Output Power Variation Research Articles

Navigating Economies of Scale and Multiples for Nuclear-Powered Data Centers and Other Applications with High Service Availability Needs

Nuclear energy is increasingly being considered for such targeted energy applications as data centers in light of their high capacity factors and low carbon emissions. This paper focuses on assessing the tradeoffs between economies of scale versus mass production to identify promising reactor sizes to meet data center demands. A framework is then built using the best cost estimates from the literature to identify ideal reactor power sizes for the needs of the given data center. Results should not be taken to be deterministic but highlight the variability of ideal reactor power output against the required demand. While certain advocates claim that with the gigawatts of clean, firm energy needed, large plants are ideal, others advocate for SMRs that can be deployed in large quantities and reap the benefits from learning effects. The findings of this study showcase that identifying the optimal size for a reactor is likely more nuanced and dependent on the application and its requirements. Overall, the study does show potential economic promise for coupling nuclear reactors to data centers and industrial heat applications under certain key conditions and assumptions.

Strategy for enhancing energy conversion efficiency and cyclist helmet safety: A theoretical and experimental study of diverse thermoelectric generator models

Recent studies have focused on Thermoelectric Generators (TEGs) as a key to sustainable energy, using thermal power through temperature differentials to produce electric power. Despite the promise of TEGs, there is diversity of TEG models and the shortage of comprehensive evaluations on energy conversion. In particular, measuring the output of electrical energy and time of production across temperature variances, which has impeded their broad adoption. This research conducted a comprehensive analysis of TEG models. It used a new test rig designed in SolidWorks and actualized, coupled with MATLAB simulations to validate the predicted results. This includes developing a wearable device such as a helmet-mounted warning light for motorcyclists or cyclists. In the study, five different thermoelectric generator models (TEG1-12703, TEG1-12706, TEG1-12709, TEG1-12712, and TEG1-12715) were tested, these models showed varying power outputs of 66.46, 97.51, 117.5, 191.72 and 358.74 mW. Their efficiencies were 1.78 %, 1.982 %, 2.097 %, 2.567 % and 2.93 %, respectively, when ΔT reaches 30 °C. The experimental and theoretical data indicate discrepancies in results and thermal response delays due to heat transfer and energy conversion within the test rig’s layers. These discrepancies were addressed to adjust simulations closer to reality. A differential correction ratio (19.133 % for power, 17.94 % for efficiency) was applied to enhance prediction accuracy. After adjustment, the maximum power generation reached 1.64355, 2.8386, 3.83433, 4.6843, 4.96746 W. The maximum efficiency peaked at 2.236, 3.59462, 4.1184, 6.278154, 6.75779 %, respectively, when ΔT reaches 70 °C. The output power and efficiency from these TEGs could run certain sensors.The study shows that TEG model 12,715 excels in generating electrical energy with large temperature differences. However, its output nearly vanished under a 1 °C differential, ending tests prematurely. In contrast, the model 12,703 consistently generates electricity over long periods (more than 420 min) under minimal temperature differential, while it is unable to produce high power under greater differentials. This suggests that using diverse TEG models and integrating together to enhance the efficiency and continuity of free energy generation, depends on the models’ varied performance and temperature differences. Utilizing the results, five TEG units connected in parallel were installed on a cyclist’s helmet to power a rear warning light, this installation enhances night-time safety. These TEG models demonstrated continuous power generation, producing an average of 55.7 mW per hour with a temperature difference ΔT between 3.2 °C and 7.4 °C.

Fault Detection on Short-Haul or Highly Dynamic Flights Using Transient Flight Segments

Abstract A machine learning-based approach is presented, which allows to detect persistent engine faults after a single flight. It utilizes transient in-flight measurements and a transient engine model. The time series of the residuals between the measured data and the data resulting from performance synthesis is evaluated using moving windows containing at least one transient segment. A continuous wavelet transformation and a pretrained convolutional neural network are utilized on the residuals for feature extraction. The fault detection is carried out via a one-class support vector machine, trained exclusively on nominal engine operation data. Therefore, the approach requires no a-priory knowledge of the effects of engine faults on the in-flight measurements. Under the assumption of persistent faults, all windows of a single flight, which contain at least one transient segment, are considered in order to improve the reliability of the fault detection. This approach is validated using measured data of a small helicopter engine that replicates the dynamic flight of the corresponding model helicopter on a ground test bed. Consequently, step changes as well as complex variations of the shaft power output are considered. Four standard gas path sensors are considered. The one-class support vector machine is used successfully to detect two types of total pressure sensor anomalies. Assuming a typical number of transient segments for an average short haul flight, it turns out that persistent faults can be detected within one flight with a probability of above 90%.

