Sudden Load Changes Research Articles

Voltage and frequency control of solar – battery – diesel based islanded microgrid

Abstract Islanded microgrids with low-inertia distributed energy resources (DERs) are prone to frequency fluctuations. With the increasing integration of DERs in microgrids, the complexity of control and stability has also increased. Moreover, the integration of DERs into microgrids may result in a power imbalance between energy supply and demand during sudden changes in load or energy generation. This can cause frequency variations in the microgrid, which could have disastrous consequences such as equipment damage or even blackouts. This paper proposes a control strategy to ensure the efficient operation of an islanded hybrid microgrid consisting of a PV generator, battery energy storage system (BESS), and emergency diesel generator. According to Energy Exchange Model proposed in this paper, the hybrid system presented operates independently without being connected to the electrical grid, where the PV system and BESS act as the main energy sources, while the emergency diesel generator provides active power backup with voltage and frequency regulation. The novel in this paper is also that DER aids in frequency regulation during active power transients by delivering and absorbing active power in accordance with the inverter's suggested P droop control strategy. In this way inverter droop control decreases system frequency nadir emulating so called “synthetic inertia”. To design both the islanded hybrid system and the proposed control strategy, the MATLAB/Simulink environment is utilized. Based on the results, it can be concluded that the analyzed microgrid system is capable of maintaining stability and operating efficiently in a range of operating conditions.

Modified Chameleon Swarm Optimization Algorithm to Improve the Power System Stability

Power system stability has been difficult due to the occurrence of low frequency oscillation in the modern power system. Oscillation is mainly due to sudden changes of frequency, load, voltage, active power and reactive power. In this paper we provide a damping solution to oscillate the low frequency by using modified chameleon optimization algorithm. Damping performance and stability analysis of system is done by proposed modified chameleon Swarm Algorithm compared with conventional chameleon Swarm algorithm and Genetic algorithm with different operating condition in terms of Real power, Reactive power and Load disturbances. The comparative results confirmed that the proposed controller exhibit higher damping ratio, and better damping of deviations in speed and power angle to improve the stability of the system.

Enhancing dynamic security assessment in converter dominated distribution networks through digital twin-based small signal stability analysis

Abstract As renewable energy sources are increasingly integrated and distributed in the power system, the number of converters in the grid is growing. This leads to more and more dynamics in the distribution networks and may result in more frequent disturbances such as voltage fluctuations, power quality problems, etc. To prevent possible threats to the security and stability of the network due to the above issues, Dynamic Security Assessment (DSA) is necessary for a distribution network to ensure its safe and reliable operation. In this work, an innovative approach to DSA using Digital Twin (DT) technology, with a primary focus on small signal stability (SSS) analysis using an eigenvalue method is proposed. The DT of the distribution network is first constructed by incorporating machine learning algorithms and updated in real-time using data from sensors and SCADA systems to accurately represent the behaviour of the physical system. The DT will be used to continuously monitor and assess the stability of the distribution network characterised by the presence of power electronic converters. The DSA then uses SSS to analyse network behaviour under different operating conditions and identify potential risks or disturbances. This can include assessing the impact of sudden changes in load or renewable energy output, detecting potential faults or equipment failures, and identifying potential instabilities in the power system. Numerical case studies are used to verify the viability of the proposed approach. As a result, by integrating a DT into the DSA process for converter-based distribution networks, operators can improve the accuracy and efficiency of their security measures, reduce the risk of outages, and increase the overall reliability of the system.

Research on Diesel Engine Speed Control Based on Improved Salp Algorithm

To better regulate the speed of diesel engines and optimize the speed overshoot and fast response, a speed control method combining the improved salp swarm algorithm (ISSA) with the proportional integral and differential (PID) controller was proposed. A real-time simulation model for a high-pressure common rail diesel engine was established. Addressing the challenges of the salp swarm algorithm (SSA), such as uneven population distribution and its tendency to become trapped in local optima, logistic-tent chaotic mapping, adaptive parameters was introduced, as well as adaptive dynamic inertia weights, elite strategy, and a dynamic inverse strategy. These enhancements bolstered the algorithm’s precision and efficiency in both global and local searches. Using the enhanced SSA, the parameters of the PID controller for the diesel engine model was optimized. The results indicated that the ISSA offers superior parameter identification precision, strengthening speed control stability. During sudden changes in speed and load, the overshoot decreased by an average of more than 30.3% and more than 8.6%, respectively. Moreover, the settling time decreased by an average of more than 0.76 s and 1.52 s, respectively, significantly enhancing the quality of diesel engine speed control.

