Journal of Electronics and Electrical Engineering

Design, Dynamic Modelling, Simulation and Control of a Solar Powered Sucker Rod Oil Pump

2025-01-13T10:37:25+08:00

The sucker rod pump is a crucial artificial lift system widely deployed in the oil industry to extract crude oil from producing wells. Accurate modelling of the sucker rod pump has become essential as a viable strategy for optimizing performance, and ensuring both efficient and economic operation. This paper presents a comprehensive methodology for the design, dynamic modelling, simulation, and control of a solar-powered sucker rod oil pump. It combines load modelling of the sucker rod pump using SolidWorks with design, dynamic modelling, simulation, and control of the solar microgrid in Matlab's Simscape and Simulink. The model seamlessly integrates the mechanical and electrical systems with 100%renewable energy to power the sucker rod pump system. This approach combines the solar photovoltaic system, battery charge control system, battery energy storage system, step-up transformer, and the squirrel cage induction motor, which serves as the electric motor prime mover. The surface pump model is first developed in SolidWorks and then converted to Simscape, the rating of the pump is then implemented as a load in the solar-powered electrical microgrid. Environmental conditions such as solar irradiance and ambient temperature for summer and winter are obtained from data repositories and included in the modelling and analysis of the overall system performance demonstrating stable operation, robustness, and resilience to changing environmental and operational conditions.

Investigation into Shaped Wide-Beam Reflectarray Surfaces Reflectors as Passive Repeaters in Wireless Networks

2024-12-12T14:17:18+08:00

This paper investigates the use of a Reflectarray Surface (RAS) to provide a shaped beam for use as a passive repeater in a wireless network. A shaped beam can be desirable as it may provide coverage over a dead-spot region. Examples of a flat-topped and sloping top shaped beams having a nominal beamwidth of 30^◦ and a steering angle of 40^◦ at 10 GHz are investigated, designed using the particle swarm optimizer in MATLAB. Measurement and simulation from CST show reasonable agreement to the 'array factor' synthesis patterns but display practical detuning effects that may limit this approach. Additionally, it was noted element factor has a more significant impact on such beam shaping.

Improved Transmission Line Relay Algorithm Based on Signum Function of Incremental Currents

2024-12-24T09:25:27+08:00

Transmission lines are a key part of the power system because they carry power from one end to the other. In case of a fault, the power transfer is perturbed, and the equipments on generation side as well as on the load side can get damaged. Transmission lines carry power from generation end to load end, so it is very important to keep the transmission lines protected. A swift protection system is necessary for the power system. For a quick protection system, rapid fault detection is crucial. A novel method for detecting as well as classifying the faults on transmission lines is reported in this paper. The direction of incremental current along the transmission line's two ends forms the base of this technique and uses a modified signum function. The effectiveness of the said technique is validated by simulating signals in a PSCAD/EMTDC environment on a 50 Hz, 230 kV, 5-bus network. The parameters considered in this study are the line loading, DC offset, fault location and the fault resistance (FR). The FR values considered for simulation purposes range from 0.01 ohm to 1000 ohms. Two types of line structures have been adopted, viz., first, a line connecting generator bus (PV bus) to a load bus (PQ bus) (L_GL) and second, a line connecting two generator buses (L_GG). Detailed results of this study show that the relay detects all internal faults with different loading levels and various FR values. The maximum operating time of the relay is ascertained as 4 ms. The technique has also been validated on IEEE 30-bus system.

Robust Nonlinear Control for Synchronising and Regulating Neural Activity

2024-12-12T12:13:29+08:00

Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.

The Threat of Adversarial Attacks against Machine Learning in Network Security: A Survey

2024-12-06T09:24:23+08:00

Machine learning models have made many decision support systems to be faster, more accurate and more efficient. However, applications of machine learning in network security face more disproportionate threat of active adversarial attacks compared to other domains. This is because machine learning applications in network security such as malware detection, intrusion detection, and spam filtering are by themselves adversarial in nature. In what could be considered an arm's race between attackers and defenders, adversaries constantly probe machine learning systems with inputs which are explicitly designed to bypass the system and induce a wrong prediction. In this survey, we first provide a taxonomy of machine learning techniques, tasks, and depth. We then introduce a classification of machine learning in network security applications. Next, we examine various adversarial attacks against machine learning in network security and introduce two classification approaches for adversarial attacks in network security. First, we classify adversarial attacks in network security based on a taxonomy of network security applications. Secondly, we categorize adversarial attacks in network security into a problem space vs. feature space dimensional classification model. We then analyze the various defenses against adversarial attacks on machine learning-based network security applications. We conclude by introducing an adversarial risk grid map and evaluate several existing adversarial attacks against machine learning in network security using the risk grid map. We also identify where each attack classification resides within the adversarial risk grid map.

A High-Power Hybrid-Strip Monopulse Antenna Array for Secondary Surveillance Radars

2024-12-02T11:27:44+08:00

This paper proposes a novel design of a high-power monopulse antenna array for secondary surveillance radars utilized in air traffic control systems. A novel technique of hybrid-strip technology is applied to the antenna array (composed of stripline for the feeding network and microstrip for the antenna elements) to minimize the effect of the transition between the feeding network and antenna elements. The antenna array consists of two identical mirrored halves. Each half is 2 rows × 6 columns. The antenna elements are rectangular microstrip patches with shorting vias while the feeding network is composed of a combination of synthesized stripline dividers/combiners. A backfill antenna along with a control network is utilized to achieve the monopulse technique and sidelobe suppression. The control network is a stripline rat race attached to couplers. The antenna array achieves an excellent monopulse performance at the uplink (1030 MHz) and the downlink (1090 MHz) with a return loss better than 15 dB, a realized gain of 22.2 dBi and two independent Sum and Diff channels with a Sum-to-Diff ratio of 30 dB at the antenna boresight. The antenna array can handle a peak power of up to 2.7 MW for long-range traffic detection and control. Such performance makes the proposed antenna array a perfect candidate for secondary surveillance radar.