Low Inertia Research Articles

Research on static voltage stability enhancement for new energy station based on grid-forming control strategy

The advent of novel power systems has given rise to a multitude of safety and stability concerns associated with the integration of emerging energy sources and power electronic equipment. The active support of the grid-forming control strategy represents an effective solution to the voltage and frequency stability issues associated with the weak damping and low inertia inherent to high-ratio new energy systems. Firstly, a static voltage stability index based on critical impedance is proposed for assessment of the static stability margin of a new energy grid-connected system, based on the static voltage stability theory of a traditional single-unit single-load system. Secondly, an analysis is conducted of the control principle of the grid-forming control converter and its impedance characteristics. In conclusion, a method for enhancing the static voltage stability margin of grid-connected new energy stations through parameter control of grid-forming converters is presented. The simulation verification of the single-feed and multi-feed systems demonstrates the efficacy and accuracy of the methodology presented in this study.

Controller design and experimental validation of walking for a musculoskeletal bipedal lower limb robot based on the spring-loaded inverted pendulum model

In the study of PAM (McKibben-type pneumatic artificial muscle)-driven bipedal robots, it is essential to investigate whether the intrinsic properties of the PAM contribute to achieving stable robot motion. Furthermore, it is crucial to determine if this contribution can be achieved through the interaction between the robot’s mechanical structure and the PAM. In previous research, a PAM-driven bipedal musculoskeletal robot was designed based on the principles of the spring-loaded inverted pendulum (SLIP) model. The robot features low leg inertia and concentrated mass near the hip joint. However, it is important to note that for this robot, only the design principles were based on the SLIP model, and no specialized controller was specifically designed based on the model. To address this issue, based on the characteristics of the developed robot, a PAM controller designed also based on the SLIP model is developed in this study. This model-based controller regulates ankle flexion PAM to adjust the direction of the ground reaction force during robot walking motion. The results indicate that the proposed controller effectively directs the leg ground reaction force towards the center of mass during walking.

The study of active support for energy storage system in system frequency regulation

Abstract As the penetration of new energy sources increases, the proportion of traditional energy units continues to decline, reducing the inertia and primary frequency regulation capability of the power system. Therefore, exploring the frequency support capabilities of energy storage systems with low inertia is crucial. Based on this, this paper first proposes an active frequency support method for energy storage system based on a Voltage Source Virtual Synchronous Generator (VSG), aiming to enhance system inertia and reduce response delay. Based on this issue, a parameter tuning optimization selection model based on the Transient Search Optimization (TSO) algorithm is proposed to determine the optimal power output and best frequency regulation parameters for the energy storage system. Finally, the model proposed in this paper is applied to the IEEE 14-bus system to verify its effectiveness.

Application of a decision tree approach to predict energy consumption in lightweight buildings under subtropical climate

PurposeLightweight building systems have emerged as alternatives to reduce the high environmental impact of conventional masonry. However, in subtropical climates, the low thermal inertia of lightweight envelopes negatively affects energy performance. The purpose of this paper is to investigate the thermophysical parameters that influence heating and cooling energy consumption in lightweight residential buildings under subtropical climates and develop a model to predict these parameters using statistical and machine learning tools.Design/methodology/approachA database was created with computer simulation data on the energy performance of 2048 building conditions generated by factorial combination of 10 parameters. Sensitivity analysis was performed to identify which parameters contribute most to energy performance indicators. Subsequently, decision trees were created using a classification and regression tree (CART) algorithm to visualize parameters and improve energy performance indicators, particularly cooling energy consumption.FindingsLow thermal transmittance and ground contact are interesting strategies for low thermal capacity buildings. Furthermore, the findings showed that relying only on the most influential properties does not ensure good energy performance; rather, it is the adequate combination of envelope properties that leads to good energy efficiency. The tree developed by CART can be used as a guide to assist designers and researchers in the initial selection of building envelopes, demonstrating the impact of each choice on electrical energy consumption for indoor climate control.Originality/valueBy adopting a global approach to assess the thermal performance of lightweight buildings, this study makes a significant contribution to synthesizing the results of a complex and time-consuming methodology into a guide for optimizing envelope design decisions and directing efforts and resources toward efficient strategies.