FOPDT model and CHR method based control of flywheel energy storage integrated microgrid

The main causes of frequency instability or oscillations in islanded microgrids are unstable load and varying power output from distributed generating units (DGUs). An important challenge for islanded microgrid systems powered by renewable energy is maintaining frequency stability. To address this issue, a proportional integral derivative (PID) controller is designed in this article. Firstly, islanded microgrid model is constructed by incorporating various DGUs and flywheel energy storage system (FESS). Further, considering first order transfer function of FESS and DGUs, a linearized transfer function is obtained. This transfer function is further approximated into first order plus time delay (FOPTD) form to design PID control strategy, which is efficient and easy to analyze. PID parameters are evaluated using the Chien-Hrones-Reswick (CHR) method for set point tracking and load disturbance rejection for 0% and 20% overshoot. The CHR method for load disturbance rejection for 20% overshoot emerges as the preferred choice over other discussed tuning methods. The effectiveness of the discussed method is demonstrated through frequency analysis and transient responses and also validated through real time simulations. Moreover, tabulated data presenting tuning parameters, time domain specifications and comparative frequency plots, support the validity of the proposed tuning method for PID control design of the presented islanded model.

Energy and environmental performance from field operation of commercial-scale SOFC systems

Solid Oxide Fuel Cells (SOFCs) are capable of generating electrical and thermal power with very high conversion efficiency and almost no pollutant emissions into the atmosphere. Despite extensive literature on SOFC-based energy system models and experimental testing at the cell and short-stack level, there is currently a lack of performance data for SOFC modules under actual field conditions. To fill this gap, the present work investigates the energy and environmental performance of six SOFC modules, ranging in size from 10 to 60 kW, over thousands of hours of operation. These systems, supplied by the three leading SOFC manufacturers in Europe, have been installed and operated in different non-residential buildings worldwide, as part of the European Comsos project. The aim of this study is to establish a comprehensive set of field operation data to characterise commercial-scale SOFC systems. Specifically, raw data are processed to derived electrical and thermal efficiency maps, degradation rates and pollutant emissions, including particulate matter (PM), nitrogen oxides (NOx) and carbon monoxide (CO). A comparison with competing technologies is also provided to better highlight the potential benefits of adopting SOFC-based cogeneration systems. Values in the range of 51–61% were found for the system-level electrical efficiency under rated conditions. The electrical efficiency also remained consistently high across a wide modulation range (between 50% and 100% of rated power), with peak values reaching 65%. In addition, promising results were obtained for the average percentage loss in electrical efficiency, with a minimum value of 0.7%/1000 h. Regarding the environmental analysis, NOx and CO emissions were analysed at both constant and variable power output, proving to be impressively low across the entire modulation range. The same applies to PM concentrations, which were below ambient level. Overall, SOFCs demonstrated to be one of the best cogeneration solutions for commercial-scale systems (tens to hundreds of kW in size), from both an energy and environmental perspective. However, further reductions in costs and dedicated financial schemes are necessary for a widespread market penetration.

Exploring the impact of variable power outputs on the efficacy and safety during microwave ablation for lung carcinoma: a real-world study.

Microwave ablation (MWA) is an important method for the treatment of lung cancer, but there is still a lack of standard guidelines for the selection of power. This study aimed to explore the effectiveness and safety of MWA at different power levels. The study gathered individuals underwent MWA for lung cancer between January 2012 and December 2020. All patients were divided into low power group and high power group based on the power of MWA. By intergroup comparisons, we clarified the differences between the two groups. In this study, 265 participants were involved, with 192 in the low power group and 73 in the high power group. Compared to the low power group, the high power group had a significantly higher incidence of postoperative complications (63.0% vs. 24.0%). In the Kaplan-Meier analysis, overall survival (OS) and disease-free survival (DFS) of the high power group were both better than the low power group. We found through Cox regression analysis that smoking, tumor volume, tumor differentiation, gene mutation, neutrophil count, and lymphocyte count were independent factors affecting the OS of patients. Based on the above factors, we constructed a nomogram, with areas under the curve (AUCs) of 0.941, 0.903, and 0.905 for predicting 1-, 2-, and 3-year OS after MWA, respectively. While high-power MWA brings better long-term prognosis to patients, it also leads to an increase in postoperative complications. The application of a nomogram for stratifying the prognosis of patients may be a more feasible approach to further develop individualized treatment plans.