Experimental research on cooling performances of radial expanding-channeled heat sinks applied for multiple heat sources

Intrinsic two-phase flow instability using multiple parallel boiling channels hinders the actual implementation of flow boiling cooling techniques in high heat flux and multiple heat source applications. Recently, we proposed a radial expanding-channeled heat sink (ECHS) to realize a high two-phase flow stability under extreme conditions. In the present work, the cooling performances of two heat sinks connected in series or in parallel were investigated with the heat load adjusted individually. The results indicated that when two ECHS were connected in parallel, the inlet flowrate was evenly distributed into the two heat sinks, and their heat transfer performance was identical. At a sudden change in the heat load of one path, the flowrate of the other heat sink may change by 10% to 30% without inducing flow instability or heat deterioration. The thermal resistance for both heat sinks was lower than 0.025 °C/W, and no instability or dry-out was observed as long as the initial flowrate was larger than 0.28 kg/min. With the proposed ECHS, multiple heat sources such as central processing unit, server, rack, etc. can be connected in series or in parallel to construct an integrated cooling system for large-scale data center applications.

DESIGN OF CLOSED LOOP MULTIPORT DC DC CONVERTER

In recent years, there has been lots of emphasis put on the development of renewable energy. While considerable improvement on renewable energy has been made, there are some inherent limitations for these renewable energies The Closed-Loop Multiport DC-DC Converter with Adaptive Sliding Mode Control (ASMC) is difficult in power electronics system designed to efficiently manage and control energy flow between multiple energy sources and loads in various applications, including renewable energy integration, electric vehicles, and microgrids. This paper provides an overview of the key features and benefits of this innovative converter system. Multiport DC-DC converters have gained significant attention due to their ability to interface multiple energy sources, such as solar panels and batteries with different voltage levels and power ratings, providing a versatile platform for energy management. The ASMC controller enhances the converter's performance by dynamically adjusting the control parameters based on system conditions and load requirements, thereby improving efficiency and reliability .The ASMC employs a sliding mode control strategy, a robust and adaptable control method, which ensures that the converter operates effectively under various operating conditions, including rapid changes in load and source characteristics. This control technique offers inherent advantages, such as fast transient response and reduced sensitivity to parameter variations, contributing to superior system performance. The ASMC controller optimizes power conversion by minimizing switching losses and ensuring that the converter operates close to its peak efficiency. The controller continuously adapts to changes in input voltage, output voltage, and load conditions, ensuring stable and reliable operation even in dynamic environments. The sliding mode control strategy enables rapid response to sudden load changes, making it suitable for applications with varying power demands. Key Words: DC-DC converter, Sliding-mode control, Battery, Solar PV.

Improving the Synchronous Stability Control Strategy of Virtual Synchronous Generators

The microgrid dominated by new energy has small inertia and weak damping, while a virtual synchronous generator (VSG) is an effective means to enhance inertia and damping to improve the stability of the microgrid. However, it also introduces power angle oscillation problems similar to that of synchronous machines. This paper is based on the current inner loop and voltage outer loop control of the three-phase LCL inverter. It introduces the virtual inertia and damping coefficient of the virtual synchronous generator, achieving a good grid connection effect. While a significant change in active power occurs, the system can lose synchronization and stability. Therefore, the paper proposes an improved synchronization stability control strategy for virtual synchronous generators by introducing a frequency-proportional integral feed-forward link in the reactive power loop to suppress power angle oscillation and improve system synchronization stability. Theoretical analysis was conducted on the synchronous stability of the improved control strategy in case of sudden changes in active power load. The effectiveness of the strategy was verified through simulation.

Sliding-mode control for boost converters under voltage and load variations

<p><span lang="EN-US">Boost converters are employed in DC motors, switch-mode power supplies, and other applications. Practical implementation difficulties, reliance on variable-frequency units, and delayed dynamic responses to changes in load and voltage are the main drawbacks of different control methods for the boost converter. In this paper, two techniques were proposed with the target of controlling the boost converter to improve the efficiency of the converter's performance. The two techniques used in this paper depended on fixed-frequency mode instead of variable-frequency mode because of the demerits of the latter factor. The first technique is the sliding-mode control for the AC-DC converter to achieve power factor correction and reduce the harmonic ratio significantly while regulating the output voltage. This technique was used for the DC-DC converter to obtain a rapid dynamic response to control sudden or considerable changes in loads or input voltages with a regulated output voltage. Moreover, the two-loop cascade control is the second proposed technique for the DC-DC converter to achieve an excellent dynamic response under step loads or input voltage variations with an excellently regulated output voltage. Re-simulation results validated the proposed design approach and illustrated the proposed controller's robustness and faster response time.</span></p>

