Standalone Research Articles

Hybrid Renewable Systems for Small Energy Communities: What Is the Best Solution?

This research developed smart integrated hybrid renewable systems for small energy communities and applied them to a real system to achieve energy self-sufficiency and promote sustainable decentralized energy generation. It compares stand-alone (SA) and grid-connected (GC) configurations using a developed optimized mathematical model and data-driven optimization, with economic analysis of various renewable combinations (PV, Wind, PHS, BESS, and Grid) to search for the optimal solution. Four cases were developed: two stand-alone (SA1: PV + Wind + PHS, SA2: PV + Wind + PHS + BESS) and two grid-connected (GC1: PV + PHS + Grid, GC2: Wind + PHS + Grid). GC2 shows the most economical with stable cash flow (−€123.2 annually), low CO2 costs (€367.2), and 91.7% of grid independence, requiring 125 kW of installed power. While GC options had lower initial investments (between €157k to €205k), the SA configurations provided lower levelized costs of energy (LCOE) ranging from €0.039 to €0.044/kWh. The integration of pumped hydropower storage enhances energy independence, supporting peak loads for up to two days with a storage capacity of 2.17 MWh.

Finite element analysis of biomechanical investigation on diverse internal fixation techniques in oblique lumbar interbody fusion

BackgroundTo establish a three-dimensional finite element model of the lumbar spine and investigate the impact of different fixation techniques on the biomechanical characteristics of oblique lumbar interbody fusion (OLIF).MethodsThe study aimed to establish and validate a comprehensive three-dimensional model of the lower lumbar spine (L3-S1) using the finite element method. L4-L5 was selected as the surgical segment, and four distinct OLIF surgical models were constructed: Stand-alone (SA), unilateral cortical bone trajectory screw (UCBT), bilateral cortical bone trajectory screw (BCBT), and bilateral pedicle screw (BPS). The models were underwent a pure moment of 10N·m to simulate lumbar extension, flexion, left bending, right bending, left and right rotation movements. Subsequently, the range of motion (ROM), cage stress, and fixation stress were calculated.ResultsIn the L3-L5 segment, the BCBT group showed the most limited range of motion (ROM) under exercise load, indicating superior stability within this group. The ROM and cage stress values were found to be highest in the SA group. In contrast, the cage and internal fixation stress in the BPS group were observed to be lowest (9.91 ~ 53.83MPa, 44.93 ~ 84.85 MPa). With the exception of right bending and right rotation, the UCBT group demonstrated higher levels of internal fixation stress (102.20 ~ 164.62 MPa).ConclusionsThe study found that OLIF-assisted internal fixation improved segmental stability and reduced cage stress. The BPS group had advantages over the CBT group in preventing endplate damage and reducing the risk of cage subsidence. However, BCBT group has distinct merits in maintaining surgical segment stability, distributing stress load on the spinal motor unit, and reducing the likelihood of adjacent segment degeneration (ASD).

Biomechanical changes of oblique lumbar interbody fusion with different fixation techniques in degenerative spondylolisthesis lumbar spine: a finite element analysis

ObjectiveThere is a dearth of comprehensive research on the stability of the spinal biomechanical structure when combining Oblique Lumbar Interbody Fusion (OLIF) with internal fixation methods. Hence, we have devised this experiment to meticulously examine and analyze the biomechanical changes that arise from combining OLIF surgery with different internal fixation techniques in patients diagnosed with degenerative lumbar spondylolisthesis.MethodsSeven validated finite element models were reconstructed based on computed tomography scan images of the L3-L5 segment. These models included the intact model, a stand-alone (S-A) OLIF model, a lateral screw rod (LSR) OLIF model, a bilateral pedicle screw (BPS) OLIF model, an unilateral pedicle screw (UPS) OLIF model, a bilateral CBT (BCBT) OLIF model, and an unilateral CBT(UCBT) OLIF model. The range of motion (ROM), as well as stress levels in the cage, L4 lower endplate, L5 upper endplate, and fixation constructs were assessed across these different model configurations.ResultsS-A model had the highest average ROM of six motion modes, followed by LSR, UPS, UCBT, BPS and BCBT. The BCBT model had a relatively lower cage stress than the others. The maximum peak von Mises stress of the fixation constructs was found in the LSR model. The maximum peak von Mises stress of L4 lower endplate was found in the S-A model. The peak von Mises stress on the L4 lower endplate of the rest surgical models showed no significant difference. The maximum peak von Mises stress of the L5 upper endplate was found in the S-A model. The minimum peak von Mises stress of the L5 upper endplate was found in the BCBT model. No significant difference was found for the peak von Mises stress of the L5 upper endplate among LSR, BPS, UPS and UCBT models.ConclusionAmong the six different fixation techniques, BCBT exhibited superior biomechanical stability and minimal stress on the cage-endplate interface. It was followed by BPS, UCBT, UPS, and LSR in terms of effectiveness. Conversely, S-A OLIF demonstrated the least stability and resulted in increased stress on both the cage and endplates. Combining OLIF with BCBT fixation technique enhanced biomechanical stability compared to BPS and presented as a less invasive alternative treatment for patients with degenerative lumbar spondylolisthesis.