Smart Grid Technologies: Advancements and Applications in Nigeria

This study explores the impact of smart grid technologies on the modernization of power grids in response to evolving energy demands and the integration of renewable energy sources in Nigeria. It aims to empirically assess advancements in smart grid technologies, focusing on four key objectives: eval_uating the impact of smart meters on energy consumption and peak demand reduction, analyzing the effectiveness of Advanced Distribution Management Systems (ADMS) in enhancing grid reliability and efficiency, assessing the role of demand response programs in balancing supply and demand, and examining the integration and management of Distributed Energy Resources (DERs) within smart grids. The research employs a quantitative methodology, collecting and analyzing data from utility companies that have implemented smart grid technologies. Key findings reveal that smart meters significantly reduce energy consumption and peak demand by providing real-time monitoring, while ADMS improves grid reliability and operational efficiency through enhanced fault detection and automated control. Demand response programs effectively balance energy supply and demand, reducing peak loads and energy costs. The integration of DERs increases renewable energy utilization and grid stability but also presents challenges related to variability in power output and management complexity. The study concludes that smart grid technologies play a crucial role in achieving a more resilient and efficient power grid, though addressing challenges related to DER integration and system management is essential for maximizing their benefits.

An assessment methodology for the flexibility capacity of new power system based on two-stage robust optimization

The inherent variability in wind and solar power output presents a significant challenge to the flexibility balance of power systems. This paper introduces an innovative method for evaluating the flexibility capacity of a new power system, employing a two-stage robust optimization approach. Firstly, a power system flexibility supply and demand balance mechanism model is constructed and quantitatively characterized for the power system flexibility shortfalls set. Subsequently, taking into account timescale characteristics and directionality, the time series production simulation technique is applied to establish the effective ramping and flexibility supply distribution model of thermal power and energy storage units, enabling an analysis of the power system's supply regulation capabilities. On this basis, a power system flexibility capacity assessment method is proposed, which divides the system regulation resources into demand set and supply set, and constructs a power system flexibility capacity assessment model to ensure that the maximum system flexibility margin and the lowest operating cost are taken as the optimization objectives under the system security operation constraints. The column and constraint generation (C&CG) robust optimization algorithm is used to decompose the master problem and the max-min dual-layer subproblems for iterative solving, and the optimal capacity of each unit of the system in terms of output and flexibility is derived. Finally, the effectiveness and superiority of the proposed method is verified through case analysis, which shows that the method can improve the flexibility capacity by 14.9% and reduce the operating cost by 15.83% compared with the traditional proportional allocation method.

Hardware in the loop testing of converter control in solar PV and BESS based islanded microgrid

Over the past decades, microgrids have garnered significant attention due to their ability to offer resilient power supply and efficiently integrate renewable energy sources (RESs). The test model includes an islanded microgrid having common voltage source converter for solar photovoltaic and battery energy storage system, characterized by low inertia. To minimize the effect of reduced inertia caused by lack of synchronous generators and also to cope up with the variation in power output from different renewable energy sources, an adaptive virtual inertia and damping based control, is incorporated through voltage source converter control, utilizing swing equation of the synchronous generator. However, it is imperative to verify the proposed control strategy before implementation in an actual plant. In that direction, this paper discusses the practicality of the proposed control in the real-time using Controller Hardware-in-the-Loop (CHIL) platform. So, the plant is built in real time simulator OP4512 and the proposed control is implemented using practical microcontroller TMS320F28379D. Subsequently, configuration and modelling of ADC and EPWM are explained. CHIL testing platform demonstrates flawless compatibility with the converter control, having a system model running in real time. Simulation results are compared with that of HIL results for various loading configurations, hence proving the efficacy of the proposed control strategy.

