The stability analysis is one of the most important elements to describe the performance of AC drive systems under both dynamic and steady-state operating circumstances. This is particularly essential because electric motors operate over a wide range of speeds and utilize complex control systems such as field-oriented control (FOC). This study establishes a small-signal stability analysis (SSSA) in a 1-horsepower vector-controlled Y-connected three-phase induction motor (YCTPIM) drive during an insulated gate bipolar transistor short-circuits failure (IGBT-SCF). In the beginning, a vector control system that is based on the indirect rotor FOC (IRFOC) method is described for post-fault functioning of the YCTPIM while the IGBT-SCF is taking place. After that, a small-signal model of the system that has been provided is explored. This model is based on a voltage-current model, and it is constructed by linearizing the non-linear dynamic equations of the system. During IGBT-SCF, an IRFOC strategy as well as SSSA operations are carried out on the 1-HP, 380 V, and YCTPIM. In this research, both analytical and simulation-based methodologies are applied.

This work presents the novel maximum power point tracking (MPPT) approach for a small 50 W photovoltaic (PV) system using the dc-dc converter. The method of modeling of PV module is discussed. The firefly (FFY) algorithm and the perturbation and observation (P&O) algorithm are combined to implement MPPT of the PV system connected to battery load. The operating principle is discussed in detail and steady-state analysis of the proposed system is implemented through simulation. The charging profile of the 7.5 Ah VRL battery is also studied using simulation. Furthermore, a low-cost microcontroller-based experimental setup rated at 50 W system connected to battery load was built to implement a hybrid FFY-P&O algorithm. The experimental results are in same as the simulation result. In contrast to the traditional P&O approach, it demonstrated the quick and efficient maximum power point operation triggered by a sudden transition in the environment.

The self-aligned hybrid carrier-based pulse-width modulation (PWM) for modular multilevel converters (MMC) based on decentralized control is proposed in this paper. It is based on parallel cells in a submodule (SM) using self-aligned hybrid carrier-based PWM, which combines the concept of level-shifted carrier-based PWM (LSC-PWM) and phase-shifted carrier-based PWM (PSC-PWM) methods. By implementing a decentralized control system digitally, hybrid carriers align themselves. Each SM interacts with the other SMs and each parallel cell in an SM communicates with the other cells to generate hybrid carriers. The proposed control strategy makes advantage of the redundancy idea by adding or removing a cell in the case of cell malfunction and system reconfiguration. A current balancing method is incorporated into the decentralized control system to ensure current balance among parallel cells in an SM. The simulation results illustrate the effectiveness of the presented control method in piecewise linear electrical circuit simulation (PLECS) software.

This research work modelled and optimized the hybrid microgrid energy system for electricity generation at the University of Abuja, Nigeria, using PV, wind, diesel, and battery renewable energy resources. The model and optimization of the system are performed through HOMER software. The estimated university average annual power consumption is 2355 kWh/day, and the optimal load demand is 313.40 kWp. The PV/wind/diesel/ converter/battery hybrid system has the lowest cost of energy (COE) of 0.1616 $/kWh, operating cost of $50,592, and net present cost (NPC) of $1,795,026 but diesel/wind/converter/battery hybrid system has highest COE of 0.4242 $/kWh and NPC of $4,710,983. The optimal total electricity generated is 1,272,778 kWh/yr while electricity generated by PV contribute the highest energy of 1,030,485 kWh/yr (81%), whereas diesel generator and wind produced energy of 93,927 kWh/yr (7.38%) and 148,366 kWh/yr (11.7%) respectively. The wind/diesel/converter/battery hybrid system produced carbon dioxide (CO2) of 557,749 kg/yr. The most environmentally friendly is the wind/PV/battery and PV/battery hybrid system without pollutants emissions, but the diesel/wind/battery hybrid system has the highest rate of pollutants emissions. The result shows that PV’s electrical power is extremely high from February to June, which causes a high rate of irradiance within the specified period.

Problems with voltage and stability have arisen as a result of the dramatic development in renewable energy generating units, notably solar energy systems linked to low and medium voltage networks, and the influence of active loads that vary rapidly from time to time during the day. Because reactive power is directly proportional to voltage, its use to renewable energy producing units can only improve their efficiency. Better performance for these controllers is possible via the usage of several controller types. In this paper, we use a salp swarm optimization algorithm (SSA) to design fractional order proportional-integral (FO-PI) controllers, whose job it is to regulate the active and reactive power of solar inverters by compensating for the overvoltage and undervoltage presented by the inverters' ability to absorb and produce reactive power. After that, we compared the FO-PI controller's results to those of the standard PI controller. Grid-connected photovoltaic (PV) system modeling and simulation were performed using the MATLAB/ Simulink modeling and simulation tools. After that, the full PV system was simulated in the most likely situations across a range of grid and weather conditions. We may infer from the simulation results that this model is credible, reliable, and applicable to the analysis of grid-connected PV systems.

