Showing papers presented at "International Symposium on Industrial Electronics in 2020"

Challenges and Future opportunities of Hairpin Technologies

Abstract: Hairpin windings are seeing an ever-increasing application and development in electrical machines designed for high power and torque densities. In fact, due to their inherently high fill factor, they are very attractive in applications, such as transportation, where these characteristics are considered main design objectives. On the other hand, high operating frequencies also contribute to improve power density of electrical machines. However, at high fundamental frequencies, hairpin windings are characterised by increased Joule losses due to skin and proximity effects. Hence, while these technologies are introducing new opportunities, a number of challenges still need to be addressed. These include manufacturing aspects, contacting processes, thermal management, etc. This paper presents an overview of the current state-of-the-art of hairpin technologies and propose possible future opportunities. The authors’ perspective is then finally provided, showing how innovative winding patterns can potentially overcome the above mentioned challenges.

Monolithic Bidirectional Switch Based on GaN Gate Injection Transistors

Abstract: The paper deals with a bi-directional switch based on N-channel enhancement-mode GaN FET. The proposed device is a Gate Injection Transistor monolithic solution to reduce the volume of the switch with high current density and blocking voltage of 600V. It features a dual-gate control pin and two power terminal. In the paper, the main characteristics of the bi-directional switch and the performance in the four-quadrant of operation are examined and discussed. The device characteristics are compared with the traditional MOSFET and IGBT solutions. The gate driver design issues are considered to optimize the switching transient of the GaN-based switch. Finally, an experimental evaluation of the GaN FET as the bidirectional circuit breaker is carried out in an AC power supply system to validate the effectiveness of the proposed monolithic new device.

Digital Twin Modelling of Ship Power and Propulsion Systems: Application of the Open Simulation Platform (OSP)

Abstract: Today, modelling and simulation technologies are extensively used in the maritime industry. As a reaction to changing market demands and environmental challenges, maritime systems are becoming more complex and coupled. Digital approaches such as digital twins and co-simulation are coping these challenges and offer new opportunities throughout the lifecycle of a vessel. In this work, we present the digital twin modelling and the co-simulation of a typical AC ship power and propulsion system including the power stage, relevant local controllers and a high-level controller. The power and control components are modelled individually and exported as Functional Mock-up Units (FMUs). To perform a co-simulation of the ship electric power system, the Open Simulation Platform (OSP) is utilized. This co-simulation environment connects the individual FMUs and routes the data between the sub-simulators of the digital twin. A typical test scenario is carried out to demonstrate the correct functioning of the ship power and propulsion system as well as the OSP environment.

Deployment of a Smart and Predictive Maintenance System in an Industrial Case Study

Abstract: Industrial manufacturing environments are often characterized as being stochastic, dynamic and chaotic, being crucial the implementation of proper maintenance strategies to ensure the production efficiency, since the machines’ breakdown leads to a degradation of the system performance, causing the loss of productivity and business opportunities. In this context, the use of emergent ICT technologies, such as Internet of Things (IoT), machine learning and augmented reality, allows to develop smart and predictive maintenance systems, contributing for the reduction of unplanned machines’ downtime by predicting possible failures and recovering faster when they occur. This paper describes the deployment of a smart and predictive maintenance system in an industrial case study, that considers IoT and machine learning technologies to support the online and real-time data collection and analysis for the earlier detection of machine failures, allowing the visualization, monitoring and schedule of maintenance interventions to mitigate the occurrence of such failures. The deployed system also integrates machine learning and augmented reality technologies to support the technicians during the execution of maintenance interventions.

DQ-Based Radial Basis Function Controller for Single-Phase PEC9 Inverter

Abstract: Controlling active and reactive powers in single-phase grid-connected inverters is matter of issue. This paper proposes an intelligent controller using Radial Basis Function (RBF) artificial neural network in a single-phase Direct Quadrant (DQ) frame to control active and reactive powers generated by nine-level Packed E-Cell (PEC9) inverter. Because of using single DC source, single DC link and less number of power switches, PEC9 is much interesting for grid-tied applications. In the proposed RBF-based control loop, active and reactive powers are separately controlled by using single-phase DQ transform. Since the grid current is converted to DC form, transient and steady-state errors can be suppressed remarkably. Simulation tests performed by MATLAB software show that the proposed DQRBF control loop desirably tracks active and reactive current references without significant transient response under different dynamic modes. The results also illustrate low THD, minimum capacitor voltage ripple and unity power factor.