Hybrid offshore wind–solar energy farms: A novel approach through retrofitting

Due to the inherent variability of the power output of offshore wind farms, their integration into electrical grids poses a challenge to their stability and leads to significant balancing costs. Combining wind and solar power may be expected to mitigate the power output variability. In addition, a number of synergies can be realised—shared infrastructure, shared crews and vessels for operations and maintenance, and last but not least, optimum use of scarce marine space. The objective of this work is to investigate this hybrid approach and, in particular, to determine the optimum capacity of the solar energy subsystem given a certain installed capacity of the wind energy subsystem. Three case studies are considered in Europe and China. Each of them is an existing wind farm that could be retrofitted with floating solar PV. After assessing the local wind and solar energy resources, the optimal size of the floating solar array is calculated with a view to smooth the aggregated power output of each farm. Subsequently, the benefits of this hybrid approach are demonstrated from various perspectives. It is found that a much larger solar array is required for a wind farm with a large installed capacity, but the specific optimal size depends more on the local wind and solar resources. The novelty of this paper lies in its exploration of retrofitting existing offshore wind turbines with floating solar PV systems from the perspective of addressing the variability challenge for the currently operating wind farms. This study could serve as a guideline for project designs aiming to retrofit existing offshore wind farms with solar PV technology, thus reducing balancing costs and facilitating the penetration of offshore renewable energy into national power grids.

Impact of shading heaviness on voltage, current and power of the solar photovoltaic string

The short-term power output variability of solar photovoltaic (PV) systems caused by passing clouds is becoming a major concern for grid operators. As the penetration of utility-scale PV systems boosts, the rapid power fluctuations greatly challenge the grid's transient stability. A photo voltaic system is greatly vulnerable to Partial Shading. The performance analysis of PV systems clearly suggests that the maximum power of partially shaded PV systems is inversely proportional to the heaviness of shading. However, some literatures are not of the same opinion; for them, the maximum power of a partially shaded system is invulnerable to shading heaviness, often at certain critical points. According to research on the P-V characteristic curve under various numbers of shaded modules and shading levels, the irradiance of the shaded modules reaches a certain turning point or critical point. The PV array becomes insensitive to high-level shading, categorically for the series topology. This paper presents an experimental results of performance parameters with varying shading heaviness. The experiment is performed on a Photovoltaics string of series connected modules, a 119KW grid-connected rooftop solar power plant using the Power Quality analyser for continuous recording of various parameters under changing shading heaviness. The degree or heaviness of shading decides the critical point. The critical point can vary based on the number of the shaded modules.

Future scenario generation and reduction methods for solar photovoltaic electricity production analysis

Abstract A morphing-clustering-based method of generation and reduction future scenario for solar photovoltaic electricity production analysis is studied. Present historical annual weather data are transformed into future scenarios and timeframes by a morphing method with a general circulation model. The Copula methodology is applied to model the forthcoming decade’s annual meteorological data and generate abundant intra-day hourly scenario samples. The comparative analysis of the photovoltaic power output variations between future and present in reduction typical scenarios is conducted by the K-means clustering method with appropriate clustering parameter optimization. The simulation results show that the annual mean variations in global horizontal radiation, dry bulb temperature, and wind speed are projected to increase by approximately from 20.1 to 36.5 W/m2, 1.6 to 2.3°C, and 0.1 to 0.6 m/s, respectively in the forthcoming scenario of shared socioeconomic pathways 2-4.5. It is seen that solar photovoltaic electricity production anticipates a positive increase from 2.5% to 17.9%.

Experimental investigation of the wake of tandem cylinders using pivoted flapping mechanism for piezoelectric flag

In this paper, the current of ocean at a depth with the velocity of 0.1–0.3 m/s has been studied. The effect of the mounting mechanism of the piezoelectric flag on the energy efficiency of the energy harvester is investigated. The flag is mounted uniquely, and the results are analyzed to explain the underlying mechanism associated with variations in power output. The experiments described extend our previous work and it is the experimental investigation of the baseline case for our previous work. It was found that using a pivoted mounting mechanism caused a significant improvement in flapping amplitude (51%) and dominant frequency (23%). The variation in the flag's distance from the bluff body (Gd) is also investigated. The maximum output for a passively mounted flag was obtained at Gd=2D due to the existence of a vortex core position at the same point where the flag's head was positioned. The same mechanism is implemented for tandem cylinder arrangement. The study found that increasing the distance between the bluff bodies resulted in the suppression of vortex shedding of the upstream cylinder by the rear cylinder. However, this behavior was found to be random and was thoroughly explored in this study. The obtained results were also verified through the flow visualization technique. A comparative analysis is made to show the optimal performance of the harvester by fine-tuning parameters such as the gap between cylinders and piezo flag, flow rate, and flag-mounting technique. The comparative analysis with benchmark cases demonstrated a rise in the A/L ratio by 30.25% and in the flapping frequency by 19.09% in the case of 120° cut C-shaped inverted cylinder upstream, indicating a higher percentage gain of 66% more energy harvesting. An increase of 51.18% in the A/L ratio and 22.79% in flapping frequency with the use of a pivot-mounted piezoelectric flag was observed, indicating higher energy harvesting performance compared to the baseline case (circular cylinder with fixed flag head).

