Power Fluctuations Research Articles

High-performance 320-nm continuous-wave solid-state laser

For the first time, to our knowledge, we realized a high-performance 320-nm continuous-wave (CW) laser with a fiber-coupled blue laser diode as the pump source. A V-shaped folded cavity is constituted by three mirrors, with a Pr3+:LiYF4 (Pr:YLF) as the laser crystal and a LiB3O5 (LBO) as the frequency doubling crystal, respectively. Under an absorbed pump power of 19.5 W, the maximum 320-nm output power reaches 4.26 W, corresponding to an optical conversion efficiency of 21.8% and a root-mean-square (RMS) power fluctuation of 0.61%, which give the best results of a 320-nm CW laser up to now. The excellent performance will make this ultraviolet laser source very suitable for practical applications, including semiconductor detection, spectral analysis, microscopic imaging, and biotechnology.

State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control

To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by hybrid energy storage systems (HESSs), this paper proposes a state of charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.

Multi-Time Scale Energy Storage Optimization of DC Microgrid Source-Load Storage Based on Virtual Bus Voltage Control

The energy storage adjustment strategy of source and load storage in a DC microgrid is very important to the economic benefits of a power grid. Therefore, a multi-timescale energy storage optimization method for direct current (DC) microgrid source-load storage based on a virtual bus voltage control is studied. It uses a virtual damping compensation strategy to control the stability of virtual bus voltage and establishes a virtual energy storage model by combining different types of distributed capability units. The design of an optimization process for upper-level daily energy storage has the objective function of maximizing the economic benefits of microgrids to cope with unplanned fluctuations in power. A real-time energy-adjustment scheme for the lower level is introduced, and a real-time energy-adjustment scheme based on virtual energy storage for the short-term partition of the source-load storage is designed to improve the reliability of microgrid operations. The experiment shows that, in response to the constant amplitude oscillation of the power grid after a sudden increase in power, this method introduces a virtual damping compensation strategy at 20 s, which can stabilize the virtual bus voltage. From 00:00 to 09:00, the battery power remains at around 4 MW, and from 12:00 to 21:00, the battery exits the discharge state. The economic benefits from applying this method are significantly higher than before. This method can effectively adjust the source-load energy storage in real time. During peak electricity price periods, the SOC value of supercapacitors is below 0.4, and during normal electricity price periods, the SOC value of supercapacitors can reach up to 1.0, which can make the state of the charge value of supercapacitors meet economic requirements.

Cascaded Integral Minus Tilt Integral Derivative With Filter for Frequency Stabilization of V2G/G2V Enabled Hybrid Microgrid

ABSTRACTRenewable generation plays an important part in today's power system. With the inclusion of the inverter interfaced renewable energy sources (RESs) into a microgrid, the total system inertia decreases and it leads to increased frequency deviation in presence of a disturbance. This paper proposes a cascaded Integral Minus Tilt Integral Derivative with Filter (I–TDN)‐Proportional‐Integral (PI), [(I‐TDN)‐PI] controller for frequency stabilization of a hybrid microgrid in presence of electric vehicles (EV). The microgrid model includes reheated thermal power plant with high degree of non‐linear system such as inverter based RESs like photovoltaic and wind generation systems. A diesel engine generator is incorporated for load frequency control during perturbation in the system frequency. Virtual inertia controller (VIC) with inverter based energy storage system (ESS) is commonly used to improve system inertia and frequency stability of the microgrid. In addition to the ESS, this paper proposes inclusion of the EVs in this VIC. The optimal gains of the proposed cascaded I‐TDN‐PI controller are determined using Mountain Gazelle Optimizer (MGO), a modern metaheuristic optimization algorithm. Sensitivity of the proposed controller is investigated in presence of system nonlinearities, load perturbations, time delay, system parameter variation and RES power fluctuations. The simulation results justify the robustness of the proposed control structure for frequency stabilization of the microgrid.

Frequency shift caused by a magnetic field and light intensity inhomogeneity in an optically detected clock

We present a novel, to the best of our knowledge, frequency shift mechanism in the optically detected atomic clock. This frequency shift is analogous to the light shift that is associated with a detecting light power. However, this shift arises from the inhomogeneity of the magnetic field (C-field) and the detecting light intensity. We call this shift the “pseudo-light shift” (p-LS). This shift allows the correlation between the clock output frequency and the detecting light power to switch between positive and negative, depending on the magnetic field. The mechanism is described and experimentally validated in our cesium beam clock through two experiments. The study of this frequency shift can enhance the accuracy of light shift assessments in atom–laser interaction systems and suppress long-term stability deterioration caused by the light power fluctuation.

