGs are potentially characterized by high overall global efficiency with respect to a conventional alternative internal combustion engine. Like conventional internal combustion engines, FPLGs have several configurations: single piston, dual piston, opposed piston and boxer are the configurations considered in this work. Two configurations are compared in this paper from a functional and energetic perspective: opposed piston (Opposed) and Boxer. This is done with the aim to highlights pro and cons of these configurations. They are modelled using the 0D/1D modelling coupling GT-Power® and Simulink®. The comparison between the two configurations was done modelling the architecture with the same size and in two-strokes operating mode. The comparison of the two configurations highlights differences between them in terms of scavenging process, thermodynamic efficiency and global energy efficiency, putting in evidence what aspects need to be improved for each configuration and what are their advantageous features. Boxer configuration can provide less power due to lower volumetric efficiency compared to the Opposed configuration. Boxer configuration can provide 102.2 kW while Opposed can provide 110.0 kW at full load with a frequency of 20 Hz (equivalent to 1200 rpm). The Opposed configuration results in lower heat loss but higher energy lost at the exhaust. The final balance shows that Boxer configuration has a slightly higher brake efficiency (equal to 28.9 %) compared to the value found for Opposed (27.6 %).

Energy loss mechanism of a full tubular pump under reverse power generation conditions using entropy production theory

This paper investigates the energy dissipation mechanism of the internal flow field of the full tubular pump during reverse power generation and pump conditions, utilizing CFD and model test methods to research the device’s hydraulic characteristics, internal flow field and entropy production. The results indicate that the reverse power generation and pump conditions’ performance curves have opposite trends. Under PRPG conditions, the flow uniformity and weighted average angle of the impeller inlet flow field are smaller and the inlet flow field is poor. The stator-rotor gap flow under PRPG conditions increases with the increase in total flow, the gap flow under the design flow is 2.88 L/s, and the torque is 7.35 N·m. Under the PRPG condition, the turbulent and wall entropy production ratio increases gradually with the flow increase. Under the design flow rate, the entropy production rate of the impeller is 55.07%, and the entropy production rate of the impeller is the largest among the components under different flow rates. The entropy production of the outlet channel rises significantly with the flow rate. The research results of this paper provide a theoretical basis for the distribution of energy loss in reverse power generation of the full tubular pump.

Modular Open Source Solar Photovoltaic-Powered DC Nanogrids with Efficient Energy Management System

Initially the concept of a DC nanogrid was focused on supplying power to individual homes. Techno-economic advances in photovoltaic (PV) technology have enabled solar PV stand-alone nanogrids to power individual devices using device-specific architectures. To reduce costs and increase accessibility for a wider range of people, a modular open-source system is needed to cover all applications at once. This article introduces a modular PV-powered nanogrid system, consisting of a do it yourself (DIY) PV system with batteries to allow for off-grid power. The resultant open-source modular DC nanogrid can deliver DC power to loads of different voltage levels, which is possible because of the efficient and parametric energy management system (EMS) that selects modes of operation for the grid based on DC bus voltage and state of charge of batteries. Simulation results verify the coordination between the EMS and the PV-battery system under varying PV power generation and load conditions. This EMS has potential to enable easy personalization of a vast area of applications and expand appropriate technology for isolated communities. A thorough stability analysis has been conducted, leading to the development of an LQR (Linear Quadratic Regulator) controller as a replacement for the conventional PI (Proportional - Integral) controllers for better transient stability of the system.

Experimental and Numerical Investigation of Cavitation Assessment for Runner Blades in a Francis Turbine

Cavitation in hydro turbines causes component deterioration that requires continuous and costly maintenance in the hydroelectric power generation stations. The Tarbela Dam Hydel Project (TDHP) in Pakistan is facing a cavitation problem in the Francis Turbine components, such as the runner and draft tube. Simulation work has been performed to examine and quantify the cavitation rate as a function of the suction head (SH) and flow velocity (FV) by utilizing a homogeneous cavitation model. The result shows that pressure fluctuation is maximum for overcrowded conditions and minimum for rated load conditions. Moreover, a higher cavitation rate is found for the part and overcrowded conditions compared to the rated load condition. Additionally, the cavitation rate becomes 50% higher when the SH increases from 5.54 to 12.34 m. Moreover, SEM results have verified the CFD results that higher FV and SH enhance the cavitation rate. Furthermore, the numerical work is validated by simplified hydrofoil geometry. The computational fluid dynamics results presented a good arrangement with the experimental data.