Efficiency Optimization in Parallel LLC Resonant Inverters with Current-Controlled Variable-Inductor and Phase Shift for Induction Heating

This paper presents a comprehensive analysis of a novel control approach to improve the efficiency of parallel LLC resonant inverters using a combination of a current controlled variable inductor (VI) and phase shift (PS). The proposed control aims to reduce the Root Mean Square (RMS) current, thereby reducing conduction and switching losses, and improving power transfer efficiency, while considering zero-voltage-switching (ZVS) operation, output power variations and load changes. Furthermore, a design methodology for the variable inductor is proposed, and design considerations relevant to this application are discussed. The effectiveness of the proposed approach is evaluated through mathematical modeling and experimental results. The mathematical modeling results show that the proposed approach, utilizing SiC MOSFETs, maintains a maximum efficiency of 98.5% for a 20 kW inverter over a wider range of output power, which is a significant improvement over existing approaches. The experimental results also confirm the effectiveness of the proposed control in improving the efficiency of parallel LLC resonant inverters.

Offshore wind power prediction based on two-stage hybrid modeling**

Accurate prediction of offshore wind power generation is essential for efficient power scheduling and grid integration. This study introduces an innovative hybrid forecasting approach to address variability in power output due to different climatic conditions and challenges in measuring offshore wind speeds. The approach consists of two primary phases. First, a gated recurrent unit neural network with an attentional mechanism and a quantile regression model forecast wind speeds between cut-in and rated wind speeds, capturing trends under distinct climatic conditions. Second, wind speeds at nine quantile points are used as inputs to a relevance vector machine model, optimized via a cuckoo search algorithm, to establish the relationship between wind speed and power output. An empirical evaluation on a European offshore wind power dataset validates the approach's effectiveness across various climatic conditions. The two-stage model demonstrates enhanced adaptability, offering more reliable power predictions than conventional methods. Results indicate this hybrid forecasting method is more accurate than traditional techniques, significantly improving offshore wind power prediction performance.

Coordinated scheduling of wind-solar-hydrogen-battery storage system for techno-economic-environmental optimization of hydrogen production

Green hydrogen production powered by renewable energy emerges as a promising alternative to reduce emissions in the context of the global Net Zero target. Nevertheless, the inherent randomness and intermittency of renewables such as wind and solar cause prominent fluctuations in power supply to water electrolyzers, which pose challenges to their operational stability and efficiency, leading to decreased performance and shortened lifespan. To address these challenges, coordinated operation scheduling of the renewables-hydrogen system with multi-electrolyzers is investigated to enhance the system’s stability and efficiency while contributing to higher cost-effectiveness and sustainability. Meanwhile, the battery storage system is incorporated as a buffer to mitigate the variability of renewable power output and as a supplement to alkaline electrolyzers (AEL). This study also designs a dung beetle optimizer-gated recurrent unit (DBO-GRU) model for wind-solar power forecasting, offering guidance for more efficient and adaptive scheduling of AEL operations. To achieve multi-optimized scheduling of this integrated energy system, a refined rolling optimization strategy is developed, considering technical, economic, and environmental benefits to comprehensively improve green hydrogen production. Case studies using real-world scenarios validate its superiority across multiple time scales. For instance, compared with two other scheduling methods, the results show that the proposed strategy can respectively increase hydrogen production, reduce start-stop cycles, decrease LCOH, and lower carbon emissions by up to 4.19%, 25.40%, 7.98%, and 5.71% over a yearly-long operation. Therefore, the refined rolling optimization strategy simultaneously improves the overall system efficiency, operational cost-effectiveness, and sustainability of hydrogen production, underscoring its advantages and significance.