Forecasting the Dynamic Response of Rotating Machinery under Sudden Load Changes

This paper analyzes vibration data that shows sudden amplitude changes due to non-stationary load conditions. The data were recorded in a wind turbine that operated under gusty winds and showed high peaks during short periods. Data were analyzed with the auto-regressive integrated moving average (ARIMA) algorithm, and the results were compared to the exponential forecasting method. Other methods have been applied for forecasting vibration data, but the simplicity of this method makes it suitable for rotating machinery with high variable loading conditions. The analysis of the method’s parameters is included in this paper, and the results showed that the optimum configuration depends on the data variations and the existence of significant trends. Forecasting vibration data is challenging; it depends on the source data quality, the preprocessing algorithms, and the deterioration of the mechanical elements. Predictions become less accurate when the machine operates under sudden changes, and evaluating damaging effects caused by the sudden event is difficult to estimate.

Experiment and analysis of drop-weight damping control of MR semi-active impact resistance-based hydraulic actuator

The impact vibration caused by sudden changes in the external load of hydraulic actuators reduces the service life of hydraulic components and limits the high-precision applications of hydraulic actuators. Therefore, to improve the underdamped characteristics and impact resistance of valve-controlled cylinder systems, a semi-active impact resistance control of hydraulic actuator based on magnetorheological damper (MRD) is proposed. Firstly, based on the shear force characteristics of magnetorheological fluid, a multi-stage flow channel MRD is designed, which is connected in series with the hydraulic actuator to form a hydraulic damping actuator (HDA). Meanwhile, based on the mechanical experimental data, the parameters of MRD dynamic model are identified to ensure the accuracy of MRD output force. Secondly, a drop weight impact model is established, and a sliding mode controller which can track the command current in real time is designed, so as to realize the resistance force coupling between the MRD and the hydraulic actuator for improving the impact resistance control effect. Then the dynamic performance test and impact resistance simulation program are established to verify the excellent dynamic performance and impact resistance effect of the HDA with the sliding mode control. Finally, the drop weight impact experimental platform is built. The experimental results show that under the impact with a height of 200 mm, the dynamic offset of the HDA is only −1.25 mm, and the time to return to the original position is 0.08 s, which validate the excellent performance of the proposed scheme in improving the underdamped characteristics of the valve-controlled cylinder system and the dynamic response performance of the hydraulic actuator.

Inertia control method of direct drive permanent magnet wind turbine under high wind power permeability

Direct-drive permanent magnet wind turbine has high power generation efficiency, especially in low wind speed environment, and is widely used for wind power generation. Direct-driven permanent magnet wind turbines show no inertia response to the system through the grid connection of full-power converters, resulting in increased frequency fluctuation, poor response effect and reduced stability time of the system under sudden load and sudden wind speed conditions. Based on this, an inertia control method of direct-drive permanent magnet wind turbine under high wind power penetration is proposed, and the model of direct-drive permanent magnet wind turbine is built by designing functional modules to improve the synchronous control effect under high wind power penetration. The vector control calculation method is used to design the virtual inertia control parameters, and the decoupling quantity is introduced to decouple the parameters with filter inductance, so as to improve the supporting capacity of power grid frequency fluctuation. The simulation results show that the proposed method has a fast frequency response under sudden load change, and it drops to the lowest value of 49.16 Hz at 12.14 s. Under the condition of sudden change of wind speed, the system frequency rises to the highest value of 50.38 Hz at 12.94 s. It is proved that the proposed method has a certain suppression effect on the amplitude of frequency change, effectively shortens the time for the system frequency to return to steady state, and thus has more advantages.

Improved power sharing in inverter based microgrid using multi-objective optimization

The voltage-source inverter has an important role in electrical power sharing in microgrids, although, it requires a tight control and optimization technique to enhance performance and to improve power sharing. A sudden load change is a common phenomenon which may lead to fluctuations in the terminal voltages and load currents and eventually the system might become unstable. The PI control law represents one of the preferred control algorithms in industry, meanwhile its parameters need to be tuned to ensure its superiority. Two multi-objective optimization algorithms, the Genetic Algorithm, and the Water Cycle Algorithm, are proposed in this article to tune the controller gains. A microgrid consisting of two-parallel inverters is used to investigate the performance of the proposed tuning techniques where the system is analyzed in the dq-frame and the Space Vector Pulse Width Modulation was undertaken as a switching technique. MATLAB/SIMULINK simulations demonstrated the improved performance of the proposed approach.