Evaluation of Energy Transfer Efficiency for Shore-to-Ship Fast Charging Systems

Abstract: Shore-to-ship charging systems are usually designed based on various operational and design parameters including the onboard power and propulsion requirements, available charging times, and the capability of local power grids. In rural areas with weak grids, onshore energy storages are utilized to enable the high-power charging necessary for vessels with short charging times. However, on-shore energy storage increases the system complexity, and the choice of system configuration can have significant impact on the energy transfer efficiency from the grid to the vessel. This paper presents an energy efficiency comparison between AC, DC and Inductive shore-to-ship charging solutions for short-distanced ferries with AC- and DC-based propulsion. The results demonstrate how an increased share of energy contribution from the onshore battery leads to reduced overall energy efficiency of the charging process. Hence, the energy efficiency should be considered when sharing the load between the grid and the onshore battery. The results show that DC charging is advantageous over other solutions for AC-based propulsion systems in terms of energy efficiency. However, for a DC-based propulsion system, the most efficient solution could be either DC or the AC charging, depending on the load sharing between the grid and onshore battery. Moreover, it is concluded that the inductive charging solution energy efficiency is not far less than the wired schemes, even though it adds more conversion stages and complexity to the system. Considering other advantages of contactless charging, namely, reliability, safety and robustness, these results promote the inductive charging as a promising solution.

Nadir Frequency Estimation in Low-Inertia Power Systems

Abstract: Increasing amounts of non-synchronous generation in power grids are bringing reductions in system inertia. In a grid with extremely low inertia, the estimation of frequency indicators such as the frequency nadir can be used to feed into predictive system controls that would avoid nuisances such as triggering system protection systems, avoiding needless blackouts. In this paper, the timing of a frequency nadir is predicted using a Nonlinear Auto-Regressive (NAR) model based on an Artificial Neural Network (ANN). The estimation method is tested under a gradual inertia reduction in order to observe the adaptability of the method, under various prediction horizons.

Power Sharing Management of a PEC9-based Microgrid by Feedback-Feedforward Control Strategy

Abstract: Multilevel converters can be considered as a worthy alternative for microgrid applications because of their abilities at reaching more active and reactive power generation as well as more suitable power quality enhancement. In this paper, two parallel 9-level Packed E-Cell (PEC9) inverters are utilized to form a grid-connected microgrid with LCL filter. Based on the microgrid specifications, the dynamics of the PEC9 output currents and C filter voltages in d-q reference frame are incorporated in a feedback-feedforward control strategy to manage the power sharing of the inverters for grid stability and unity power factor. The proposed control technique is evaluated through the PEC9 output current-based transfer functions to achieve effective control coefficients. The microgrid system is assessed by Matlab/Simulink environment under load variations to verify the proposed control strategy abilities.

Automatic Industry PCB Board DIP Process Defect Detection with Deep Ensemble Method

Abstract: The conventional PCB (Printed Circuit Board) DIP (Dual Inline Package) process solder defect detection was done by labor inspection, which is not only time-intensive but also labor-intensive. This paper proposes a deep ensemble method to inspect the PCB solder defects to replace the labor inspection. To achieve a high detection rate and a low false alarm rate, two distinct detection models, a hybrid YOLOv2 (YOLOv2 as a foreground detector and ResNet-101 as a classifier) and Faster RCNN with ResNet-101 and FPN are separately trained to obtain a high detection rate result. The final ensemble model aggregates the result from the two detection models. That achieves a 96.73% detection rate and a 19.73% false alarm rate in real tests. The detection time is less than 15 seconds for inferencing a PCB image with a resolution of 7296*6000. The proposed method has been proven efficient in terms of guiding operators to identify and fix PCB solder defects [1] and thus is able to reduce 33% of labor demand for each PCB production line at our real test site. [1].

Analysis of the Reaction Time of eSports Players through the Gaze Tracking and Personality Trait

Abstract: eSports is a developing industry where teams or individual players compete for achieving a specific goal by the end of the game. Although the industry greatly evolved within the last decade, the eSports research is in its infancy: physiological and psychological aspects are not considered together as well as there is a lack of experimentation with the support of Pro players and teams. In this work, we assess the reaction time of the Pro and amateur eSports players using an eye tracker. The whole reaction time consists of three parts: saccadic latency, time between saccade and fixation, and time for aiming and shooting. The correlations between these times’ means and variances with the Big Five personality traits are investigated.