Experimental and modeling study of full- condition combustion characteristics of exhaust gas burners for solid oxide fuel cells

SOFC exhaust gas burner is an essential component of the SOFC thermal management system. The burner in the whole operating conditions of safe and stable combustion and smooth transition in the switching operating conditions is of great significance to the long-term and efficient operation of the SOFC power generation system. This paper builds an experimental test platform for the SOFC exhaust gas burner, tests the combustion performance of the burner in full operating conditions and operating conditions switching process, and establishes a prediction model for the combustion performance of SOFC exhaust gas burner by machine learning algorithm. The results show that the SOFC exhaust gas burner can meet the requirements of safe and stable combustion in all operating conditions and smooth transition between operating conditions; reliable combustion is achieved at the stable power generation condition with excess air factor of 7 ∼ 26, and the average cathode and anode pressure drop in the stable power generation condition is 142 Pa and 185 Pa, respectively; BP neural networks, support vector machines and random forests are used to establish a prediction model for the performance of the SOFC exhaust gas burner, and the random forests achieve the best prediction effect.

Dynamic response analysis of a semi-submersible floating wind turbine based on different coupling methods

This article compares and analyzes the overall performance of offshore floating wind turbines using fully coupled and semi-coupled methods considering aerodynamic loads, as well as decoupled methods without considering aerodynamic loads. The aim is to study the impact of different coupling methods on the dynamic response of floating wind turbines and provide a reference for selecting more convenient calculation methods for the preliminary design of floating wind turbines. Based on the open-source software OpenFAST and the commercial hydrodynamic software AQWA, the OC4-DeepCwind semi-submersible offshore floating wind turbine foundation and the NREL 5 MW reference wind turbine model are selected as the research objects. The natural period of the floating structure is validated, and then the power generation and shutdown conditions of the floating wind turbine are selected as the calculation conditions. The motion responses of the floating structure and mooring tension of the floating wind turbine are calculated in the time domain, and the calculation results are statistically analyzed. The research results show that the decoupled analysis method without considering aerodynamic loads significantly underestimates the dynamic response of the floating wind turbine, and the semi-coupled method is more conservative than the fully coupled method. Therefore, in the absence of conditions for fully coupled analysis, the semi-coupled method can be used as a substitute analysis method in the preliminary design stage.

Assessment of Offshore Wind Power Potential and Wind Energy Prediction Using Recurrent Neural Networks

In recent years, Taiwan has actively pursued the development of renewable energy, with offshore wind power assessments indicating that 80% of the world’s best wind fields are located in the western seas of Taiwan. The aim of this study is to maximize offshore wind power generation and develop a method for predicting offshore wind power, thereby exploring the potential of offshore wind power in Taiwan. The research employs machine learning techniques to establish a wind speed prediction model and formulates a real-time wind power potential assessment method. The study utilizes long short-term memory networks (LSTM), gated recurrent units, and stacked recurrent neural networks with LSTM units as the architecture for the wind speed prediction model. Furthermore, the prediction models are categorized into annual and seasonal patterns based on the seasonal characteristics of the wind. The research evaluates the optimal model by analyzing the results of the two patterns to predict the power generation conditions for 1 to 12 h. The study region includes offshore areas near Hsinchu and Kaohsiung in Taiwan. The novelty of the study lies in the systematic analysis using multiple sets of wind turbines, covering aspects such as wind power potential assessment, wind speed prediction, and fixed and floating wind turbine considerations. The research comprehensively considers the impact of different offshore locations, turbine hub heights, rotor-swept areas, and wind field energy on power generation. Ultimately, based on the research findings, it is recommended to choose the SG 8.0-167 DD wind turbine system for the Hsinchu offshore area and the SG 6.0-154 wind turbine system for the Kaohsiung offshore area, serving as reference cases for wind turbine selection.

Environmental fate of microplastics in alpine and canyon-type river-cascade reservoir systems: Large-scale investigation of the Yalong River in the eastern Qinghai-Tibet Plateau

Reservoirs are regarded as potential collection sites for microplastics (MPs), and ample water resources in plateau regions provide favorable natural conditions for hydroelectric power generation. However, research on the impact of cascade reservoir construction in the plateau region on the fate of MPs within the watershed is limited. In this study, the Yalong River, an alpine canyon river in the eastern Qinghai-Tibet Plateau, was selected as the research area. This study explored the distribution of MPs at various depths in water, sediment, and riverbank soil as well as the formation of “MP communities” within the river-cascade reservoir system. Furthermore, the effects of dam construction on MPs' migration in different environments were analyzed. The results revealed that the abundance of MPs in the water and sediment within the cascade reservoir area (CRA) was significantly higher than that in the river area (RA) (P < 0.001). Additionally, the trend of increasing MPs in water with decreasing altitude was notably slower in CRA. Regarding shape, the proportion of fibers in the water within the CRA was significantly lower than that in the RA, with a smaller vertical migration rate in the water than in the sediment. The proportion of MPs < 500 μm in the water within the CRA was significantly higher than that in the RA. High-density MPs were notably deposited in the reservoir sediments. The analysis of the MP communities revealed that the construction of cascade dams led to relative geographical isolation between different sampling sites, reducing the similarity of MP communities in the CRA. This study established a theoretical foundation for understanding the impact of cascade dam construction on the fate characteristics of MPs and their potential risks in plateau areas.