Connecting different renewable energy sources (RESs) to the electrical grids is presently being urged to fulfill the enormous need for electric power and to decrease traditional sources' ecological related issues, the so-called hybrid systems. Unfortunately, these hybrid systems suffer from the possible negative environmental impacts of the wind gusts in wind energy conversion systems (WECSs) that may degrade the overall system performance. Additionally, various severe faults may disconnect some RESs from the hybrid system, like three-phase faults. In this paper, the static synchronous compensator (STATCOM) is considered for both improving the performance of a hybrid system, contains WECS and photovoltaics (PVs) against wind gusts and maintaining the continuous operations of RESs during three-phase fault occur at the point of common coupling (PCC) between the RESs and the grid. The STATCOM is stimulated by two PI controllers regulating the reactive power flow between the STATCOM and the hybrid system at PCC and, consequently, regulating the voltage at PCC. A metaheuristic optimizer optimally schedules these two PI controllers based on whale optimization algorithm (WOA). The impartial comparison between the WOA dynamic performance and the particle swarm optimization as another optimization algorithm verifies the efficiency of the WOA for the near-optimal gain scheduling of the PI controller gains.

Optimal power flow (OPF) is one of the most significant electric power network control and management issues. Adding unreliable and intermittent renewable energy sources to the electrical grid increase and complicates the OPF issue, which calls for using modern optimization techniques to solve this issue. This work presents the optimal location and size of some FACTS devices in a hybrid power system containing stochastic wind and traditional thermal power plants considering OPF. The FACTS devices used are thyristor-controlled series compensator (TCSC), thyristor-controlled phase shifter (TCPS), and static var compensator (SVC). This optimal location and size of FACTS devices was determined by introducing a multi-objective function containing reserve costs for overestimation and penalty costs for underestimating intermittent renewable sources besides active power losses. The uncertainty in the wind power output is predicted using Weibull probability density functions. This multi-objective function is optimized using a hybrid technique, gradient-based optimizer (GBO), and moth–flame optimization algorithm (MFO).

Recently, there was a great focus on integrating renewable energy sources (RESs) into electrical power systems (hybrid systems) due to their many environmental and economic advantages. The output of most of these RESs is DC; some power electronic devices, including inverters, must be used to integrate these RESs into the electrical grid. Any maloperation, faults, or improper control in these power electronic devices will enormously affect these hybrid systems’ performance. This paper aims to mitigate the misfire and fire-through faults that occur at the switching of the inverter that connects three renewable sources: PV, wind, and the fuel cell to the grid. This mitigation of such inverter faults (misfire and fire-through) is performed through optimal tuning of the PI controller driving a dynamic voltage restorer (DVR) connected at the system’s AC side. The optimization technique used is particle swarm optimization (PSO). While mitigating these two inverter faults using the PI-PSO controller for the DVR, improved system performance through voltages, currents, and powers waveforms is achieved. Besides, the three renewable sources were kept in continuous operation without disconnection from the system during these faults.

Magnetron‐based marine radar technology is mature, affordable, reliable, and very effective for maritime safety applications. Commercial systems may be procured at a modest cost as compared to fully coherent solid‐state systems. Magnetron oscillators inherently generate random phase signals. Phase instability on a pulse‐to‐pulse basis impedes this class of marine radars from success in applications requiring coherency such as moving target indication (MTI) or in generating target imagery. This limitation may be overcome by incorporating radio frequency sampling and cross‐correlation of the transmit and receive signal technology to augment the current capability of available systems. In this research, the pulse train on transmit and receive is correlated in order to reject interference and detect image targets. Sampling the transmit signal and target echo on receive permits fully coherent processing. Marine radars traditionally operate non‐coherently, and as such, offer limited surveillance in clutter rich environments. In this study, the authors report on a non‐coherent marine radar that has been modified to produce a pseudo‐coherent or coherent‐on‐receive sensor system. This is crucial to MTI and target image formation. In laboratory experiments, they employed a magnetron oscillator‐based system to generate an inverse synthetic aperture radar image. The image was formed using four different algorithms: filtered back‐projection (FBP), time domain back‐projection (TDBP), an algebraic reconstruction technique, and frequency domain back‐projection. In their research, TDBP produces exquisite imagery of steel rods, and it is the standard developed in this study. FBP performed poorly as compared to all other algorithms.

The objective of this research is to improve monostatic radar detection performance via scan-to-scan processing (SSP) and scan rate modulation (SRM). This concept employs two mechanically scanned radars (MSRs), scanning at different scan rate. The scan rate modulation increases the probability of detection and scan-to-scan processing reduces the probability of false alarm. Our goal is to characterize the performance at the fusion area and to control the scan rate inside the fusion area to provide the minimum satisfactory probability of detection per scan with highest scan rate. Decreasing the fusion scan time increases the number of scans, which improve the cumulative probability of detection inside (and outside) the fusion area. The scan inside the fusion area is regulated for each antenna beam. Once a detection is declared the estimator predict the target appearance position and time within the fusion area. Then the controller uses a rule matrix to select the best scan rate to improve the total performance inside and outside the fusion area.

Non-coherent marine radar technology has matured over the past several decades. Researchers have developed coherent magnetron oscillator based marine radars by sampling the signals on transmit and receive [1]. We leverage this research to contribute to the science and technology of RF Tomography based upon exploitation of marine radar technology, and digital sampling / signal processing techniques. This requires many steps. First, selecting and modifying an affordable yet suitable marine radar. In this case, we employed a Furuno DRS25A. Second, by embedding an RF sampling circuit, we captured the various radar waveforms. Third, we digitized transmit and receive signals using a Signatec model PX1500 analog-to-digital converter (ADC). Next, we designed an experimental geometry to support image formation via RF Tomography. We applied Filtered Back Projection based upon the Projection-Slice Theorem, the Algebraic Reconstruction Technique, and classical Inverse Synthetic Aperture Radar imaging algorithms in order to match filter data and image targets. We provide both simulation analysis and experimental results in this paper.