Evaluation of Capacitive Power Transfer for Small Vessels Charging Applications

Abstract: This paper evaluates capacitive power transfer (CPT) with application to the charging of small electric maritime vessels. CPT may provide a cheaper and lighter solution for charging boats with broader safety range and lower eddy losses than inductive charging. The behavior source-based and chain-based equivalent circuit models were used in the analysis. As a case study, the feasibility of charging of the fully electric boat GMV Zero using CPT is considered. The required design parameters needed in order to achieve a similar power level to the conductive charging are analyzed and discussed, where CPT is shown to be a viable solution.

Comparison of Two and Three-Level DC-AC Converters for a 100 kW Battery Energy Storage System

Abstract: This paper discusses a qualitative comparison between Two and Three-Level Voltage Source Converter (VSC) topologies for battery energy storage applications. Three-Level Neutral Point Clamped (NPC) and T-Type circuit topologies are benchmarked versus the state-of-art Two-Level VSC in terms of efficiency and power density considering a 100 kW system. Analytical equations for determining the power losses in the semiconductor modules are given, and the procedure for designing the output LCL filter and the DC-link capacitors is described. The analysis, based on off-the-shelf circuit components, shows that the Three-Level topologies perform better than the Two-Level one in both considered metrics, mainly due to their lower switching losses that allow operating at higher switching frequency without significantly degrading the system efficiency, and, at the same time, increasing the system power density. Additionally, it is found that the T-Type topology shows better performances than the NPC topology at full and high partial loads, being then more suitable for applications that require most of the operation at maximum power.

Plant Growth Prediction through Intelligent Embedded Sensing

Abstract: Precision agriculture is a research domain aimed at securing the food production for the growing Earth population and urbanization. In this paper, we report on a monitoring system that provides robust prediction of plant growth dynamics. Based on the knowledge about plants growth, we propose a solution that consists of two data analysis stages. The first consists of image preprocessing using filters and time series pruning applying statistical methods. On the second stage we make predictions with superficial machine learning algorithms. The proposed solution can run on embedded devices locally. The computation on low-power devices allows us to reduce the data transmission and ensure ‘distributed intelligence’. As for the dataset, we collected the top-down view sequences of plant images. We achieved 5% relative error on four days predictions. The experimental results and modelling demonstrate the high potential of the proposed solution for the precision agriculture industry, being a crucial part for the development of a plant growth control system.

Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins

Abstract: Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of Piping and Instrumentation diagrams as well as 3D pipe routing. However, a complete digital plant model requires combining these two representations. 3D pipe routing information is essential for building any accurate first-principles process simulation model. Piping and instrumentation diagrams are the primary source for control loops. In order to automatically integrate these information sources to a unified digital plant model, it is necessary to develop algorithms for identifying corresponding elements such as tanks and pumps from piping and instrumentation diagrams and 3D CAD models. One approach is to raise these two information sources to a common level of abstraction and to match them at this level of abstraction. Graph matching is a potential technique for this purpose. This article focuses on automatic generation of the graphs as a prerequisite to graph matching. Algorithms for this purpose are proposed and validated with a case study. The paper concludes with a discussion of further research needed to reprocess the generated graphs in order to enable effective matching.

Load Frequency-Based Power Management for Shipboard DC Hybrid Power Systems

Abstract: The development of marine integrated power systems has enabled all-electric ship, with electric propulsion systems to be powered from diesel-generators. In addition, vessels with DC hybrid power sources such as fuel cell, super-capacitor, and battery have been emerging in recent decades. Despite several studies related to hybrid-electric vessels, the integration of hybrid power systems and its application for the marine industry still requires additional research tasks since marine power concepts have unique features, which are different from well-known hybrid vehicle concepts in respect of the number of generators & size, system response, and load profile characteristic. Especially, efficient power management in terms of load sharing among different hybrid power sources is one of the critical issues in the marine hybrid system. In this paper, the load frequency-based approach is proposed for power management and load sharing in DC hybrid electric ships. The main idea is that each power source has distinctiveness with respect to response time. By the application of several low-pass filters, an acceptable range of load frequency for each power source can be classified and distributed to each power controller. The integrated modeling & simulation of the DC hybrid powered vessel is developed to verify the proposed method. The simulation test is implemented as a feasibility study of the proposed load-sharing model for marine applications. As a result, the load frequency-based power management provides an effective load distribution scheme in terms of charging/discharging intervention of hybrid systems, and it is able to protect the generator from the sudden load variation which leads to tears & wears in mechanical systems as well as poor quality of power in electrical systems.

