Integrating renewable resources, such as wind and solar into the existing power system, has introduced new challenges due to their rapid fluctuations, which tends to decrease the reliability of the grid. One method to cope with this uncertainty and variability in generation is managing the demand side through direct load control. Thermostatically controlled appliances can play a significant role for this purpose; however, the system operator requires a reliable estimation about the magnitude of the load and how much it can be shifted. This article presents a novel methodology to formulate and forecast the control capacity of a population of thermostatically controlled appliances. In addition to that, this methodology can provide an estimation on how long the system can follow a desired level of power consumption and how the aggregated load would change once the controller stops (i.e., the payback). The performance of the proposed method was evaluated using a numerical simulator of a population of the loads. Simulation results show that the proposed method can provide a reliable estimation about controllability of the load in terms of minimum and maximum achievable load, the time interval that it can hold the load at a certain level, and how the uncontrolled load would behave after the control period.
Sequential reporting has the potential of reducing the duration of the reporting phase of the cooperative spectrum sensing (CSS) schemes, thereby increasing the overall system throughput. In this article, we study decision-based CSS using random medium-access sequential reporting and a K-out-of-M decision rule at the fusion center. Closed-form expressions are derived for the detection and false alarm probabilities as well as the average reporting time of two early termination sequential reporting schemes, assuming a reporting channel shared with the primary user (PU). Furthermore, a heuristic energy-based reporting priority scheme that favors cognitive radio (CR) terminals based on their capacity to detect the PU is proposed. Computer simulations are used to assess the accuracy of the derived expressions and to evaluate the proposed heuristic reporting priority scheme.
This account details the design and construction of a sophisticated tracking wheel for the accelerated aging of polymer insulators by subjecting them to surface contamination and high voltage. Automated control of wet-dry cycles is achieved by means of a computer-controlled lift mechanism that operates in tandem with the rotation. The applied voltage is continuously variable and can accommodate insulators of mixed lengths. The design incorporates a fail-safe control system that automates the selected test cycle, provides an intuitive user interface, and integrates multiple safety measures. This is achieved by implementing a programmable logic controller with digital and analog inputs and outputs. An associated ladder logic program automates the actuation of electromechanical hardware while also processing the inputs provided from control hardware, such as limit switches, optical encoders, variable frequency drives, and sensors. A touch-screen human interface module provides feedback and allows the user a means of input. Programmed fault detection, flood sensors, and a trapped key system increase the level of user safety and provide environmental and infrastructure protection.
In this article, a threshold-based induction motor fault diagnosis method is proposed using the measured stator current signal. A 0.25-HP three-phase squirrel-cage induction motor fed directly online is tested in the laboratory with various single- and multielectrical faults under six different loading conditions. The discrete wavelet transform (DWT) is chosen as the signal processing technique for the measured stator currents. The threshold and energy values at each decomposition level of the DWT processing results are evaluated. Threshold values appear to be more consistent than energy values at different measured data windows, and thus, the threshold at the decomposition level d8 is chosen as a fault indicator. Curve fitting equations are developed to calculate threshold values for the motor loadings that were not tested in experiments. The suitability using threshold values for induction motor fault diagnosis is further validated using two probabilistic methods, the correlation analysis and the confidence interval estimation.
Over the past several decades, there has been a constant increase in the use of unmanned aircraft systems (UASs). Hence, there has also been a growth in the number of control algorithms to service many applications embodied by these vehicles. Initially, UASs were made popular by the military for reconnaissance, intelligence, surveillance, and target acquisition (RISTA) applications. Nowadays, UASs are used for everything from crop surveys to tourism. Nowhere is this more evident than with a multi-rotor unmanned aerial vehicle (UAV). This paper presents a survey of control methods for multi-rotor systems, namely quadrotors. In doing so, we hope to visualize a clear path to what additional capabilities might be needed in the future. In our examination, we review many of the notable research organizations and their efforts to expand the utility of multi-rotor aircraft. We also summarize the basic literature definitions and control strategies for autonomous quadrotors.