Multi‐timescale optimal scheduling of microgrids for generating new energy output scenarios based on correction error sampling intervals

AbstractMicrogrid can realize energy saving and emission reduction and multi‐energy complementation, but the fluctuation of renewable energy output and the error of day‐ahead scheduling will threaten the stability of microgrid operation. For this reason, this article proposes a microgrid multi‐timescale optimal scheduling method based on new energy output scenario generation. First, the microgrid framework of this article is introduced, and an energy cycle emission reduction model taking into account electricity‐to‐gas conversion is designed; second, a new energy prediction error model is established based on the prediction box and Gaussian hybrid model, and the scenario of wind and photovoltaic power generation is generated by correcting the sampling intervals for error sampling; and then, based on the day‐ahead scheduling plan, an intraday cooling, heating and electricity two‐layer rolling optimization model is established to correct the day‐ahead scenario. Finally, the example analysis shows that the cyclic emission reduction model can realize the recycling of resources, reduce the fuel cost and carbon emission, and the generation of scenarios for wind power can smooth out the fluctuation of new energy power, which, together with the intra‐day two‐layer rolling optimization, can reduce the day‐ahead scheduling error and improve the stability of microgrid operation.

Single-longitudinal-mode self-seeded Brillouin fiber laser with an ultra-narrow linewidth achieved utilizing a triple-ring resonator

What we believe to be a novel single longitudinal mode (SLM) triple-ring (T-R) self-seeded Brillouin fiber laser (BFL) featuring outstanding stability, an ultra-narrow linewidth, and a high optical signal-to-noise ratio (OSNR) is proposed and experimentally investigated in this study. The key innovation in this design is eliminating the need for an additional costly ultra-narrow linewidth pump source typically required in conventional BFL. Instead, the laser preferentially excites stimulated Brillouin scattering (SBS) in the fiber through the self-seeded cavity mode dominant in the cavity. This approach generates Brillouin stokes and leverages the Vernier effect of the T-R resonator structure to suppress multimode oscillations, ensuring the generation of a Brillouin laser with an ultra-narrow linewidth and enabling SLM operation. The experimental results show that with the output power of 980-nm LD fixed at 400 mw, the OSNR of the self-seeded BFL spectrum reaches 54 dB, and the side mode suppression ratio (SMSR) is 22 dB. The -3 dB linewidth of the self-seeded BFL can be measured by the heterodyne beat frequency method at 30 Hz, and the output power and wavelength fluctuations are lower than 1.318 dB and ±0.007 nm, respectively, during the sixty minutes observation period. Additionally, the wavelength of the self-seeded BFL can be flexibly tuned within the range of 1560 – 1575 nm. This innovative approach demonstrates significant theoretical and practical implications for the development of low-cost, high-performance BFL systems compared to traditional BFL methods.

Hydrogen production efficiency enhancement for alkaline water electrolyzers operating at varying temperature via an adaptive multi-mode control

The low-load efficiency performance of alkaline water electrolyzers (AWEs) is poor so its operation range is limited. It is unfeasible for AWEs to follow the fluctuant renewable energy sources (RESs). Besides, the power fluctuation will lead to the electrolyzer temperature variation. The efficiency performance is negatively influenced. Focusing on these problems, an efficiency enhancement control strategy for AWEs operating at varying temperature is introduced in this paper. First, the efficiency model of AWEs is established. Then, a multi-mode adaptive control strategy is proposed to improve the hydrogen production efficiency of AWEs. Based on the U–I curves of AWEs, parameter identification method is used to obtain the key parameters of proposed efficiency model. Finally, the feasibility of the control strategy is experimentally validated on a 10 kW AWE. The experimental outcome shows that by applying the proposed method, the low-load hydrogen production efficiency of AWEs can be improved at different temperatures. At 15% rated load, the electrolyzer efficiency increases from 21.54% to 42.73% at 80°C. The operation range of the electrolyzer can be extended from 30% to 100%–21%∼100% of rated load at 80°C.© 2024 The Authors. Published by Elsevier Ltd.