Super-Twisting Sliding Mode Control for Grid-Tied T-Type qZSI with Reduced Capacitor Voltage

Abstract: This paper proposes a super-twisting sliding mode control (ST-SMC) strategy for a three-phase grid-tied three-level T-type quasi-Z-source inverter (qZSI) with LCL filter. The qZSI topology used in this study offers a reduction in the capacitor voltages. While the dc capacitor voltages and inductor currents in the dc-side are controlled by conventional SMC, the grid current in the ac-side is controlled by ST-SMC. Unlike the existing methods, the use of SMC in the dc-side not only eliminates the need for using PI regulator, but also requires one gain only. The proposed ST-SMC in the ac-side controls the grid current successfully without using a special active damping method. Also, it eliminates chattering and leads to a fixed switching frequency operation. The validity of the proposed control strategy is investigated by computer simulations during steady-state and transients caused by the reference change.

Feasibility Design Study of High-Performance, High-Power-Density Propulsion Motor for Middle-Range Electric Aircraft

Abstract: This paper deals with the design of a high power-density, high efficiency and low torque ripple propulsion motor for electric aircraft. The proposed design procedure resulted in a high-performance propulsion motor intended for a direct-drive solution on an 8–12 passenger commercial aircraft with a range up to 1000 miles. The electromagnetic design is firstly addressed and then the thermal management is discussed. A set of design development steps are investigated and validated through finite-element software, involving studies for the optimal selection of the of air gap diameter and the slot/pole combination, followed by improving the efficiency by suitable material selection and methods for losses mitigation. Finally, in order to prove the enhancement of power density and efficiency through this feasibility design study, the designed propulsion motor performance is compared to the state-of-the-art motors of similar direct-drive aircraft propulsion systems.

3D Pipe Network Reconstruction Based on Structure from Motion with Incremental Conic Shape Detection and Cylindrical Constraint

Abstract: Pipe inspection is a critical task for many industries and infrastructure of a city. The 3D information of a pipe can be used for revealing the deformation of the pipe surface and position of the camera during the inspection. In this paper, we propose a 3D pipe reconstruction system using sequential images captured by a monocular endoscopic camera. Our work extends a state-of-the-art incremental Structure-from-Motion (SfM) method to incorporate prior constraints given by the target shape into bundle adjustment (BA). Using this constraint, we can minimize the scale-drift that is the general problem in SfM. Moreover, our method can reconstruct a pipe network composed of multiple parts including straight pipes, elbows, and tees. In the experiments, we show that the proposed system enables more accurate and robust pipe mapping from a monocular camera in comparison with existing state-of-the-art methods.

A Comparative Study of Control Methods for Grid Side Converters in PMSG-Based Wind Energy Conversion Systems

Abstract: Wind energy conversion systems are interfaced with the power grids through power electronic converters. The main duty of grid side converters is to deliver the power to the grid, while fulfilling the grid code requirements. In this paper, the grid codes for the integration of wind power to the grids are presented first. Then the principles of three main control methods for the grid side converters, i.e. vector control, direct power control, and combined control, for permanent magnet synchronous generators are reviewed. In addition, their capabilities and weaknesses in meeting grid codes are investigated. Finally, a comparison of the control performances in fulfilling grid code requirements are presented by extensive simulation results.

Pentagon Connected Five-Phase Induction Machine Working under One-Phase Fault

Abstract: The presented paper deals with the five-phase induction motor (IM) having pentagon connected stator winding, which is working under one phase supply failure. Computation of the motor electromagnetic quantities are made using the space vector theory in the complex plane. Analysis is done assuming, the motor is supplied by a pulse width modulation (PWM) controlled inverter with sufficiently high modulation frequency. Only the first stator voltage harmonics is taken into consideration. On the base of measured IM parameters, trajectories of stator and rotor current space vectors were investigated. On their basis, the motor electromagnetic torque ripple waveform for failure supply mode is derived. Finally a possibility to reduce torque ripple in failure state is shown.

