Robust PLL Synchronization Unit for Grid-Feeding Converters in Micro/Weak Grids

A grid-feeding voltage source converter (GFD-VSC) requires a phase-locked loop (PLL) synchronization unit to be connected to the grid. The PLL critically affects the dynamic performance and stability of the GFD-VSC. In particular, a PLL with in-loop filtering, for working under distorted/polluted conditions, possesses a narrow stability margin and deficient performance in weak grid connections and fault ride-through (FRT) transients, also poor performance in frequency estimation. To address these problems, for the first time, a robust PLL with several enhanced characteristics is proposed in this paper. The robust PLL with a dynamic state feedback controller is designed using an H∞ robust control. The feedback controller is designed to improve the dynamic stability/response of the PLL, exposed to control uncertainties and exogenous disturbances, weak-grid connection, FRT transients and to improve its performance in frequency estimation. Numerical simulations validate the effectiveness of the proposed PLL

Deep Reinforcement Learning Based Joint 3D Navigation and Phase Shift Control for Mobile Internet of Vehicles Assisted by RIS-equipped UAVs

Unmanned aerial vehicles (UAVs) are utilized to improve the performance of wireless communication networks (WCNs), notably, in the context of Internet-of-things (IoT). However, the application of UAVs, as active aerial base stations (BSs)/relays, is questionable in the fifth-generation (5G) WCNs with quasi-optic millimeter wave (mmWave) and beyond in 6G (visible light) WCNs. Because path loss is high in 5G/6G networks that attenuate, even, the line-of-sight (LoS) communicating signals propagated by UAVs. Besides, the limited energy/size/weight of UAVs makes it cost-deficient to design aerial multi-input/output BSs for active beamforming to strengthen the signals. Equipping UAVs with the reconfigurable intelligent surface (RIS), a passive component, can help to address the problems with UAV-assisted communication in 5G and optical 6G networks. We propose adopting the RIS-equipped UAV (RISeUAV) to provide aerial LoS service and facilitate communication for mobile Internet-of-vehicles (IoVs) in an obstructed dense urban area covered by 5G/6G. RISeUAV-aided wireless communication facilitates vehicle-to-vehicle/everything communication for IoVs for updating IoT information required for sensor fusion and autonomous driving. However, autonomous navigation of RISeUAV for this purpose is a multilateral problem and is computationally challenging for being optimally implemented in real-time. We intelligently automated RISeUAV navigation using deep reinforcement learning to address the optimality and time complexity issues. Simulation results show the effectiveness of the method

AI-based Navigation and Communication Control for a Team of UAVs with Reconfigurable Intelligent Surfaces Supporting Mobile Internet of Vehicles

Unmanned aerial vehicles (UAVs) are employed in wireless communication networks (WCNs) to improve coverage and quality. The applications of UAVs become problematic in the millimeters wave fifth-generation (5G) and beyond in the optical 6G WCNs because of two reasons: 1) higher path loss which means UAVs should fly at lower altitudes to be closer to the user's equipment; 2) complexities associated with a multi-input multi-output antenna to be incorporated in the UAV as an active aerial base station. We propose equipping UAVs with a (passive) reconfigurable intelligent surface (RIS) to resolve the issues with UAV-enabled wireless communication in 5G/6G. In this paper, the trajectory planning of the RIS-equipped UAV (RISeUAV) that renders aerial LoS service (ALoSS) is elaborated. The ALoSS facilitates vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communication in obstructed dense urban environments for Internet-of-vehicles. (IoVs). To handle the nonconvexity and computation hardness of the optimization problem we use AI-based deep reinforcement learning to effectively solve the optimality and time complexity issues. Numerical simulation results assess the efficacy of the proposed method

SLAPS: Simultaneous Localization and Phase Shift for a RIS-equipped UAV in 5G/6G Wireless Communication Networks