Model Predictive Evolutionary Temperature Control via Neural-Network-Based Digital Twins

In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digital twin of the system, facilitating a robust response to unknown disturbances. During inference, the trained digital twin is utilized to virtually test alternative control actions for a multi-objective optimization task associated with each control action. Subsequently, the best policy is applied to the system. To evaluate the proposed model predictive control pipeline, experiments are conducted on a multi-mode heat transfer test rig. The objective is to achieve homogeneous cooling over the surface, minimizing the occurrence of hot spots and energy consumption. The measured variable vector comprises high dimensional infrared camera measurements arranged as a sequence (655,360 inputs), while the control variable includes power settings for fans responsible for convective cooling (3 outputs). Disturbances are induced by randomly altering the local heat loads. The findings reveal that by utilizing an evolutionary algorithm on measured data, a population of control laws can be effectively learned in the virtual space. This empowers the system to deliver robust performance. Significantly, the digital twin-assisted, population-based model predictive control (MPC) pipeline emerges as a superior approach compared to individual control models, especially when facing sudden and random changes in local heat loads. Leveraging the digital twin to virtually test alternative control policies leads to substantial improvements in the controller’s performance, even with limited training data.

A Fast Diagnosis Strategy for Inverter Open-Circuit Faults Based on the Current Path of Brushless DC Motors

The proposed method in this paper aims to diagnose open-circuit faults quickly and accurately in brushless DC motor inverters to ensure the motors' safe operation. The technique utilizes a topology for current path detection and a method based on current path change to identify and locate faults in the inverter. The proposed method improves the speed of fault diagnosis and is not affected by sudden changes in load. Additionally, it allows for prompt handling of faults and ensures reliable motor operation. The effectiveness of this method is validated through experimental results.

Prediction Model of Horizontal Drilling Trajectory of Anti-collision Drilling Robot

The horizontal drilling trajectory of the anti-collision drilling robot is taken as the research object and its drilling trajectory prediction model is established in this paper. The drilling trajectory is affected by many factors, such as the structural parameters of the auger, the drill bit, the drilling process parameters, and the geological characteristics of the coal seam, etc., which results in the existence of multi-level time-scale structure and localization characteristics of the drilling trajectory data in the time domain. The wavelet analysis method can decompose the relatively complex non-stationary time series problem into low-frequency decomposition signals representing trend items and high-frequency decomposition signals representing periodicity and randomness. It can not only predict the main trend of drilling trajectory changes but also effectively predict sudden load changes and short-term changes. Based on this, a new prediction method is proposed in this paper. Firstly, the data is decomposed into relatively simple component signals using wavelet decomposition technology, then the prediction models are established according to the characteristics of each component signal. Finally, the drilling trajectory prediction model is established by synthesizing the prediction results. The anti-impact drilling robot drilling test bed is set up and the drilling experiments are carried out to verify the effectiveness of the model, which can lay the foundation for the anti-impact drilling robot drilling deflection control.

Overcoming voltage fluctuation in electric vehicles by considering Al electrolytic capacitor-based voltage stabilizer

Battery pack used in electrical vehicles (EVs) have developed fastly nowadays and are important due to its capability to stores electric charge. However, it is still found that there is an electrical voltage fluctuations due to sudden load changes or faults in the power system. To overcome this problem, the conventional strategy focuses on using voltage stabilizer with inductor-capacitor resonant circuits, leaving the problem of using capacitors at cryogenic temperatures. Herewith, we design a vehicle automatic voltage stabilizer (VAVS) operating at room temperature. The VAVS consists of nine main components, including resistors, capacitors, transistors, and diodes arranged with a specific composition to stabilize the voltage. By considering Al electrolytic capacitor, type of diode, resistor, and transistor, the VAVS device stabilizes the input voltage from 10-15V to obtain an output voltage of 12V. Then, by varying the engine rotation speed of vehicle, VAVS applied in vehicle battery supplies a constant voltage of about 12.1 V. The lowest line regulation analysis reveals a regulated voltage fluctuation of 0.17%/V. Our result shows that VAVS design works at room temperature, overcomes the voltage fluctuation and complies with the standard regulation of voltage stabilizers.