Robust Optimization Approach for Generation Scheduling of a Hybrid Thermal-Energy Storage System

Abstract: In this paper, a new framework for optimal generation scheduling of a hybrid thermal-energy storage (HTES) system is proposed. The proposed generation scheduling is formulated based on the profit maximization of the HTES system, concentrating on taking part in the energy market. The proposed hybrid structure integrates energy storage system (ESS) and thermal units in the form of a hybrid system in a way that a physical connection between these two resources is installed. This physical connection lets the HTES operator charge the ESS through thermal units while it is economical. In order to efficiently address the generation scheduling problem in the presence of market uncertainty, a robust optimization architecture is suggested. The proposed robust model is capable of deriving conservative strategies that are robust against the energy market uncertainty. The formulation of the considered robust problem is carried out based on mixed-integer programming (MIP) and is solved via general algebraic modeling system (GAMS) software.

Technical Assessment of Large Scale PEM Electrolyzers as Flexibility Service Providers

Abstract: To counter the inherent intermittent and unpre dictable power generation from large amounts of wind and solar, fast-acting resources are required, one of the options being sector coupling via power to gas devices. Industrial Power to Gas (IPtG) resources, such as an electrolyzer, represent an attractive solution to satisfy the rising energy flexibility needs of renewable-rich power systems. Since these electrolyzers can be asked to respond quickly following steep power ramps of renewables, it is imperative to understand their capabilities and limitations in fulfilling such requirements. The contribution of this paper is twofold. First, we introduce a detailed model of a Proton Exchange Membrane (PEM) electrolyzer suitable for power system flexibility studies. Second, using this model we assess large scale electrolyzer as a flexibility service provider (FSP) to the grid. To evaluate electrolyzer performance, we construct the V-I characteristic curve before and after simulating each test case to derive insights on the influence of time and dynamic operation on the electrolyzer system.

A Lean Convolutional Neural Network for Vehicle Classification

Abstract: Image classification is an important task in machine vision, in which vehicle classification is used for different applications like traffic analysis, autonomous driving, security, among others. Recent studies made with Convolutional Neural Networks (CNN) have shown that these networks have surpassed older algorithms like Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) in terms of accuracy, speed, and resources management. Even though that CNN have better accuracy and speed they still are heavy in resource consumption on computers which makes them not suitable to deploy on an embedded platform. This paper proposes a lean CNN that has a smaller number of parameters and still maintaining the best accuracy possible on vehicle classification.

Optimal Battery Storage Arbitrage Considering Degradation Cost in Energy Markets

Abstract: Energy arbitrage have monetary benefits for privately owned battery energy storage systems, such as the battery of an electric vehicle or residential batteries. However, the life cycle and degradation cost of the battery storage should be taken into consideration and can decrease obtained income in the long-term. This paper proposes an optimization framework to derive optimal bidding and offering curves for lead-acid battery storage participate in a stepwise energy market. The objective is to maximize the profit comes from participating in energy arbitrage action, while the life cycle of the battery is considered by objective function and constraints. Due to the small capacity of the considered storage unit, it can be assumed that this unit is a price-taker participant, which its actions cannot influence the market prices. Hence, the energy prices are modeled as uncertain parameters using stochastic programming approach. The second order stochastic dominance constraints are as risk management method.

A Feature Reduction Strategy For Enabling Lightweight Non-Intrusive Load Monitoring On Edge Devices

Abstract: Non-Intrusive Load Monitoring (NILM) implies disaggregating the power consumption of individual appliances from a single power measurement point. Recent approaches use a mix of low and high-frequency features, but real-time NILM on low-cost and resource-constrained smart meters is still challenging due to the computing effort needed for feature extraction and classification. In this paper, we present a thorough survey on low, mid, and high-frequency features for enabling the deployment of NILM algorithms on edge-devices. We compare four different supervised learning techniques on different use-cases. Moreover, we developed a novel Microcontroller (MCU) based Smart Measurement Node for collecting measurements, providing computational capabilities to perform NILM on-the-edge. Experimental results demonstrate that by selecting the proper features, a robust disaggregation model for real-time load monitoring is feasible on our MCU-based meter with an accuracy of 95.99%, relying on merely 9.4kB of memory requirements and 16K MACs operation.