Oil price volatility and changes in corporate debt: An empirical study in the Indian landscape

Changes in crude oil prices affect corporate debt position. This study investigates the association between changes in debt and crude oil price volatility in nonfinancial, BG, and SA firms in India. We use financial variables, crude oil prices, and macroeconomics data from 2004 to 2020 for 16,452 firm-years and this study employs unbalanced panel data and utilizes different empirical methodologies, including the generalised method of moments (GMM) estimator, to test the stated hypotheses. The results reveal that the debt position and the crude oil price volatility significantly have different effects on business group (BG) and stand-alone (SA) firms. Crude oil price volatility is positively related to changes in the debt position. The effects of the financial variables also significantly differ for the BG and SA firms. Finally, firms change their debt position in the positive or negative direction based on the fluctuations in crude oil prices. Policy implications have also been provided.

Intelligent learning approach for transition control and protection of solar PV integrated electric vehicle charging station

Recently, the control of distributed generations (DGs) with electric vehicles (EVs) parking lot charging systems has received much attention for supporting emergency local loads during grid outages. To achieve optimal transition control of grid-connected (GC) and standalone (SA) modes, an intelligent learning-based algorithm is implemented for optimal handling of the disturbance in the system by injecting a fault condition over certain cycles during a weak/strong grid operation. Here, a fuzzy Q-learning (FQL) based algorithm is implemented for detecting and monitoring the distributed grid condition during different scenarios and a seamless transitioning control in GC and SA modes of operation. In this context, the implementation of designed FQL algorithm enables dynamic adjustments of control signals in response to real-time uncertainties in two major applications (grid synchronization and islanding detection mode). The FQL algorithm focuses on real-time decision-making in response to sudden fault scenarios, addressing the problem under various modes of operation. To validate the proposed FQL controller accuracy, a real-time hardware-in-loop (HIL) simulation and their experimental validation is carried out of a 16kWp grid integrated PV sub-system with different load profiles. The performance evaluation of the FQL controller is investigated under linear and nonlinear local load scenarios.

Economic assesment of cellular technologies deployment under carrier aggregation techniques for inter radio access technologies

Purpose: The deployment of the fifth-generation (5G) of wireless communications that was launched worldwide in 2020 is entering its final stage in some countries. In this stage carriers apply new techniques that are boosting network performance without heavy investments of the initial build of the infrastructure. This techniques include but are not limited to carrier aggregation, 5G Non-standalone(NSA) and standalone(SA) NR modes, mmWave frequency range and higher bandwidth. Given considerable research in the area about economic and financial validation of the 5G, this work is an extension of a techno-economical assess of the cellular networks under these technologies.
 Method: Computer simulations, theroretical derivations.
 Findings: Major factors such as spectral efficiency, intercell interference and deployment cost are revisited, and updated to fit realities of the current technological progress. Finally, we use abovementioned theory and present simulation results from the city center of Kyiv city using recently developed pysim5G network simulator.
 Paper type: Scientific and practical.

Design and Implementation of a Specialised Millimetre-Wave Exposure System for Investigating the Radiation Effects of 5G and Future Technologies.