Current Compensation for Faulted Grid-Connected PV Arrays Using a Modified Voltage-Fed Quasi-Z-Source Inverter

Large-scale photovoltaic (PV) systems are being widely deployed to meet global environmental goals and renewable energy targets. Advances in PV technology have driven investment in the electric sector. However, as the size of PV arrays grows, more obstacles and challenges emerge. The primary obstacles are the occurrence of direct current (DC) faults and shading in a large array of PV panels, where any malfunction in a single panel can have a detrimental impact on the overall output power of the entire series-connected PV string and therefore the PV array. Due to the abrupt and frequent fluctuations in power, beside the low-PV systems’ moment of inertia, various technical problems may arise at the point of common coupling (PCC) of grid-connected PV generations, such as frequency and voltage stability, power efficiency, voltage sag, harmonic distortion, and other power quality factors. The majority of the suggested solutions were deficient in several crucial transient operating features and cost feasibility; therefore, this paper introduces a novel power electronic DC–DC converter that seeks to mitigate these effects by compensating for the decrease in current on the DC side of the system. The suggested solution was derived from the dual-source voltage-fed quasi-Z-source inverter (VF-qZSI), where the PV generation power can be supported by an energy storage element. This paper also presents the system architecture and the corresponding power switching control. The feasibility of the proposed method is investigated with real field data and the PSCAD simulation platform during all possible weather conditions and array faults. The results demonstrate the feasibility and capability of the proposed scheme, which contributes in suppressing the peak of the transient power-to-time variation (dP/dt) by 72% and reducing its normalized root-mean-square error by about 38%, with an AC current total harmonic distortion (THD) of only 1.04%.

Wavelength-Switchable 2 μm Single-Longitudinal-Mode Thulium-Doped Fiber Laser Based on Dual-Active Cavity and DLTCTR

A thulium-doped fiber laser (TDFL) with a dual-active cavity and a directly linked three-coupler triple-ring filter is designed and demonstrated. Its operational principle is analyzed, and a corresponding experimental setup is built. Eleven single-wavelength laser outputs with a single-longitudinal-mode (SLM) output near 2 μm are obtained. The laser output covers a wavelength range from 1933.95 nm to 1971.76 nm, with a continuous switchable output range of 37.81 nm and a minimum center wavelength interval of 0.22 nm. The optical signal-to-noise ratio (OSNR) of the output laser within the tuning range is >48.53 dB, and its maximum OSNR is 70.24 dB. The minimum wavelength fluctuation is 0.03 nm, and the power fluctuation is between 0.15 and 2.61 dB. A single wavelength with a center wavelength of 1933.95 nm is monitored for 75 min, and the radio-frequency spectrum is scanned 27 times within the frequency range of 0 to 400 MHz. The results demonstrate that the TDFL can operate continuously and stably in an SLM state. The linewidth and linewidth fluctuation of the TDFL are measured, and the minimum linewidth, corresponding to a measurement time of 0.001 s, is 65.14 kHz. The experimental results show that the proposed TDFL has a high OSNR and excellent wavelength-switching ability, and its SLM operation is very stable.

Innovative fuzzy logic type 3 controller for transient and maximum power point tracking in hydrogen fuel cells

This study introduces an advanced Fuzzy Logic Type 3 (FLT3) controller for Proton Exchange Membrane Fuel Cells (PEMFCs), aiming to optimize Maximum Power Point Tracking (MPPT) under dynamically varying temperature conditions. The FLT3 controller advances fuzzy logic control by incorporating an additional layer of uncertainty modelling, which enhances its ability to manage the inherent nonlinearities in PEMFC systems, such as temperature fluctuations and gas pressure variations. The controller is developed and validated through MATLAB/Simulink simulations, using a refined rule based on mechanism with finely tuned membership functions for precise adaptation to changing conditions. When compared to traditional Perturb and Observe (P&O) and Fuzzy Logic Type 2 (FLT2) controllers, the FLT3 controller demonstrates superior performance by achieving faster sitting times, minimizing power fluctuations, and maintaining operation closer to the nominal power point, particularly under transient conditions for hydrogen-based fuel cell. This innovative approach significantly improves the efficiency and stability of PEMFC systems, marking a substantial advancement in their operational management.