Unmanned aerial vehicles (UAVs) are utilized to improve the performance of wireless communication networks (WCNs). In 5G/6G WCNs, where massive muti-input multi-output (mMIMO) base stations (BSs) are operated for beamforming to address fast fading, shadowing, and blockage issues of millimeter waves (mmWave) and quasi-optic signals, the application of UAVs as active mMIMO transceivers is questionable. This is due to the prohibitive complexity of the required overhead baseband processor. Reconfigurable intelligent surface (RIS) is a complementary technology to mMIMO BSs to address the energy inefficiency and complexity of 5G/6G WCNs. Equipping UAVs with RISs, comprising passive elements, allows UAVs to remain promising gadgets for improving coverage and blockage issues in 5G/6G by reflecting in the sky and providing aerial line-of-sight (ALoS) service. Particularly, RIS-equipped UAVs (RISeUAVs) can be beneficial for ALoS vehicle-to-vehicle (V2V) communication of autonomous intelligent vehicles. However, channel estimation is prohibitive in a highly dynamic environment. In this light, accurate localization makes it feasible to use geometry information for phase shift and passive beam-steering. Also, accurate localization is required for crash avoidance and safe navigation in dense urban canyons. We propose the simultaneous localization and phase shift (SLAPS) method as a mmWave-localization technique for RISeUAVs. Simulation results prove the effectiveness of the method

Effective UAV Navigation for Cellular-Assisted Radio Sensing, Imaging, and Tracking

The paper develops a new cellular-assisted radio surveillance and tracking technique with an Unmanned Aerial Vehicle (UAV) being the mobile receiver and a static cellular ground base station (BS) being the illuminating source. Under the proposed framework, the resolution of the radio surveillance and imaging depends critically on the relative positions (or geometry) between the UAV, BS and target, as well as the instantaneous motions of the UAV and target. A novel UAV navigation law is developed to guarantee that after some time, the range resolution, the azimuth resolution and the distance between the UAV and the moving target will be below some given upper limits. Its mathematically rigorous analysis is presented. Simulations demonstrated the effectiveness of the developed navigation law

Consensus-Based Autonomous Navigation of a Team of RIS-Equipped UAVs for LoS Wireless Communication With Mobile Nodes in High-Density Areas

The reconfigurable intelligent surface (RIS) technology has gained increased attention for improving the performance and efficiency of the fifth-generation (5G) millimeter-wave (mmWave) wireless communication by obviating the propagation and blockage issues. On the other hand, the great flexibility of unmanned aerial vehicles (UAVs) has made them effective gadgets to enhance the coverage of wireless communication networks. Combining these two emerging technologies, the RIS-outfitted UAV (RISoUAV) is a promising solution for providing line-of-sight (LoS) wireless links for mobile targets (MTs) in obstructed high-dense urban areas. In this light, high-speed real-time communication is essential for some vital municipal services like ambulances, fire engines, security guards, police, etc. This important goal is achievable thanks to the RISoUAV-assisted 5G/quasi-optic wireless communication. This paper develops a framework for optimal navigation of a team of RISoUAVs for maintaining LoS links with a team of ground vehicles in a dense urban area. The trajectories of the RISoUAVs are optimized considering the energy efficiency, communication channel gains, and constraints associated with RISoUAVs motion and LoS service. A consensus-based coordinating approach is adopted to coordinate the RISoUAVs navigation to cover all MTs under a good quality of service. Simulation results show the effectiveness of the method. Note to Practitioners: In this paper, we consider a scenario where vehicles need to have high-speed, uninterrupted data links in obstructed, highly dense urban environments. Due to spectrum crunch, the data links are increasingly likely to rely on a high-frequency spectrum, including mmWave with quasi-optic nature, visible light communications, or even laser. However, the obstructed LoS and propagation are critical issues with the 5G and beyond as they rely on the availability of an unobstructed path (e.g., the LoS or a quality reflective path). On the other hand, the RIS performs as a passive reflective element that provides an indirect LoS link, a one-bounce channel, to improve the performance and efficiency of mmWave, and beyond, wireless communication networks. UAVs equipped with RISs are suggested in this paper to be adopted as aerial transponders to reflect signals and facilitate communication in high-density environments. Therefore, the problem of UAV navigation and 3D trajectory planning should be addressed regarding the application, particularly, for providing LoS service for mobile vehicles with arbitrary directions. Autonomous navigation of RISoUAVs for LoS wireless communication is a natural multi-dimensional extension of autonomous navigation with obstacle avoidance where regions in which LoS communication is lost are viewed as obstacles to avoid. However, the environment and valid LoS links can change dynamically due to moving vehicles in the obstructed environment. This makes the navigation design an NP-hard problem that is tackled in this paper by developing an effective navigation program

