Skyworks Solutions (United Kingdom)

Converter-dominated networks (CDN) not only limits the fault current, but also results in different fault current signatures with respect to what is typically observed during a fault with conventional generation. Major research activities across the globe (SANDIA and MIGRATE projects) have raised concerns that the commercially available distance relays are not reliable and could misoperate in the presence of inverter based resource(IBR).

Shunt reactors are one of the main apparatuses used in power systems to compensate the capacitive current resulting from the increasing demand of HV cable. Reducing their vibration and noise emission will lessen their environmental impact. In this study, the effects of different core lamination pressures on the vibration characteristics of shunt reactors were investigated experimental and analytically. Experimental modal analysis (EMA) and finite element analysis (FEA) were performed on a scaled-down yoke model to validate non-linear contact behaviour of the laminations. Modal and harmonic analysis supported by the results from EMA were used to investigate the influence of core lamination pressure on vibration velocity. These indicate that core lamination pressure is one of the key factors in characterising shunt reactor active part vibration and consequently can be used as an effective means to reduce vibration and noise emission.

The use of artificial intelligence (AI) and machine learning (ML) in digital marketing is becoming increasingly prevalent as technology continues to advance.These technologies have the potential to revolutionize the way that marketers reach and engage with consumers, encouraging new levels of personalization, automation, and efficiency.It examines the various applications of these technologies, including customer segmentation, predictive analytics, natural language processing, and chatbots.The paper also explores the challenges and ethical considerations associated with the use of AI and ML in marketing, as well as the future trends and possibilities in this field.This research highlights the benefits and limitations of AI and ML in digital marketing, and provides insights and recommendations for marketers seeking to leverage these technologies effectively.

Asset Management is one of the key aspects that utilities and industries rigorously follow in electrical sector to monitor, assess and diagnose the condition of the assets. This is a crucial step to ensure lower failure rates, reduce operational & maintenance costs and extend asset lifetime. Industrial motors play a critical role in process and manufacturing industries and hence reliability and availability of these motors is vital. Although vibration analysis has been used extensively for condition assessment of these motors, the technology viability is limited to large or HV motors and the cost associated with measuring equipment is high. In this paper, we propose a simple, effective, and affordable industrial motor pro-active asset management solution using protection relay based electrical signature analysis and demonstrate the efficacy of the proposed technology with practical case studies.

Transformers are one of the critical assets in the substation. In general, transformers are protected with differential or unit protection and the protection zone is defined by the location of CTs. Through faults or external faults are categorized as faults outside the differential protection zones and excessive currents due to an external fault is not detected by the differential protection. The life expectancy for liquid-immersed power transformers are largely influenced by the number of “through-fault” operations. To detect the through faults, it is essential to coordinate overcurrent protective devices with the transformer short-circuit withstand capability. In general, majority of through fault algorithms uses cumulative I²t to calculate the transformer remaining withstand capability. However, many practical cases are identified, where the conventional algorithms fail to accurately predict the maintenance alert. IEEE Std C57. 109-2018 provides transformer damage withstand capability curves based on the transformer category, exposure to frequent/in-frequent faults, duration and magnitude of the symmetrical fault currents subjected to the winding. This paper discusses and compares the conventional I²t algorithm with algorithm based on IEEE Std C57.109™ -2018. The transformer through fault scenarios are simulated using EMTP software and results are analyzed. A comparative analysis of transformer maintenance scheduling with different faults are presented with graphical results.

Perovskite Quantum Dots have excellent optical properties but low stability under high flux irradiation. In this work, a method to synthesize perovskite QDs‐polymer composite will be presented to overcome the high flux stability problem. As compared to pristine perovskite QDs, the perovskite QDs‐polymer composite shows higher stability under high flux condition in a long term.

This paper presents the design and validation of a Wide Area Monitoring and Control (WAMC) system for Fast Frequency Response (FFR) to address the challenges associated with reduced and non-uniformly distributed inertia in power systems. The WAMC system, designed for the power system in Great Britain, is termed "Enhanced Frequency Control Capability (EFCC)." It uses real time measurements from Phasor Measurement Units (PMUs) to monitor the system state in order to rapidly detect frequency disturbances and evaluate the magnitude of power imbalances. The impact of the disturbances on different parts of the network is considered to subsequently allocate the required response for different regions of the network, all within less than one second from the initiating event. The capabilities and characteristics of different resources (e.g., wind, energy storage, demand, etc.) are also evaluated and taken into account to achieve a suitable, optimized and coordinated response. Case studies using highly realistic hardware-in-the-loop setups are presented and these demonstrate that the proposed system is capable of detecting frequency events and deploying appropriate and coordinated responses in a timely fashion even with degraded communication conditions, thereby effectively enhancing the frequency control in future low-inertia systems and permitting higher penetrations of low-carbon and low-inertia energy sources.

This paper presents three types of linear model order reduction (MOR) technique, namely singular value decomposition (SVD)-based, Krylov-based, and modal truncationbased type applied to large-scale wind farm models. The first type includes a Balanced Truncation (BT) and Alternating Direction Implicit (ADI)-based BT method, while the second type encompasses a Rational Krylov (RK), and Iterative Rational Krylov Algorithm (IRKA) method. In the third type, a Subspace Accelerated MIMO Dominant Pole Algorithm (SAMDP) method is used. The effectiveness of these methods are tested on practicalsized wind farms with 90, 120 and 210 doubly-fed induction generators (DFIGs). Merits and demerits of each method are discussed in detail. The reduced order model (ROM) of wind farm is validated against the full order model (FOM) in term of frequency domain indices and waveform agreement at the point of common coupling (PCC).

Ancillaries have become a major source of revenue and profitability in the travel industry. Yet, conventional pricing strategies are based on business rules that are poorly optimized and do not respond to changing market conditions. This paper describes the dynamic pricing model developed by Deepair solutions, an AI technology provider for travel suppliers. We present a pricing model that provides dynamic pricing recommendations specific to each customer interaction and optimizes expected revenue per customer. The unique nature of personalized pricing provides the opportunity to search over the market space to find the optimal price-point of each ancillary for each customer, without violating customer privacy.