Optimization of marine hybrid power energy consumption

Abstract The energy and power system of the ship is the core of the ship, and the composite energy storage plays a great role in reducing the load power fluctuation of the ship, which effectively optimizes the energy efficiency index and reliability of the ship. [Objective] To better optimize the ship energy management system, a control model is established according to the characteristics of the energy system of hybrid electric ships. [Method] Energy consumption optimization is carried out by using a rule-based energy control strategy and energy control strategy based on equivalent fuel consumption minimum (ECMS). The dynamic control and strategy of the hybrid ship were optimized, and the data simulation and real ship application were carried out on the hybrid experiment platform. [Results] According to the data and results of the real ship application, the following results were shown: The daily fuel saving rate of the ECMS strategy is 14.6% in normal operating conditions and 13.3% in cruise operating conditions. [Conclusion] It has a great effect on the improvement of ship energy efficiency.

Optimizing Solar Power Generation and Integration in Automotive Systems Through IoT

Objective: This study presents an Internet of Things (IoT)- based system with edge intelligence that predicts power production with over 98% accuracy and monitors substations and smart solar installations, ensuring reliable power distribution in industrial IoT environments. This system enhances sustainability, safety, and energy management in smart buildings by reducing power fluctuations by 30% and improving decision-making, leading to a 95% reduction in energy management costs. Method: An IoT-enabled power monitoring system was implemented for smart solar panels and substations, incorporating edge intelligence for instantaneous prediction and decision-making. An IoT-enabled solar charging station was deployed for smart homes and Industry 4.0 applications. The cloud was used for analyzing sensor data, with a response time of less than 1 second. Findings: The proposed framework increased the efficiency and reliability of power production and distribution by 25% across commercial, residential, and industrial contexts. It significantly mitigated power fluctuations, reducing downtime by 40% and achieving a 95% cost reduction in energy management compared to traditional systems. IoT integration improved safety and sustainability metrics by 20% in smart buildings. Novelty: The framework integrates edge intelligence with IoT in smart solar systems and substations, providing a sophisticated control system that enhances power distribution decision-making. It facilitates real-time monitoring and prediction of power production with over 98% accuracy, emphasizing sustainability, safety, and energy management improvements of up to 30% in smart buildings. Keywords: IoT-based control system, Smart solar systems, Edge intelligence, Power substations, Load management, Energy sustainability

Data-based power management control for battery supercapacitor hybrid energy storage system in solar DC-microgrid.

This paper addresses the energy management control problem of solar power generation system by using the data-driven method. The battery-supercapacitor hybrid energy storage system is considered to smooth the power fluctuation. A new model-free control method is utilized in the stand-alone photovoltaic DC-microgrid to provide the power to meet the demand load, while guaranteeing the DC bus voltage is stable. Furthermore, the proposed data-based power management control strategy only needs I/O data. Numerical simulations with real data verify the effectiveness of the proposed method.

Fixed-Time Backstepping Sliding-Mode Control for Interleaved Boost Converter in DC Microgrids

Interleaved boost converters (IBCs) are commonly used as interface converters for DC microgrids (MGs) due to their high efficiency and low output ripple. However, the MGs system can easily become unstable due to the negative impedance characteristics of constant power load (CPL) and rapid power fluctuations. This paper proposes a fixed-time backstepping sliding-mode controller (FTBSMC) aimed at stabilizing the MGs system and achieving fixed-time tracking of the DC bus voltage. Firstly, the fixed-time disturbance observer (FxTDO) estimates the load disturbance at a fixed time, which improves the fast disturbance resistance of the system. Then, based on the dis-turbance estimation, the FTBSMC is designed, which combines the fast dynamic response of the sliding-mode control with the global stability of the backstepping control, avoiding the singularity problem of the conventional sliding-mode control. In addition, a first-order nonlinear filter is employed to avoid the direct differentiation of conventional backstepping control and at the same time to ensure global fixed-time stability. The fixed-time convergence of the proposed FTBSMC is rigorously demonstrated by using Lyapunov stability analysis. Finally, the FTBSMC proposed is verified by simulation and experiment in terms of faster dynamic response and stronger robustness.