Optimal Configuration Model for Large Capacity Synchronous Condenser Considering Transient Voltage Stability in Multiple UHV DC Receiving End Grids

In a multi-fed DC environment, the UHV DC recipient grid faces significant challenges related to DC phase shift failure and voltage instability due to the high AC/DC coupling strength and low system inertia level. While the new large-capacity synchronous condensers (SCs) can provide effective transient reactive power support, the associated investment and operation costs are high. Therefore, it is valuable to investigate the optimization of SC configuration at key nodes in the recipient grid in a scientific and rational manner. This study begins by qualitatively and quantitatively analyzing the dynamic characteristics of DC reactive power and induction motors under AC faults. The sub-transient and transient reactive power output model is established to describe the SC output characteristics, elucidating the coupling relationship between the SC’s reactive power output and the DC reactive power demand at different time scales. Subsequently, a critical stabilized voltage index for dynamic loads is defined, and the SC’s reactive power compensation target is quantitatively calculated across different time scales, revealing the impact of transient changes in DC reactive power on the transient voltage stability of the multi-fed DC environment with dynamic load integration. Finally, an optimal configuration model for the large-capacity SC is proposed under the critical stability constraint of dynamic loads to maximize the SC’s reactive power support capability at the lowest economic cost. The proposed model is validated in a multi-fed DC area, demonstrating that the optimal configuration scheme effectively addresses issues related to DC phase shift failures and voltage instability resulting from AC bus voltage drops.

Development of Dual-Arm Human Companion Robots That Can Dance.

As gestures play an important role in human communication, there have been a number of service robots equipped with a pair of human-like arms for gesture-based human-robot interactions. However, the arms of most human companion robots are limited to slow and simple gestures due to the low maximum velocity of the arm actuators. In this work, we present the JF-2 robot, a mobile home service robot equipped with a pair of torque-controlled anthropomorphic arms. Thanks to the low inertia design of the arm, responsive Quasi-Direct Drive (QDD) actuators, and active compliant control of the joints, the robot can replicate fast human dance motions while being safe in the environment. In addition to the JF-2 robot, we also present the JF-mini robot, a scaled-down, low-cost version of the JF-2 robot mainly targeted for commercial use at kindergarten and childcare facilities. The suggested system is validated by performing three experiments, a safety test, teaching children how to dance along to the music, and bringing a requested item to a human subject.

Analysis of Thermal Isotropy of Parallelepiped Shape of Bronze Samples for Mechanical Engineering Applications

Objective: The need to find out whether the specimens are ‘thermally thin’ or not is the basis for applying the law of conservation of energy or the Fourier differential equation of heat conduction in finding the time dependence of the specimen temperature. The aim of this study is to find out the thermal field distribution in a parallelepiped shaped bronze specimen and to verify the Bio number. Methods: A number of external variables make it difficult to maintain a monotonic change in sample temperature during the ‘heating’ stage. These factors led to the use of the cooling method to study tiny samples with low inertia of the thermal process. We used the cooling method to experimentally verify the isotropy of the thermal field in the sample and to study the kinetics of cooling relative to the sample axes over a wide range of temperatures. Results: It was found out that in natural air cooling the main mechanisms are conductive, convective and radiative heat transfer. The contribution of thermal radiation to the cooling process is noticeable at high temperatures. It was found that the typical cooling time increases with sequential radiative, conductive and convective heat transfer. By extending the temperature study area to, for the first time, we were able to observe each component of the heat transfer process independently. The values of the typical cooling time on all axes correspond to the experimental error bounds. It was found that the temperature value of the sample is independent of the coordinates and depends only on time. In this case, the law of conservation of energy can be used to explain the dependence of body temperature on cooling time. Conclusion: It is shown that the sample under study is ‘thermally thin’, i.e. the thermal field is constant in all directions. In this situation, the thermal balance equation should be applied rather than the Fourier differential equation of heat conduction, since the temperature gradient inside the body is practically zero. The results obtained are of great importance for the study of cooling processes of metallic products in thermal power engineering, heat engineering and thermophysics.

