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With the increased inverter-based resources (IBRs) connected to the grid, IBR P-Q capability charts are needed, proposed, and developed by the power industry to assure IBR operation efficiency and reliability. This paper presents a comprehensive P-Q capability evaluation for an IBR plant interconnected with the transmission grid. The proposed study considers the impact of different IBR grid-connected filters, IBR vector control implementation in the dq reference frame, and special interconnection nature of IBRs in a plant structure. The models and algorithms developed for the IBR P-Q capability analysis have considered specific IBR constraints that are different from those of a synchronous generator. The paper especially focuses on exploring the P-Q capability characteristics of IBRs and IBR plant at different interconnection points that are important for managing, designing, and controlling IBRs within an IBR plant, and for the development of international standards, such as IEEE P2800, for connecting IBRs to the transmission and distribution grids in a plant structure. 

With the proliferation of large-scale grid-connected wind farms, subsynchronous oscillations (SSOs) incidents associated with Type-4 wind turbines (WTs) with a permanent magnet synchronous generator (PMSG) occurred frequently. These incidents have caused severe reliability risks to the power grid. Conventionally, P-Q capability charts are utilized to ensure the safety operating region of a synchronous generator. However, a PMSG WT exhibits a complete different and dynamic P-Q capability characteristics due to the difference in energy conversion technique and several other critical factors related to the power converters of the WT. This paper presents a comprehensive dynamic P-Q capability study of a PMSG WT with sufficient and accurate considerations of the WT control and operation in the dq reference frame, its specific power converter constraints, variable grid conditions, etc. Models of a PMSG WT are first developed based on its control principle in the dq reference frame. Then, algorithms for obtaining the P-Q capability charts of the WT are developed with the considerations of complete WT constraints in different aspects. The proposed study is verified via an electromagnetic transient (EMT) model of a grid-connected Type-4 WT. 

The increase in penetration levels of inverter-based resources (IBRs) is changing the dynamic performance of power grids of different parts of the world. IBRs are now being more and more integrated into the grid at a single connection point as an IBR plant. Due to the complex nature and dynamicity of each inverter model, it is not realistic to build and analyze full complex models of each inverter in the IBR plant. Moreover, simulating a large plant including detailed models of all the IBRs would require high computing resources as well as a long simulation time. This has been the main issue addressed in the new IEEE Std 2800-2022. This paper proposes a novel approach to model an IBR plant, which can capture the transient nature at the plant level, detailed IBR control at the inverter level, interactions of multiple IBR groups in a plant structure, and a collector system connecting the IBRs to the grid. The IBRs in the plant use a voltage source inverter topology combined with a grid-connected filter. The control structure of the IBR includes a cascaded loop control where an inner current control and outer power control are designed in the dq-reference frame, and a closed-loop phase-locked loop is used for the grid synchronization. The mathematical study is conducted first to develop aggregated plant models considering different operating scenarios of active IBRs in an IBR plant. Then, an electromagnetic transient simulation (EMT) model of the plant is developed to investigate the plant’s dynamic performance under different operating scenarios. The performance of the aggregated plant model is compared with that of a detailed plant model to prove the effectiveness of the proposed strategy. The results show that the aggregated EMT simulation model provides almost the same result as the detailed model from the plant perspective while the running time/computation burden is much lower.

 

This paper discusses the challenges faced by electric power systems due to the increasing use of inverter-based renewable energy resources (IBRs) operating in grid-following mode (GFL) and the limited support they provide for the grid’s reliability and stability. With increased IBRs connected to the grid, electric utilities are increasingly requiring IBRs to behave like traditional grid-forming (GFM) synchronous generators to provide support for inertia, frequency, voltage, black start capability, and more. The paper focuses on developing GFM inverter technologies with L, LC, and LCL filters and investigates the performance of combined GFM and GFL inverters with different filtering mechanisms when supplying different types of loads. It also emphasizes achieving voltage controllability at the point of common coupling of the GFM with the rest of an AC system. EMT simulation is utilized to investigate the interaction of combined GFM and GFL inverters with different filtering mechanisms. The research results will assist electric utilities in ensuring the reliability and stability of electric power systems in the future. 

An interior permanent magnet (IPM) motor is a prime electric motor used in electric vehicles (EVs), robots, and electric drones. In these applications, maximum torque per ampere (MTPA), flux-weakening, and maximum torque per volt (MTPV) techniques play a critical role in the efficient and reliable torque control of an IPM motor. Although several approaches have been proposed and developed for this purpose, each has its specific limitations. The objective of this paper is to develop a neural network (NN) method to determine MTPA, flux-weakening, and MTPV operating points for the most efficient torque control of the motor over its full speed range. The NN is trained offline by using the Levenberg-Marquardt backpropagation algorithm, which avoids the disadvantages associated with online NN training. A cloud computing system is proposed for routine offline NN training, which enables the lifetime adaptivity and learning capabilities of the offline-trained NN and overcomes the computational challenges related to online NN training. In addition, for the proposed NN mechanism, training data are collected and stored in a highly random manner, which makes it much more feasible and efficient to implement lifetime adaptivity than any other methods. The proposed method is evaluated via both simulation and hardware experiments, which shows the great performance of the NN-based MTPA, MTPV, and flux-weakening control for an IPM motor over its full speed range. Overall, the proposed method can achieve a fast and accurate current reference generation with a simple NN structure, for optimal torque control of an IPM motor. 

With the proliferation of large-scale grid-connected wind farms, subsynchronous oscillation (SSO) incidents associated with Type-4 wind turbines (WTs) with a permanent magnet synchronous generator (PMSG) have occurred frequently. These incidents have caused severe reliability risks to the power grid. Conventionally, P-Q capability charts are utilized to ensure the safety operating region of a synchronous generator. However, a PMSG WT exhibits completely different and dynamic P-Q capability characteristics due to the difference in energy conversion technique and several critical factors related to the WT power converters. This paper presents a comprehensive dynamic P-Q capability study of a PMSG WT with sufficient and accurate considerations of the WT control and operation in the dq reference frame, its power converter constraints, and grid dynamics. Models of a PMSG WT are first developed based on its control principle in the dq reference frame. Then, algorithms for obtaining the P-Q capability charts of the WT are developed with the considerations of complete WT constraints in different aspects. The study analyzes the root cause of many abnormal operations of grid-connected PMSG WTs, reported in the literature, from the dynamic P-Q capability perspectives. The proposed study is verified via an electromagnetic transient (EMT) model of a grid-connected Type-4 WT.

 

Spoke-type PMSMs were designed with commercial permanent magnets and theoretically designed hexaferrite: Nd-Fe-B (NdFe35, G1NH), Alnico (8B, 8H, 9), and La-CoSrM hexaferrite (NMF-15G). It was found that coercivity (Hc) plays a crucial role in determining motor performance. The ANSYS Maxwell software was used to characterize the designed motor performance. Commercial RE-free Alnico 9 holds a 10.5 MGOe of (BH)max, much higher than a 5.5 MGOe of RE-free Alnico 8B/8H and SrM (SrFe12O19) hexaferrite magnets. However, the Alnico 9 motor performance is not better than the other Alnico 8B/8H and hexaferrite motors. The spoke-type PMSM with our theoretically designed SrM hexaferrite simulated motor performance. A motor performs best when the Hc/Br ratio equals one with a high Hc. For instance, the motor torque and peak power increase to 189 Nm and 178 kW, respectively, as the Hc increases to 4.86 kOe from 2.43 kOe. However, the motor performance is not significantly changed with a fixed Hc and various Br. It was found that regardless of (BH)max, coercivity (Hc) plays a dominant role in motor performance.