High thermal stability and high-performance efficiency capability of light sources–based rate equation models in optical fiber transmission systems

Abstract This paper clarified the high thermal stability and high-performance efficiency capability of silicon light sources–based rate equation models in the optical fiber transmission systems. The laser diode and light emitting diode output power variations are measured with input injection current under various ambient temperature effects. The light source differential quantum efficiency is demonstrated for both LED and laser diode with different injection input current and various temperature variations. The LED/laser diode light source external efficiency is clarified with different injection input current and various temperature variations. The LED/laser diode light source total efficiency is measured with different injection input current and various temperature variations. As well as the laser diode and light emitting diode, threshold current variations are demonstrated clearly with input injection current under room temperature and various spectral thermal effects. The laser diode and light emitting diode power dissipation variations are measured with input injection current under room temperature and various spectral thermal effects.

Optimization and analysis of methanol production from CO2 and solar-driven hydrogen production: A Danish case study

This paper presents a comprehensive techno-economic analysis of the world's first large-scale commercial Power-to-X (PtX) plant in Kassø, Denmark. This innovative facility combines solar photovoltaic (PV), an electrical grid, green hydrogen production, methanol synthesis, and district heating in an integrated system. We conduct an in-depth analysis to explore optimal operating conditions, the potential for sector coupling within the power and heat sectors, and the economic feasibility of the integrated system. In particular, we study different scenarios considering changes in solar PV power generation, electricity market price, CO2 price, and methanol price to explore their impacts on the system performance. Our results show that the electrolyzer's operation, a pivotal component of the system, heavily depends on the electricity spot price as well as the methanol price. Based on the green production of methanol, a premium price of 4800 DKK/t (0.64 €/t) is considered in this study (selling price of 8400 DKK/t). The results show that in case of high electricity prices (2022 spot market) or no premium price for methanol, the optimum annual production of methanol decreases by 58% and 67%, respectively. Furthermore, we observe that the variability of solar power output significantly impacts the plant's performance and economic viability, as it supplies about 30% of the plant's power consumption. Although the results are unique to the Kassø plant, the study's techniques and insights can be applied to other comparable systems around the world. The study also highlights how crucial it is to take market, climate, and technical factors into account when developing and running integrated energy systems.

Evaluation of an Erbium-Doped Fiber Ring Laser as an Edge Filtering Device for Fiber Bragg Grating Sensor Interrogation

An easy-to-implement and cost-effective Fiber Bragg Grating (FBG) sensor interrogation technique based on a ring Erbium-Doped Fiber Laser (EDFL) topology is proposed and experimentally assessed. The FBG sensor is part of the EDFL cavity and must have a central wavelength located within the linear region of the EDF’s amplified spontaneous emission (ASE) spectrum, which occurs at between 1530 and 1540 nm. In this manner, the wavelength-encoded response of the FBG under strain is converted to a linear variation in the laser output power, removing the need for spectrum analysis as well as any limitations from the use of external edge-filtering components. In addition, the laser linewidth is significantly reduced with respect to the FBG bandwidth, thus improving the resolution of the system, whereas its sensitivity can be controlled through pumping power. The performance of the system has been characterized by modeling and experiments for EDFs with different lengths, doping concentrations, and pumping power levels. The influence of mode-hopping in the laser cavity on the resolution and accuracy of the system has also been investigated.

Narrow linewidth fiber laser using compound-ring cavity filter and self-injection locked mechanism

Narrow linewidth erbium-doped fiber lasers (EDFLs) hold in significant potential optical fiber sensing, wavelength multiplexing transmission, and optical fiber communication. However, many EDFLs produced outputs with linewidth in several kHz level. Therefore, a high optical signal-to-noise ratio (OSNR), narrow linewidth single-longitudinal-mode (SLM) EDFL was proposed and investigated in this work. The EDFL utilized a combination of compound-ring cavity filter and a self-injection locked mechanism to generate a stable SLM output with an OSNR greater than 72 dB. The maximum wavelength drift and maximum peak power fluctuation over 60 min were maintained at low values of 0.0041 nm and 0.16 dB. Moreover, a narrow linewidth of 1.82 kHz at a measuring time of 0.002 s was realized. Furthermore, the research also investigated output power variations with different pump powers, relaxation oscillation, and the dependence of output central wavelength on the axial strain.