As the fifth-generation (5G) network is introduced in the millimetre-wave (mmWave) spectrum, and the widespread deployment of 5G standalone (SA) is approaching, it becomes essential to establish scientifically grounded exposure limits in the mmWave frequency band. To achieve this, conducting experiments at specific frequencies is crucial for obtaining reliable evidence of potential biological impacts. However, there is a literature gap where experimental research either does not utilise the mmWave high band (e.g., the 26 Gigahertz (GHz) band) or most studies mainly rely on computational approaches. Moreover, some experimental studies do not establish reproducible test environment and exposure systems. Addressing these gaps is vital for a comprehensive exploration of the biological implications associated with mmWave exposure. This study was designed to develop and implement a mmWave exposure system operating at 26 GHz. The step-by-step design and development of the system are explained. This specialised system was designed and implemented within an anechoic chamber to minimise external electromagnetic (EM) interference, creating a controlled and reproducible environment for experiments involving high-frequency EM fields. The exposure system features a 1 cm radiation spot size, enabling highly localised exposure for various biological studies. This configuration facilitates numerous dosimetry studies related to mmWave frequencies.

Security Vulnerabilities in 5G Non-Stand-Alone Networks: A Systematic Analysis and Attack Taxonomy

5G networks, pivotal for our digital mobile societies, are transitioning from 4G to 5G Stand-Alone (SA) networks. However, during this transition, 5G Non-Stand-Alone (NSA) networks are widely used. This paper examines potential security vulnerabilities in 5G NSA networks. Through an extensive literature review, we identify known 4G attacks that can theoretically be applied to 5G NSA. We organize these attacks into a structured taxonomy. Our findings reveal that 5G NSA networks may offer a false sense of security, as most security and privacy improvements are concentrated in 5G SA networks. To underscore this concern, we implement three attacks with severe consequences and successfully validate them on various commercially available smartphones. Notably, one of these attacks, the IMSI Leak, consistently exposes user information with no apparent security mitigation in 5G NSA networks. This highlights the ease of tracking individuals on current 5G networks.

A Private SDR 5G SA Network: An Evaluation of the Quality of Service (QoS) and Computational Resource Allocation for eMBB Slice

This paper assesses the network performance in terms of Quality of Service (QoS) for the enhanced Mobile Broadband (eMBB) slicing of a private Stand-Alone (SA) network and a base station, identified as Next-Generation Node B (gNB), which is operating at 3.75GHz and using a Software Defined Radio (SDR) device. The contributions of this work are the evaluation of the computational resource allocation of a private 5G SA and the comparison of the QoS performance of the private SA network with a controlled laboratory testbed and a simulation tool, which is known as UERANSIM (User Equipment and Radio Access Network). Additionally, open-source monitoring systems were used in order to collect memory and CPU usage of the network during the experimentation. For the deployment of the SDR 5G SA gNB, the Universal Radio Software Peripheral (USRP) version B210 equipment was utilized. The results also consider the evaluation of QoS metrics i.e. throughput, jitter, round trip time and propagation delay to assess the performance of the private SDR 5G SA network.

The Frequency Regulation Strategy for Grid‐Forming Wind Turbine Generator and Energy Storage System Hybrid System in Grid‐Connected and Stand‐Alone Modes

This paper proposes a coordinated frequency regulation strategy for grid‐forming (GFM) type‐4 wind turbine (WT) and energy storage system (ESS) controlled by DC voltage synchronous control (DVSC), where the ESS consists of a battery array, enabling the power balance of WT and ESS hybrid system in both grid‐connected (GC) and stand‐alone (SA) modes. The newly developed GFM framework, i.e., DVSC, is adopted in both WT and ESS, which utilizes DC voltage dynamics for synchronization purposes. In this paper, the GC mode and SA mode are transferred by changing the status of the series‐connected switch, and it is necessary to meet the grid connection conditions when the system is transferred to the GC mode, namely, voltage, frequency, and phase sequence. For the GC mode, the inertia response from WT can be realized using the reserved energy of the DC capacitor, while the ESS serves to eliminate the steady‐state frequency deviation and reduce the DC voltage fluctuation of WT using the designed secondary frequency regulation scheme. For the SA mode, the proposed strategy can keep the power balance without external power sources. The small‐signal model of the WT and ESS hybrid system is derived. The stability analysis in both GC and SA modes is fully conducted utilizing the modal analysis method, where the impacts of control parameters on stability are assessed. The performance of the proposed strategy in a weak system is evaluated. Simulation studies are carried out under various power system contingencies to verify the effectiveness of the proposed strategy and validate the correctness of the theoretical analysis.