Model predictive temperature control of a closed-loop spray cooling system

A dynamic model of a closed-loop spray cooling system was proposed, and a model predictive temperature control algorithm was presented. The presented algorithm could quantitively estimate sudden changes in heat load, and then plan an optimized control path along which the temperature trajectory was numerically predicted to be the most stable. Then, the presented algorithm was integrated into a closed-loop spray cooling system, and its control performance was numerically studied. The results showed that, following a 20 W downward step change in heat load, the temperature was re-stabilized in 4 s, with its oscillation less than 0.14 K. Under identical conditions, the presented algorithm outperformed PID in terms of temperature stability, with its peak time shorter by 25–55%, settling time shorter by 38–51%, and average temperature offset smaller by 50–60%. This advantage was mainly because the presented algorithm compensated for hydraulic and thermal lags, two sources of control nonlinearity, by excessive regulation in advance. Unexpectedly, temperature overshoots of the presented algorithm and PID did not differ significantly, seemingly due to the algorithm-inherent estimation lag. From a system design perspective, the length of pump pipeline should be as short as possible, which proved to help reduce overshoot and settling time. Similarly, addition in heat load’s mass also helped reduce overshoot, but would result in an unfavorable long settling time, and vice versa. The simulation results were validated by experimental data, with error less than 10%.

A Comparative Study of Static VAR Systems for ImprovingVoltage Stability in Expansion of Mining Projects with Gearless Motor Drives

In the next decade, the demand for copper is expected to grow by 25%, posing a challenge for mining facilities to increase their production by opening new mines or upgrading existing ones. To optimize the electrical infrastructure of mining facilities, the integration of flexible AC transmission systems (FACTSs) can be instrumental in mitigating voltage stability issues that may arise during the installation of new gearless motor drives (GMDs). The purpose of this paper is to conduct a comparative analysis of the dynamic performance of static VAR systems (SVSs) as a means of enhancing voltage stability in mining expansion projects, particularly in the context of the integration of new GMDs into the system. This paper presents a case study of an existing three crushing-line mine configuration that has been upgraded with two new GMD systems. The primary contribution of this research is a comprehensive methodology designed to enhance the stability of a mining system through the integration of an SVS, which includes the sizing of the SVS system, an analysis of costs, as well as a determination of the required installation surface and optimal placement of the SVS within the system. The simulation results conclusively demonstrate the effectiveness of the SVS systems in reducing the voltage drop by 2% upon activation of new GMDs, as well as mitigating the adverse impact of transient disturbances on the system. Specifically, the first oscillation voltage peak value is improved by 3.5%, following a three-phase short circuit of 1 second duration, while overvoltage is reduced by 1% in response to sudden load changes. When compared with the system without an installed SVS, these findings highlight the significant advantages and benefits of integrating SVSs into mining operations.

Power Control Strategy for a Ferry’s DC Power System Using Supercapacitors

Integrated power systems are gaining popularity in the field of power systems and DC integrated power systems are considered promising for electric propulsion ships due to their simple grid topology, low fuel consumption, and easy access to new energy sources. However, the dynamic response characteristics of the power plant can be compromised when a variable speed generator is used in a DC power system, despite achieving energy savings. In this research, we investigate the power control strategy of a specific type of a ferry’s DC power plant. We establish a mathematical model and a Matlab/Simulink-based simulation model to analyze the performance of the proposed strategy. The research utilizes the fast charging and discharging advantages of supercapacitor storage devices to compensate for the dynamic impact delay of the power output when using the variable speed generator set. Additionally, an improved DC bus voltage droop control method that incorporates voltage compensation is proposed to mitigate problems related to large bus voltage fluctuations under sudden load change conditions, enabling better load distribution between different power sources. The simulation results confirm the effectiveness of the proposed strategy in optimizing the speed-seeking method of the variable speed diesel engine sets matching with the supercapacitor, and its positive impact on the dynamic performance of the propulsion system is demonstrated under variable load conditions resulting from ferry operations.

PERFORMANCE ANALYSIS AND SPEED CONTROL USING INDIRECT VECTOR CONTROLLED FOR INDUCTION MOTOR DRIVES

This paper presents the speed control scheme of an indirect vector-controlled induction motor (IM) drive. PWM controlling scheme is based on Voltage source inverter type space vector pulse width modulation (SVPWM) and the Conventional-PID controller or Fuzzy-PID controller is employed in closed-loop speed control. Decoupling of the stator current into torque and flux producing (d-q) current components model of an induction motor is involved in the indirect vector control. The torque component Iq current of an IM is developed by an intelligent-based Fuzzy PID controller. Based on settling time and dynamic response the performance of the Fuzzy Logic Controller is compared with that of the PID Controller to sudden load changes. It provides better control of motor torque with high dynamic performance. The simulated design is tested using various toolboxes in MATLAB. Simulation results of both controllers are presented for comparison.