Wireless Networked Control System (WNCS) is made up of an actuator, sensor, and controller that communicates through a wireless network rather than typical point-to-point cable connections. Lower maintenance costs, greater flexibility, and increased safety are the main WNCS advantages, so as a result, it has attracted a lot of researchers. Nevertheless, time delays and packet losses in wireless data transmission are classified as complicated problems, which impair WNCS output accuracy and may influence the overall system stability. Integer-Order PI-PD (PI-PD) and Fractional-Order PI-PD (FOPI-FOPD) controllers are proposed to reduce the impact of the control signal transmission's time delay and improve system performance. Matlab Simulink and True-time simulator are used to simulate the WNCS, and ZigBee protocol is used in transceiving the control signal between the controller and the system. Rotary Inverted Pendulum (RIP) acted as the controller's objective. The Grey Wolf Optimization (GWO) technique is utilized to evaluate the best controller parameters. Xbee S2 modules are used to implement the signal transmission process over ZigBee protocol. The FOPI-FOPD controller outperforms the PI-PD controller in the simulation and experimental results in decreasing the influence of time delay on system stability

A quick, reliable, and accurate fault location approach is essential in underground power systems protection. Being the most optimistic research topic of electrical power systems, this article presents an optimized algorithm for fault location in multi-end underground cables using travelling waves. Existing algorithms based on wavelet theory have fewer reliability and accuracy issues that raise an error to the power systems in fault location. The proposed layout presents a multiterminal underground cables system where the entire system is segregated into several fault identification sections where this model identifies the faulty section and the faulty half. Voltage and current wave transient at the mid-point of each fault locator are taken into account to eliminate the time-synchronous error. Traveling waves models are modelled using Bewley diagrams. Detecting the first and second traveling wave transient at both ends of each cable keeps the system reliable. Extensive simulations are simulated using the alternative transient program (ATP) to discriminate, identify, and locate several faults, while the system can also validate the faults near the busbar. The model is developed in MATLAB, and the obtained results depict the proposed algorithm's higher accuracy in fault location.

Quadcopters are popular UAVs owing to their compact size and maneuverability. Quadcopters are unmanned aircraft guided by remote control, and the demand for them is increasing due to their widespread surveillance, goods delivery, aerial photography, and defense applications. Nonlinear quadcopter operation makes control system implementation very challenging. In this paper, based on artificial intelligence (AI), we train a feedforward neural network (FFNN) controller of a traditional proportional integral derivative (PID). The conventional (PID) is generally tuned to improve the quadcopter control and performance. FFNN can perform offline learning between the inputs and outputs of the controller to learn its behavior. Once the learning is complete, we replace the PID controller with the neural network controller, to get a controller that can maintain system stability,and overcome the limitations of hardware implementation problems caused by the classical PID controller.

Innovative power electronic converters have emerged because of renewable energy expansion in the past two decades. Direct current DC grids can operate independently or connected to power grids. A DC grid has distributed generation (DG) units, such as solar panels and, fuel cells. It is necessary to have a DC-DC converter in DC grids to raise output voltage. Boost converters have limited voltage gain, and their switching stress is often equal to their output voltage. This work proposes a converter which gives high gain and less stress when compared to other recent converters. At 0.8 duty ratio, this converter produces an elevated gain of 59. An experimental prototype is built for the proposed converter and the results are presented.

A new approach for sizing a hybrid solar-PV-battery and biogas generator for power generation was suggested in this study, based on the variation of energy resources and the load profile. Biogas has enormous potential and numerous economic and social advantages. In this respect, the monthly solar radiation, temperature, and biogas produced from biomass resources were used as model inputs. This study considers the total annualized of the components for the feasibility analysis. HOMER Pro® software-based outcomes in the proposed methodology revealed that the proposed solar biogas hybrid system was sufficient to meet the load requirements of the village (Ain Farba village in the Hodh El Gharbi area located in the northeast of the Mauritania country) with a net present cost over the 25-year lifespan of 61,144 $ and the energy cost was determined to be 0.0473 $/kWh.