Fifth Generation Non-Standalone to Standalone Wireless Architecture Reconstruction Solution and Implementation: South Africa Context

The wireless mobile communication industry has evolved immensely over the past five decades, starting from the voice-centric 1G technology to the current data-centric 5G technology because of the increasing data traffic and the need for higher data speed rates. To provide the initial experience of 5G technology, many network operators worldwide started their deployment with the Non-Standalone (NSA) solution to mainly reduce the cost and time. 5G NSA solution already provides lower latency, higher network capacity, and bandwidth compared to the legacy network, however, there is growing oncern about its reliance on the 4G core network, capability, and the long-term migration plan to 5G Standalone (SA) network solution. This paper discusses a brief review of 5G evolution, standardization formulation, deployment strategies, security enhancement, challenges, and presents the reconstruction of 5G NSA to SA solution implementation. Furthermore, a 5G field test will be performed to analyze the user experience under the NSA NR in South Africa, and key practical challenges facing the South African MNOs from the perspective of business and technical challenges will be discussed with recommendations.

Agent-based modeling and simulation for 5G and beyond networks : A comprehensive survey

Modeling and simulation of telecommunication networks have captivated significant inter-disciplinary attention, notably since the release of the fifth-generation (5G) technology and the heavy public interest associated with its Non-Standalone (NSA) and eventual Standalone (SA) architecture deployment. However, 5G and beyond (5G+) network simulation is rather challenging as the complexity of networks has massively multiplied, given the manifold network intricacies demanded by stringent 5G requirements like mobile mmWave, Massive Multiple-Input Multiple-Output (MIMO), Advanced Channel Coding, and more. Furthermore, the arrival of 5G marks a turning point in the evolution of mobile networks as it progresses towards the softwarization of networks and paves the path for future Artificial Intelligence (AI) native 6G and beyond networks. Consequently, classical simulation techniques have a high risk of becoming insufficient to model the demands of such drastically changing network dynamics, prompting researchers to view 5G+ networks from the perspective of Complex System Science (CSS). We move in that direction as we shed light on Agent-based modeling and simulation as a pragmatic and powerful tool to model 5G+ communication networks. Our approach involves a comprehensive survey of Agent-Based Simulation (ABS) and 5G+ networks, utilizing its insights to dissect the advantages, potential, and challenges of ABS in the context of 5G+ networks. Through proposing a prospective architecture for a simulator and its envisioned evolution into a Digital Twin (DT), we not only offer insights into the lessons learned but also chart out future research pathways in the flourishing domain of 5G+ modeling and simulation. To the best of our knowledge, this is the first study in the literature that tackles the complexities of modeling and simulating 5G+ networks, by adopting an ABS approach.

A hybrid analytical concept to QoE index evaluation: Enhancing eMBB service detection in 5G SA networks

The launch of commercial 5G networks has unlocked numerous opportunities for heavy data users and high-speed applications. The expected requirements for enhanced mobile broadband (eMBB) are pushing end-users to adopt 5G optimistically. Though already deployed 5G networks have shown high data rates and very low latency, the service-based experience and application behavior have been challenging to monitor. The legacy quality of experience (QoE) and service (QoS) monitoring and evaluation techniques have shown limitations in 5G standalone networks. The current 5G deployment large amount of user plane traffic generated by end-users makes the legacy-monitoring task very costly for mobile network operators (MNOs). And the complexity of the projected future 5G architecture, including advanced technologies such as network functions virtualization (NFV), software-defined networking (SDN), and network slicing, makes traditional service detection and QoE assessment ineffective. In this paper, we discuss a cost-effective hybrid analytical approach to eMBB service detection, analysis, and perceived user QoE measurement from raw traffic in a live 5G standalone (SA) network. We first use flow-level-based packet inspection and machine learning to detect and classify eMBB services from raw traffic. We then use a statistical approach to compute the user quality index (UQI). The concept is tested on traffic captured on a fixed 5G SA network. And the output enabled the MNO to have a 5G QoE assessment structure and awareness to adjust network traffic policies.