Peak-to-Average Ratio Analysis of A Load Aggregator for Incentive-based Demand Response

Abstract: In smart grid, demand response programs have proven to have significant potential in terms of managing distributed systems. Demand response is a strategy to flatten the load profile of the grid by motivating the users based on utility incentives or price signals. As a result, users are inclined to shift their consumption by adjusting their flexible loads to reduce the peak hours and thus the peak-to-average ratio of the grid load profile. The emergence of energy aggregators facilitates the management of financial interactions between the power market and customers. These new players extract the demand flexibility potentials from the grid by employing optimization techniques. This paper studies a multi-agent system that simulate a set of houses under an incentive-based demand response program. Residential agents are capable of performing a model predictive control and forecasting the outside temperature in order to control thermal loads. The peak to average ratio is used to develop the optimization problem of the residential agents and propose a cost function for the aggregator. The results of the simulations allow to analyze the agents response under an incentive-based demand response program and their impact over proposed cost function for the aggregator. The simulated framework enables aggregators to examine the effectiveness of optimization techniques that are aimed for actual implementation.

High-Speed Nonlinear MPC with Long Prediction Horizon for Interleaved Switching AC/DC-Converters

Abstract: The control of high-speed AC/DC-converters is still a very demanding task. This paper presents an online optimizing nonlinear model predictive control (MPC) strategy, which allows to reach long prediction horizons in the range of 100 times the sampling time. The MPC is complemented by estimation strategies for the grid phase voltages and the load current. To achieve a short calculation time of the MPC in the range of a few $\mu$s, the MPC is tailored to the efficient implementation on an FPGA. This is achieved by using the parallel computation capabilities of FPGAs and pipelining methods, and by avoiding time-and resource-demanding operations like trigonometric functions. Compared to other MPC methods discussed in the literature, the proposed MPC strategy allows for significantly longer prediction horizons. The performance and the robustness of the control strategy is evaluated by measurements on a hardware-in-the-loop test bench.

Inverter Control Based on Virtual Impedance Under Unbalanced Load

Abstract: Three-phase four-leg inverter combined with appropriate control method has a good performance when facing the unbalanced load. The three-phase four-leg inverter can generate three-phase balanced voltage under unbalanced load and improve the capacity of the inverter. However, as a result of positive sequence, negative sequence and zero sequence currents need to be controlled, the control system of the inverter is more complicated compared with the traditional three-leg inverter. In this paper, the distribution of the sequence currents are analyzed while the three-phase four-leg inverter running in parallel. To make the different sequence currents distributed according to the capacity of the inverters, the droop control and virtual impedance method are used in the positive and negative sequence currents, and the zero sequence current controlled by the virtual impedance method. Through the proposed method, the parallel inverters can output balanced voltage and the output power are distributed according the capacity of the inverters when they supply the unbalanced load. To verify the effectiveness of the proposed method, simulation study is done at the end of this paper.

Impact of grid impedance and their resonance on the stability of single-phase PV-inverters in low voltage grids

Abstract: This paper studies the behavior of grid-connected single-phase photovoltaic inverters in low voltage grids. The interaction of the inverter control, the grid-side filter and the power grid can lead to harmonic instabilities. The term is used, since its origin is not depending on the active or reactive power at fundamental frequency but an interaction of the inverter control with the impedance of the power grid at frequencies in the harmonic range. In power electronics, the power grid impedance is typically assumed as an RL- equivalent so that a critical RL- combination above which the inverter becomes instable can be calculated by using the Nyquist criterion. Neglecting resonances in a power grid can result in an erroneous assessment of stability based on the Nyquist criterion. This is of importance since recent field measurements indicate that the origin of harmonic instabilities of PV-inverters is primarily related to resonances in the grid impedance. This paper studies the behavior of a single-phase PV-inverter based on a simulation model for different impedance conditions of the power grid to illustrate the impact of the grid impedance and its resonances. The results are compared with laboratory measurements of commercially available PV-inverters.

Analysis of the Gradual Synthetic Inertia Control on Low-Inertia Power Systems

Abstract: The imminent transformation of the power grid with the large inclusion of renewable resources is bringing new challenges to face on. These challenges include an inertia diminution causing drastic changes in the frequency response. This paper analyses the impact of the gradual synthetic inertial control inclusion in the Nordic system as a possible remedial action to contribute in the primary frequency response. Additionally, it proposes slightly changes in the typical synthetic inertial controller to not only reduce the nadir but in the overshoot. Furthermore, the effect of proportional wind power curtailment in improvement of primary frequency response is assessed. Finally, several scenarios for the inertial controller and adjustments are tested in the Nordic 32 test system.