Collaborative Optimization of Multi-regional Integrated Energy System Based on Improved Beluga Whale Optimization Algorithm

With the installed capacity of the renewable energy power generation is growing at a high speed, a large number of the renewable energy is connected to the grid, the energy problem has been solved to a large extent, but the ensuing problems can not be ignored, the first is the consumption of the renewable energy, which is followed by the stability problem of the power system, and a multi-regional integrated energy system (MRIES) is constructed to solve the problem. In view of the wind power uncertainty, the absorption treatment is carried out by the equipment layer and the optimization layer respectively. A hybrid energy storage system (HESS) is introduced in the equipment layer to suppress the influence of the wind power uncertainty on the system stability. A combination of the convolutional filtering algorithm, the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise algorithm and the fuzzy control algorithm is introduced in the optimization layer to develop the charging and discharging strategy of the HESS. With the strategy, the impact of the electric power fluctuations on the power system during the optimization process can be reduced largely. Then, on the basis of fully considering the energy coupling in different equipments, a collaborative optimization model of the MRIES is constructed. And the integrated demand response model considering the time-of-use electric price is introduced in the load side. Finally, the improved Beluga optimization(IBWO) algorithm is developed to optimize the model. The optimization results show that the IBWO algorithm plays a good optimization effect both in the participation of energy supply equipments and the economy, plays a collaborative optimization role in the MRIES and ensures the stability of the whole power system.

Digital stabilization of an I/Q modulator in the carrier suppressed single-sideband mode for atom interferometry

We present an all-digital method for stabilizing the phase biases in an electro-optic I/Q modulator for carrier-suppressed single-sideband (CS-SSB) modulation. Using programmable logic on the Red Pitaya STEMlab 125-14 platform, we digitally generate and demodulate an auxiliary radio-frequency tone whose beat with the optical carrier probes the I/Q modulator’s phase imbalances. We implement a multiple-input, multiple-output integral feedback controller that accounts for unavoidable cross-couplings in the phase biases to lock the error signals at exactly zero, where optical power fluctuations have no impact on phase stability. We demonstrate >23dB suppression of the optical carrier relative to the desired sideband at +3.4GHz over a period of 15 h and over temperature variations of 20°C.

Adaptive Variable Universe Fuzzy Droop Control Based on a Novel Multi-Strategy Harris Hawk Optimization Algorithm for a Direct Current Microgrid with Hybrid Energy Storage

In the off-grid photovoltaic DC microgrid, traditional droop control encounters challenges in effectively adjusting the droop coefficient in response to varying power fluctuation frequencies, which can be influenced by factors such as line impedance. This paper introduces a novel Multi-strategy Harris Hawk Optimization Algorithm (MHHO) that integrates variable universe fuzzy control theory with droop control to develop an adaptive variable universe fuzzy droop control strategy. The algorithm employs Fuch mapping to evenly distribute the initial population across the solution space and incorporates logarithmic spiral and improved adaptive weight strategies during both the exploration and exploitation phases, enhancing its ability to escape local optima. A comparative analysis against five classical meta-heuristic algorithms on the CEC2017 benchmarks demonstrates the superior performance of the proposed algorithm. Ultimately, the adaptive variable universe fuzzy droop control based on MHHO dynamically optimizes the droop coefficient to mitigate the negative impact of internal system factors and achieve a balanced power distribution between the battery and super-capacitor in the DC microgrid. Through MATLAB/Simulink simulations, it is demonstrated that the proposed adaptive variable universe fuzzy droop control strategy based on MHHO can limit the fluctuation range of bus voltage within ±0.75%, enhance the robustness and stability of the system, and optimize the charge and discharge performance of the energy storage unit.

Study on power characteristics of wind turbine on the Loess Plateau terrain based on wind tunnel experiment

In order to investigate the impact of the flow field on wind turbine power in northwest China’s Loess Plateau, a wind tunnel experiment was conducted using a self-designed model that simulated the actual terrain. By comparing experiments utilizing an ideal mountain model under varying incoming wind speeds, it was revealed that the Loess Plateau terrain resulted in an increased inflow wind speed for the wind turbine. This higher inflow wind speed led to an approximate 5% increase in output power but also caused about a 6.1% rise in power fluctuations. Through analysis of the power spectrum of the output, it was discovered that turbulence below the decoupling frequency strongly modulates the output power of the wind turbine. This study also provided insights into spatial scale ranges where incoming flow turbulence structures can modulate output power, ranging from approximately 0.3 times to 5 times the diameter of rotor blades.

Overview of Key Technologies for Wind Energy Applications

Due to the pursuit of economic benefits and the development and damage to the environment, the need to develop new energy sources is increasing day by day. as one of the earliest and most mature new energy generation methods, wind power has received much attention. However, wind power generation system is constrained seriously by the environment because of the random fluctuation of wind power itself. It is easy to cause problems such as low power generation efficiency and fast device loss due to the influence of wind instability. At the same time, it is difficult to store and connect electric energy to the electricity grid.