Correlated adatom trimer on metal surface: A continuous time quantum Monte Carlo study

The problem of three interacting Kondo impurities is solved within a numerically exact continuous time quantum Monte Carlo scheme. A suppression of the Kondo resonance by interatomic exchange interactions for different cluster geometries is investigated. It is shown that a drastic difference between the Heisenberg and Ising cases appears for antiferromagnetically coupled adatoms. The effects of magnetic frustrations in the adatom trimer are investigated, and possible connections with available experimental data are discussed.Comment: 4 pages, 4 figure

A cloud-fog computing framework for real-time energy management in multi-microgrid system utilizing deep reinforcement learning

Uncertainties in a microgrid (MG) result in challenges in reaching the optimal production-consumption balance via the energy management system (EMS). Therefore, multi-MG systems are proposed to achieve more optimality with stability. However, the EMS yet faces more uncertainties due to the increased number of renewable energy resources in multi-microgrids. Therefore, the use of a battery energy storage system (BESS) is crucial to manage these uncertainties. BESSs impose huge investment and operation costs, so it is important to consider their optimal planning and operation to maximize their benefits and lifespan. Model-based optimization approaches are used by formulating the EMS problem based on the complete system models under uncertainties. However, this assumption is usually impractical due to the prohibitive complexity and computational burden of solving a large nonlinear problem with many uncertain variables subject to privacy policies. This paper employs the deep reinforcement learning (DRL) technique to handle uncertainties associated with the large number of uncertain variables in EMS for multi-MG systems. An auxiliary cloud-fog computing framework is proposed for the DRL agents, which includes sufficient storage space, computational resources, and communication infrastructure among MGs. Simulation results in Matlab reveal that the optimality of the EMS is improved by 15 % on average by utilizing the auxiliary computing framework

Autonomous Guidance of an Aerial Drone for Maintaining an Effective Wireless Communication Link with a Moving Node Using an Intelligent Reflecting Surface

The excellent 3D mobility has made aerial drones (ADs) good candidates to improve the coverage of wireless communication networks. However, the effectiveness/efficiency of an AD (as an aerial active relay) is questionable for holding a continuous line-of-sight (LoS) link with a moving node (MN) in fifth-generation (5G) millimeter-wave (mmWave) wireless networks due to the signal propagations/blockage issues. Nevertheless, intelligent reflecting surface (IRS) technology has been introduced as a useful and energy-efficient method to improve the spectrum efficiency of 5G networks. In this paper, an AD equipped with IRS is proposed and autonomously navigated to maintain a continuous wireless link with an MN. The MN can be a vehicle moving through a dense urban environment. Simulation results corroborate the effectiveness of the method

Explicit Impedance Modeling and Shaping of Grid-Connected Converters via an Enhanced PLL for Stabilizing the Weak Grid Connection

The voltage source converters (VSCs) are used to interface and control the renewable energy resources that are integrated into the power grids. However, a weak grid connection raises a stability problem for grid synchronization of the grid-feeding current-controlled VSCs (CCVSCs). This paper handles modeling and controller design for stabilizing the weak grid connection of CCVSCs. The impedance modeling/shaping of the VSC has been recognized as an effective tool to analyze and design the dynamics of the VSC. But an explicit and accurate impedance model of the CCVSC is required. Particularly, modeling the impact of the phase-locked loop (PLL) synchronization unit on the impedance model of the CCVSC is complex. Therefore, at first, an efficient impedance model of the CCVSC is developed while the impact of the PLL is rigorously considered through a complex procedure that results in an explicit/accurate impedance model. The developed impedance model is used to conduct passivity/weak grid connection stability analysis to clarify the underlying causes of instability problems. Then, a novel PLL, with an in-loop low-pass filter (LPF) to account for harmonics/asymmetries, is proposed with enhanced characteristics using the state feedback control. The impedance shaping method (with the aid of the impedance model) is utilized to design the state feedback gains. The state feedback loops provide degrees of freedom for bandwidth design of the PLL considering the current/power control loops and stabilize the system under weak grid connection/distorted conditions. Simulation results prove the accuracy and effectiveness of the models