High-turbulence fine particle flotation cell optimization and verification

Microfine mineral particles have a small size, light weight, and low inertia, making it difficult for them to deviate from streamlines and collide with bubbles. Conventional flotation operations consume a large amount of reagents and exhibit poor flotation indicators. This study employs computational fluid dynamics (CFD) simulation and hydrodynamic testing to investigate the flow field within a high-turbulence microfine particle flotation machine equipped with a multilayer impeller–stator configuration, and validates the practical application performance of the microfine particle flotation machine through single-batch flotation experiments. Result shows that the impeller region of the traditional mechanical stirring flotation machine has a turbulent energy dissipation rate of 20 m²/s³, whereas that for the microfine particle flotation machine averages over 120 m²/s³. In the flotation verification, the cumulative recovery rate of the fine particle flotation machine is increased by 28% compared with that of the traditional KYF flotation machine. The flotation rate is also 1.3 times that of the KYF, demonstrating stronger selectivity for fine particle concentrates. It has certain guiding significance for the resource utilization of fine particle minerals.

Design of multimodal transformable wheels for amphibious robotic vehicles

Amphibious vehicles are versatile for locomotion on both water and land; to reduce the complexities of structure and control, an amphibious vehicle is expected to use a single propulsion system without additional screw propellers or water jets; as vehicles are typically driven by wheels that are efficient for smooth land locomotion, how to make the wheels also as water propellors for multimodal transformations is meaningful, while such wheels are less explored. From this motivation, in this short article, we report the design of a multimodal transformable wheel with three driving modes (wheel mode, forward-propellor mode, and backward-propellor mode) and the integrated mode-locks for each driving mode. To achieve the multimodal transformations of the wheel, we design the integrated mode-transform mechanism and mode-lock mechanism, the two mechanical implementations are driven by only two actuators and are compact with low inertia and low control complexity, with the kinematic properties provided during the wheel transformations.

Voltage stability control strategy for DC microgrid based on adaptive virtual DC motor

The large-scale integration of distributed energy sources and power electronic devices results in the DC microgrid exhibiting significant low inertia and weak damping characteristics. This, in turn, leads to inevitable fluctuations in the DC bus voltage, which endanger the stable operation of the DC system. Energy storage devices can provide equivalent inertia. To enhance the inertia and response speed of the DC bus interface converter, this paper proposes a power allocation parameter adaptive virtual DC motor control strategy based on a hybrid energy storage unit. The strategy introduces power allocation control to regulate the energy storage converter on the basis of virtual inertia parameter adaptive control, thereby enabling the energy storage converter to simulate the inertia and damping characteristics of a DC generator. The small-signal stability of the system is analyzed by establishing a small-signal model of the photovoltaic energy storage system and utilizing the impedance ratio criterion. Finally, the proposed control strategy is validated through simulation. The results demonstrate that the strategy effectively mitigates the fluctuations in bus voltage under varying photovoltaic power and sudden load changes, ensures the power distribution in the hybrid energy storage system, and enhances the dynamic response of the system.