A comprehensive analysis of the coverage and performance of 4G and 5G deployments

5G New Radio (5G NR), has now been deployed in all available bands: low (<1 GHz), mid (1–6 GHz), and high (>24 GHz), each with a trade-off between coverage and throughput/latency performance. The preceding 4G Long Term Evolution (4G LTE) networks also catching up to 5G mid-band by deploying in the unlicensed 5 GHz (using License Assisted Access/LAA) and the 3.5 GHz Citizens Broadband Radio Service (CBRS). We present a comprehensive analysis of 4G and 5G deployments in Chicago and Miami, focusing on coverage, throughput, and latency performance in low-, mid-, and high-bands, under several scenarios: outdoor, outdoor-to-indoor, and under high temperature. To measure deployed networks, we utilized a scalable methodology with commercial and custom apps to collect detailed signal data (e.g., signal strength, cell ID, throughput) on user device (i.e., smartphones). The analysis based on our measurements yields the following findings: (i) when comparing the throughput and latency performance of optimized mid-band 4G networks to 5G (both standalone (SA) and non-standalone (NSA)), they exhibit comparable performance, and (ii) it is important to note that mmWave 5G has the capability to deliver multi-Gbps throughput, even in NSA mode. However, this high-speed performance is susceptible to limitations imposed by factors such as distance, body interference, obstructions (such as Low-e glass), and overheating, which can render its performance less reliable. Therefore, even though 5G exhibits considerable potential in its early stages, additional efforts are required to guarantee that the stated goals of 5G are met.

A 5G Coverage Calculation Optimization Algorithm Based on Multifrequency Collaboration

The fifth–generation (5G) network is developing rapidly. The network coverage directly influences the quality of service (QoS) of vertical industries. Coverage capability is a crucial and indispensable indicator when evaluating the performance of a network. However, the results of the current algorithm fall short in terms of accuracy. To restore the current status of 5G network coverage more realistically, in this study, we design a new optimization algorithm for coverage calculation based on the traditional coverage algorithm combined with fourth–generation (4G) coverage reference signal receiving power (RSRP) in management report (MR) and adopt a multisystem collaborative analysis method. The algorithm corrects the coverage results and restores the true value of 5G coverage. Based on this, we provide a practical analysis of the largest standalone (SA) commercial network in the world, which confirms the viability of the algorithm. Both theoretical and practical analyses show that the algorithm can effectively detect hidden weak coverage areas, providing a further reference for future 5G construction and improving the 5G user experience. The proposed approach can be broadly generalized and applied to multifrequency, multioperator, or even sixth–generation (6G) networks.

Predictive Power Control of PMSG based WECS: Development and Implementation for Smooth Grid Synchronisation, Balanced and Unbalanced Grid

In this paper, the distributed generation unit is controlled to operate in both stand-alone (SA) and grid-connected (GC) modes and offers a smooth transition between these modes using the model predictive control scheme. The permanent magnet synchronous generator (PMSG), along with a 2-level back-to-back converter, is named a DGU. A simple and intuitive approach using predictive control is presented in a stationary reference frame for a load-side converter (LSC). A voltage control loop is used during SA mode to fix the voltage and frequency at the load end. The smooth synchronization technique is developed without a phase-locked loop. During GC, a predictive power control regulates active and reactive power during the symmetry and unbalanced grid voltage conditions. The designed strategy makes the power factor improvement, reduction of grid current harmonics, and elimination of twice grid frequency ripple from power during grid unbalance possible. This work has proposed a solution to reduce the overall computational burden on the processor by eliminating the state prediction in each sampling period. The machine-end converter control is formulated in the rotor flux reference frame to keep the power flow across the dc-link capacitor constant. Comprehensive experiments are conducted with the designed scaled laboratory prototype to successfully validate the control’s theoretical claim.

Prediction and optimization of exergetic efficiency of reactive units of a petroleum refinery under uncertainty through artificial neural network-based surrogate modeling

Process uncertainties have been a big challenge to the stable operation and control of process industries. The current study is based on the use of an artificial intelligence model as a surrogate in the online optimization of process conditions of reactive units of a petroleum refinery under uncertainty. Initially, a steady-state Aspen model was used to perform exergy analysis for quantifying the exergy efficiency, irreversibility, and improvement potential of the plant. The process model was then transformed to a dynamic mode by inserting ±5 % uncertainty in process conditions, i.e., mass flow rate, pressure, and temperature, to generate a dataset of 216 samples. An artificial neural network (ANN) model was developed using the dataset to predict exergy efficiency. The ANN model was used as a surrogate in GA and PSO environments to achieve higher exergy efficiency under uncertainty. The optimized process condition derived through GA and PSO based approaches were fed to Aspen model for cross-validation. The Fourier Amplitude Sensitivity Test (FAST) was performed to identify the most influential process conditions in terms of their effect on process exergy efficiency. The overall plant had an exergy efficiency, irreversibility, and improvement potential of 50.57 %, 34,955.55 kW, and 17,276.98 kW, respectively. The correlation coefficient of ANN model was 0.97432. The use of ANN as a surrogate in the optimization frameworks outperformed the standalone (SA) Aspen model of the process in attaining the highest exergy efficiency. Overall the performance of both the GA and the PSO based approaches were comparable. Based on sensitivity analysis, inlet temperatures of reactors were the most sensitive variables affecting the process exergy efficiency. The current study helps in laying a foundation for the simulation of Refinery 4.0.

