Transient stability is important in power systems. Disturbances like faults need to be segregated to restore transient stability. A comprehensive review of fault diagnosing methods in the power transmission system is presented in this paper. Typically, voltage and current samples are deployed for analysis. Three tasks/topics; fault detection, classification, and location are presented separately to convey a more logical and comprehensive understanding of the concepts. Feature extractions, transformations with dimensionality reduction methods are discussed. Fault classification and location techniques largely use artificial intelligence (AI) and signal processing methods. After the discussion of overall methods and concepts, advancements and future aspects are discussed. Generalized strengths and weaknesses of different AI and machine learning-based algorithms are assessed. A comparison of different fault detection, classification, and location methods is also presented considering features, inputs, complexity, system used and results. This paper may serve as a guideline for the researchers to understand different methods and techniques in this field.

The UAE per capita energy consumption is one of the highest in the world. Since the energy sector is the center of most ecological problems facing the world today, eco-efficiency and eco-innovations are at the top of the sustainability agenda in most countries. The UAE “Green Economy for Sustainable Development” (2012–2021) aims to position the country as a center for the export and re-export of green products and technologies. In light of the above, the focus of this paper is to present a smart plug system for monitoring and controlling household energy consumption using a mobile application. The smart plug system is an essential component in smart grids as it provides real-time high-resolution information for distribution companies to aid them in decision-making. In addition, the study measures the perceived usefulness and satisfaction of the smart plug system and its mobile application in the UAE. The paper makes an important theoretical contribution by including environmental concern as an additional variable to a well-established information systems success model. Our findings suggest that the smart plug system provides users with convenient access to information regarding their personal energy consumption and allows them to control their per capital energy consumptions via the mobile application at very low costs. Further, we validated our theoretical model using structural equation modeling and conclude that environmental concern has an indirect impact on the perceived satisfaction and both an indirect and a direct impact on the perceived usefulness of the smart plug system. The practical implications of our study suggest that per capita energy consumption is likely to significantly decrease with wide adoption of the smart plug system in the UAE

Heat pumps can provide domestic heating at a cost that is competitive with oil heating in particular. If the electricity supply contains a significant amount of renewable generation, a move from fossil fuel heating to heat pumps can reduce greenhouse gas emissions. The inherent thermal storage of heat pump installations can also provide the electricity supplier with valuable flexibility. The increase in heat pump installations in the UK and Europe in the last few years poses a challenge for low‐voltage networks, because of the use of induction motors to drive the pump compressors. The induction motor load tends to depress voltage, especially on starting. The study includes experimental results, dynamic load modelling, comparison of experimental results and simulation results for various levels of heat pump deployment. The simulations are based on a generic test network designed to capture the main characteristics of UK distribution system practice. The simulations employ DIgSlILENT Power Factory to facilitate dynamic simulations that focus on starting current, voltage variations, active power, reactive power and switching transients.

The food and drink industry is gradually gaining sustainability pressure due to the high carbon emissions rate and limited availability of traditional energy supplies. Thus, it is essential to consider energy efficiency and decarbonisation of the ever-expanding food and drink industry. Ohmic heating technology is a highly energy-efficient and quick method of electrically heating food products. It uses the resistance of the food material to convert electrical energy into heat. However, the heating rate of ohmic heating depends on several process variables, such as electrical conductivity, voltage gradient, and voltage frequency. Therefore, it is important to study and understand the effects of these process variables to optimise the modelling and control of ohmic heating systems to obtain desirable output from food products. Hence, this study presents a review of the effects of process parameters on nutritional and organoleptic qualities, product yields, and energy efficiency of ohmic heating, along with its various industrial applications. The technology shows promising advancements in colour and nutritional quality, increasing energy efficiency, shorter processing times, and higher product yields compared to conventional heating processes.

As solar energy costs continue to drop, the number of large-scale deployment projects increases, and the need for different analysis models for photovoltaic (PV) modules in both academia and industry rises. This paper proposes a modified equivalent-circuit model for PV modules. A PV module comprises several series-connected PV cells, to generate more electrical power, where each PV cell has an internal shunt resistance. Our proposed model simplifies the standard one-diode equivalent-circuit (SEC) model by removing the shunt resistance and including its effect on the diode part of the circuit, while retaining the original model accuracy. Our proposed equivalent circuit, called here a modified SEC (MSEC), has less number of circuit elements. All of the PV cells are assumed operating under the same ambient conditions where they share the same electric voltage and current values. To ensure the simplification did not come at a reduction in the accuracy of the SEC model, we validate our MSEC model by simulating both under the same conditions, calculate, and compare their current/voltage (I/V) characteristics. Our results validate the accuracy of our model with the difference between the two models falling below 1%. Therefore, the proposed model can be adopted as an alternative representation of the equivalent circuit for PV cells and modules.

Modern induction furnace draws heavy current with considerable distortion in the current waveform. This heavy distorted current causes distortion in the system voltage. Owing to the insulation limitations at 11 KV line, it is very taxing for modern power quality analyzers to capture the exact distorted voltage waveform. However the distorted waveform of current with high amplitude, drawn by induction furnace, can be captured by these analyzers by virtue of the appropriate CT ratios of their current clamps. By using the FFT of the distorted current waveform, a new mathematical approach using MATLAB has been developed in this paper for the exact modeling of distorted voltage waveform resulted in by distorted current waveform. Finally, this new approach has further been worked out to derive mathematical relation to compute the THD_v which also shows its trend as a function of distance between the supply (utility) and Induction furnace load.