A blockchain-based architecture for tracking and remunerating fast frequency response

The increasing penetration of renewable sources introduces new challenges for power systems’ stability, especially for isolated systems characterized by low inertia and powered through a single diesel power plant, such as it happens in small islands. For this reason, research projects, such as the BLORIN project, have focused on the provision of energy services involving electric vehicles owners residential users to mitigate possible issues on the power system due to unpredictable generation from renewable sources. The residential users were part of a blockchain-based platform, which also the Distributors/Aggregators were accessing. This paper describes the integrated framework that was set up to verify the feasibility and effectiveness of some of the methodologies developed in the BLORIN project for fast frequency response in isolated systems characterized by low rotational inertia. The validation of the proposed methodologies for fast frequency response using Vehicle-to-Grid or Demand Response programs was indeed carried out by emulating the dynamic behavior of different power resources in a Power Hardware-in-the-Loop environment using the equipment installed at the LabZERO laboratory of Politecnico di Bari, Italy. The laboratory, hosting a physical microgrid as well as Power Hardware-in-the-Loop facilities, was integrated within the BLORIN blockchain platform. The tests were conducted by assuming renewable generation development scenarios (mainly photovoltaic) and simulating the system under the worst-case scenarios caused by reduced rotational inertia. The experiments allowed to fully simulate users’ interaction with the energy system and blockchain network reproducing realistic conditions of tracking and remuneration of users’ services. The results obtained show the effectiveness of the BLORIN platform for the provision, tracking and remuneration of grid services by electric vehicles and end users, and the benefits that are achieved in terms of reducing the number of diesel generating units that need to be powered on just to provide operational reserve due to the penetration of renewable sources, resulting in fuel savings and reduced emissions.

Two-Stage Optimal Configuration Strategy of Distributed Synchronous Condensers at the Sending End of Large-Scale Wind Power Generation Bases

The transmission end of large-scale wind power generation bases faces challenges such as high AC-DC coupling strength, low system inertia, and weak voltage support capabilities. Deploying distributed synchronous condensers (SCs) within and around wind farms can effectively provide transient reactive power support, enhance grid system inertia at the transmission end, and improve dynamic frequency support capabilities. However, the high investment and maintenance costs of SCs hinder their large-scale deployment, necessitating the investigation of optimal SC configuration strategies at critical nodes in the transmission grid. Initially, a node inertia model was developed to identify weaknesses in dynamic frequency support, and a critical inertia constraint based on node frequency stability was proposed. Subsequently, a multi-timescale reactive power response model was formulated to quantify the impact on short-circuit ratio improvement and transient overvoltage suppression. Finally, a two-stage optimal configuration strategy for distributed SCs at the transmission end was proposed, considering dynamic frequency support and transient voltage stability. In the first stage, the optimal SC configuration aimed to maximize system inertia improvement per unit investment to meet dynamic frequency support requirements. In the second stage, the configuration results from the first stage were adjusted by incorporating constraints for enhancing the multiple renewable short-circuit ratio (MRSCR) and suppressing transient overvoltage. The proposed model was validated using the feeder grid of a large energy base in western China. The results demonstrate that the optimal configuration scheme effectively suppressed transient overvoltage at the generator end and significantly enhanced the system’s dynamic frequency support strength.

Weaknesses of steady state analysis when used for selecting solar air heaters

The paper highlights the constrains faced by the user when choosing the most appropriate solar collector from a set of collectors belonging to the same category. Two basic kinds of one porous and one non-porous with single flow/pass flat solar air heaters were tested. The collectors have the same size but different internal shapes and absorber materials. The two collectors were tested and a shading procedure was implemented in order to emphasize several aspects related to the thermal inertia of the collectors. Comparison has been made between the efficiency values obtained experimentally. The shade test shows a faster decrease of the outlet air temperature for V-porous absorber collector in comparison with the U-corrugated absorber collector i.e. 6 °C and –3.5 °C respectively in a time interval of 74 s. Exposing the collectors on a fresh heating cycle under a low stability radiative regime (450–750 W/m2) one observe that 60% of the first 180 s the corrugated collector outperforms the porous collector; after that interval of time the porous collector becomes more effective. The low thermal inertia of the solar air collectors yields high variation of the thermal efficiency in days with low stability of the radiative regime. In such days, using measured series of solar irradiance data with long sampling period between two successive measurements does not allow a proper choice of the most appropriate solar collector type.