Photonic hydrogel for continuous glucose monitoring using smartphone readout

Diabetes has become one of the leading deaths causes worldwide. Developing low-cost, rapid, and reusable sensors can provide a solution for continuous glucose monitoring to reduce the diabetic complications that could be fatal. Here, Phenylboronic acid (PBA)-based hydrogel sensors with embedded photonic nanostructures were developed for rapid and continuous glucose quantification within the physiological range. The photonic nanostructures were imprinted on the PBA-based hydrogel using simple and rapid process. Three different sensors: free-standing (FS), stand-alone (SA), and optical fiber (OF) were fabricated and tested in the glucose concentration range of 0–50 mM. A sensitivity of 6, 3, and 1.2 µW/mM was documented for FS, SA, and OF sensors, respectively. A rapid response time of 20 s and saturation time of 3 min were recorded along with a limit of detection of 1 mM. The sensing capabilities of these sensors were examined in both transmission and reflection configurations. Practicality of the sensors was tested using smartphone readout. The optical power was measured using a smartphone exploiting its photodiode and the power changes were correlated with glucose concentrations. These developed sensors may have applications in remote, continuous, and real-time glucose monitoring systems.

The Design and Processor-In-The-Loop Implementation of a Super-Twisting Control Algorithm Based on a Luenberger Observer for a Seamless Transition between Grid-Connected and Stand-Alone Modes in Microgrids

The abrupt transfer from grid-connected (GC) to stand-alone (SA) operation modes is one of the major issues that may threaten the stability of a distributed generation (DG) system. Furthermore, if the islanding mode happens, it is vital to take into consideration the load voltages or load current waveforms as soon as feasible. This paper develops an advanced control technique based on a super-twisting sliding mode controller (ST-SMC) for a three-phase inverter operating in both the GC and SA modes. This control scheme is proposed to ensure a smooth transition from the GC to SA mode and enhance the load voltage waveforms under the islanding mode. In addition, to minimize the operational costs of the system and the complexity of the studied model, a digital Luenberger observer (DLO) with a proper design is adopted for estimating the inverter-side current. The control scheme of the whole system switches between a current control mode during the GC mode and a voltage control mode during the SA mode. The super-twisting control algorithm is applied to the outer voltage control loop involved in the cascaded voltage/current control scheme in the SA mode. Simulation tests of a three-phase inverter are performed for the purpose of assessing the suggested control performance by using the PowerSim (PSIM) software and comparing it with a classical PI controller. Furthermore, a processor-in-the-loop (PIL) implementation in a DSP board TMS32F28335 while debugging is conducted using code composer studio 6.2.0. The obtained results show efficient control properties, such as a smooth transition among the microgrid (MG) operating modes, as well as effectiveness and robustness during both the GC and SA operation modes.

H∞-Based Control Design for Grid-Forming Inverters With Enhanced Damping and Virtual Inertia

Grid-forming inverters (GFMIs) are identified as an important asset for achieving renewable energy-rich power grids. GFMIs are attracting significant attention due to their superior characteristics over grid-following inverters in both grid-connected (GC) and standalone (SA) scenarios. In this article, a second-order discrete-time controller is proposed to achieve a well-damped step response for power reference commands and improved virtual inertia provision capability. In this article, a control design method based on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{\infty} $ </tex-math></inline-formula> is proposed, which is based on the frequency response of the system, to tune the proposed controller. The proposed control design presents a methodical process to specify the desired performance indices through frequency-domain constraints. The performance of the controller is thoroughly validated analytically and through simulation results. The superior performance of the proposed controller over the virtual synchronous generator controller in terms of tracking performance and virtual inertia provision capability is verified through experimental results.