Load frequency control performance enhancement of an electric vehicle integrated time-delay multi-microgrid system

ABSTRACT Frequency control in a microgrid (μG) is problematic due to low inertia of distributed generators (DGs) and uncertainty of the renewable energy source-dependent DGs. Consequently, deploying distributed storage units (DSUs) in a μG is crucial for quickly arresting frequency deviations. The electric vehicle (EV) technology, as DSU, is being preferred over conventional energy storage due to its lower cost and slower degradation rate, facilitating demand side response in a μG. The adoption of the EV technology necessitates an open communication infrastructure in the μG, with a pre-existing communication time delay (CTD). This article explores the impact of EV integration on load frequency control (LFC) performance of a multi-microgrid (MμG) system and determines an optimal CTD value simultaneously. A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the MμG system. Simulation results reveal significant improvements in dynamic responses when integrating EVs in the MμG, with a 97.33% increase in objective function value. The recommended controller also outperforms standard controllers in terms of how quickly frequency and tie-line power variations settle down to zero. Thus, the proposed controller meets the LFC requirements. Robustness of the proposed LFC scheme is tested against parametric variations in the MμG system.

Cyber resilience in renewable microgrids: A review of standards, challenges, and solutions

Increasing penetration of power electronic-based renewable energy generation resources, decreasing total rotational inertia, and bidirectional power flow have changed the concept of smart microgrid stability and operational requirements. The stability of low inertia and fast dynamic renewable smart microgrids is highly dependent on reliable and feasible interoperability between their components. Communication infrastructure is responsible for providing this interoperability within the specified time horizon, considering confidentiality, integrity, availability, and authenticity of the exchanged information. This makes smart microgrids vulnerable to cyber-attacks. Attackers attempt to disrupt microgrid operations by manipulating transmitted data or attacking the physical system. This paper presents a systematic review of standards, challenges, and solutions for renewable smart microgrid cyber resiliency, focusing on communication technologies, protocols, intelligent electrical devices, and renewable energy generation sources. It provides a detailed cyber threat investigation, including targeted components, methods of execution, provided solutions, and attack destructive results. Then, with deep practical and theoretical knowledge of renewable smart microgrid cyber-attack vulnerabilities, this review recommends several practical solutions for cyber resiliency and proposes potential future studies.

Improving primary frequency response in photovoltaic systems using hybrid inertia and intelligent control techniques

Abstract Low inertia poses a significant challenge to the widespread integration of photovoltaic (PV) systems into the grid, particularly affecting frequency stability. This paper addresses this challenge by proposing an advanced hybrid inertia (AHI) approach, characterized by the integration of real and virtual inertia, combined with the application of intelligent control techniques, to enhance the primary frequency response of a PV system. Internal inertia is provided by a synchronous generator (SG) acting as a compensator, while virtual inertia is generated through a real-time deloading strategy in the PV plant. The AHI is implemented on an isolated grid, utilizing various intelligent control techniques to improve frequency stability. The intelligent techniques employed include genetic algorithms (GA) and fuzzy logic controllers (FLC), which do not require mathematical modeling. This allows them to overcome the nonlinear dynamics of the PV plant and the uncertainties associated with climatic changes. These techniques are applied to the nonlinear components on the generator side, including the governor loop, DC-DC converter loop, and power reserve injection management loop. A frequency fluctuation scenario, induced by generating power perturbations in the proposed system, demonstrates and validates the improvement in frequency stability achieved by the HI and intelligent techniques. All tests are conducted using MATLAB Simulink. Various simulation results show a significant improvement in frequency stability through the incorporation of HI and intelligent control techniques.

Profilometry‐Based Indentation Plastometry at High Temperature

This is a first report on profilometry‐based indentation plastometry (PIP) at high temperature (HT), covering both thermal characterization and issues for obtaining stress–strain curves. The heating system has a relatively low thermal inertia, reaching 800 °C within about 10 min, while both indentation (≈20 s) and cooling (≈20 min) are also quick. This capability is useful in terms of limiting exposure of the sample to prolonged periods at HT, and hence avoiding the formation of thick oxide layers (which can affect indent profiles and hence inferred stress–strain curves). There is good general consistency between stress–strain curves obtained via HT‐PIP and those from tensile testing. However, the possibility of creep (time‐dependent deformation) affecting the outcomes (of both types of test), particularly at higher temperatures, should be borne in mind. Creep has a characteristic effect on tensile curves, which can often be confirmed and investigated by changing the imposed strain rate. It can also be revealed by carrying out the HT‐PIP testing with different penetration velocities or by monitoring the shape of the load–displacement plot.

Low-Cost Cable-Driven Robot Arm with Low-Inertia Movement and Long-Term Cable Durability

Our study presents a novel design for a cable-driven robotic arm, emphasizing low cost, low inertia movement, and long-term cable durability. The robotic arm shares similar specifications with the UR5 robotic arm, featuring a total of six degrees of freedom (DOF) distributed in a 1:1:1:3 ratio at the arm base, shoulder, elbow, and wrist, respectively. The three DOF at the wrist joints are driven by a cable system, with heavy motors relocated from the end-effector to the shoulder base. This repositioning results in a lighter cable-actuated wrist (weighing 0.8 kg), which enhances safety during human interaction and reduces the torque requirements for the elbow and shoulder motors. Consequently, the overall cost and weight of the robotic arm are reduced, achieving a payload-to-body weight ratio of 5:8.4 kg. To ensure good positional repeatability, the shoulder and elbow joints, which influence longer moment arms, are designed with a direct-drive structure. To evaluate the design’s performance, tests were conducted on loading capability, cable durability, position repeatability, and manipulation. The tests demonstrated that the arm could manipulate a 5 kg payload with a positional repeatability error of less than 0.1 mm. Additionally, a novel cable tightener design was introduced, which served dual functions: conveniently tightening the cable and reducing the high-stress concentration near the cable locking end to minimize cable loosening. When subjected to an initial cable tension of 100 kg, this design retained approximately 80% of the load after 10 years at a room temperature of 24 °C.

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.

Deep Entropy-Learning based virtual inertia control for VRFB regulation considering Phase-Locked loop dynamics

The virtual inertia control (VIC) technique is often adopted as a prominent mechanism to address the inertia deficiency of modern integrated power systems with high penetration of sustainable energy units. In such control mechanisms, a phase-locked loop (PLL) is required to estimate the grid frequency. However, utilization of such frequency measurement platforms is accompanied by large frequency fluctuations due to its inherent dynamics. In particular, this paper proposes an adaptive integral recursive backstepping (I-RBSC) based on virtual inertia for the regulation of vanadium redox flow battery (VRFB) in stand-alone Micro-Grids (SMGs). Unlike previous works that neglected the effect of frequency measurement devices, this work investigates the effect of PLL dynamics in virtual inertia control. The I-RBSC controller is designed by an entropy-driven actor-critic neural networks (NNs) to adaptively adjust the tunable coefficients during its interaction with the SMG. By training the ability of deep NNs, the entropy is maximized to regulate the system output. The VRFB unit can be discharged up to 90% which can quickly respond to the randomness of loads and sustainable energy units. The transient outcomes of SMG reveal the feasibility of I-RBSC (designed by entropy learning) to address the challenges of low inertia and PLL dynamics. The real-data of wind turbine and solar radiation are utilized to simulate the SMG in a more realistic framework from a systematic point of view. The comprehensive analysis under typical scenarios confirms the supremacy of the suggested VIC controller over prevalent state-of-the-art virtual inertia controllers including conventional VIC, fuzzy logic, backstepping, and model-predictive control (MPC).